Nat Rep Spain FOG

8/3/2019 Nat Rep Spain FOG

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Short-term forecasting methods of fog, visibility and lowclouds in Spain. An inventory.

Daro Cano . Instituto Nacional de Meteorologa. Madrid, SpainEnric Terradellas . Instituto Nacional de Meteorologa. Barcelona, Spain

Abstract

The current situation in the field of short-term forecasting of fog, visibility and low-clouds at the SpanishInstituto Nacional de Meteorologa is analysed. Some plans that have been issued for future research anddevelopment are also presented. Most of the current communication is based on the analysis anddiscussion that was done during the INM National Seminar on short-term forecasts of fog, visibility andlow clouds held in Valladolid on 16-17 April 2002.

1. Introduction

The Instituto Nacional de Meteorologa (INM) is the organisation in charge of theweather watching and forecasting in Spain. Its operational units are the NationalForecasting Centre and 11 regional Watching and Forecasting Groups. The basic toolfor short-term forecasts is theHIRLAM-INM model, which is run 4 times a day at 0.5and 0.2-degree resolutions.

During recent years, the INM has made important advances in the forecasting of deepconvection, heavy rain and thunderstorms. On the other hand, less attention has been

paid to the fog forecasting.The geographic and climatic variety in Spain,from Atlantic regions with a similar climatethan Western Europe countries to near-subtropical regions, makes the fog forecasting acomplex issue. Visibility reduction may appear as a local or a mesoscale phenomenon and itsorigin may be extremely diverse, from winter

radiative-cooling fog in the interior of theIberian Peninsula to the outbreak of Saharan dust over the Canary Islands.

Fig. 1. Radiative-cooling fog over theCentral Spanish Plateau

Fig. 2. Outbreak of Saharan dust over theCanary Islands

The socio-economic impact of fog,

visibility reduction and low clouds ismainly relevant on the transportation
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sector: both, safety and reliability of ground, water and air transport are affected.

2. Understanding of the physical mechanisms involved in the formation andevolution of fog.

The INM, in co-operation with the University of Valladolid, rules theCentro de Investigacin de la Baja Atmsfera (CIBA) (Research Centre for the Lower Atmosphere). It is located at 4149 N 547 W, near Valladolid, in the northernSpanish plateau. The site is equipped with a 100-meter tower.

During the 80s and 90s, some experiments took place in theCentre (San Jos et al., 1985; Yage and Cano, 1994).

At the end of the 90s, the CIBA instrumentation had becomeobsolete. Since the site and the installations, especially the maintower, are very suitable for boundary-layer research, a project tore-instrument it was issued. The first step was done duringSeptember 1998, with a new experiment SABLES98- aimed tothe study of the stable atmospheric boundary layer (Cuxart et al.,2000b). As a result, some mathematical tools were developed for the identification and characterisation of structures and theanalysis of fluxes, most of them based on wavelet methods

(Terradellas et al., 2001; Cuxart et al., 2002). The next step was done during August2001, when the main tower was equipped with a permanent set of instruments. The re-instrumentation was carried out by theDanish Risoe National Laboratory, which alsotakes care of its calibration and maintenance.

Fig. 3. CIBA.Main tower.

3. Remote sensing

Some satellite-based products are currently implemented at the INM for watching andforecasting fog and low clouds.

The cloud classification product ismade usingTIROS/NOAA Advanced Very High Resolution

Radiometer (AVHRR)images(Garca-Pertierra, 1999). It is amultispectral classification based onsome thresholds previouslycalculated (Derrien et al., 1993). Atthis moment, it includes eight cloudtypes. Three different algorithmsare used, for daytime, transition periods and nighttime. The last oneis the most interesting with relationto fog, since visible images usually

give enough information to detectfog during light-time.Fig. 4. Cloud classification image.
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The first step consists of discriminating between cloudy and clear pixels. It ismade using the method described bySaunders and Kriebel (1988). Then, the

classification is made from the fourth (11 m) and the third channel (3.7 m)radiance. The algorithm allowsdiscriminating between fog/stratus,cumulus/stratocumulus andstratocumulus, although not between fogand low stratus.Fig. 5. Nighttime cloud classification from 11

and 3.7 m AVHRR channels

The fog detection at night is reasonably good. The main objections are the low periodicity of available images and the fact that in some Atlantic regions, stratocumulusare often misidentified as fog.

The sea surface temperature images, availableevery 6 hours, are also made from TIROSAVHRR data. The method to obtain them is based on the hypothesis that infrared channelsof satellite-borne radiometers measure the blackbody temperature of the underlyingsurface. A correction term depending on thesatellite zenith angle has to be added at every pixel. The image calibration is made from buoyand ship data.

Fig. 6 . Sea surface temperature

The SST images have proved to be a basic tool in the near-shore fog forecasts(Lpez and Izquierdo, 2001).

The Normalised Difference VegetationIndex (NDVI) is related to the proportionof photosynthetically absorbed radiation.

It is calculated from the visible and near-infrared AVHRR channels. The principleunderlying behind the physicalinterpretation of the index is explained in

Tucker (1979).

Fig. 7. NDVI image

Until present day, this index has been operationally used at the INM only for fire risk assessment (lvarez et al., 2001). Nevertheless, it is now under consideration the use of any physiographic product in fog forecasting.

As it is mentioned in the introduction, the Canary Islands are sometimes affected byoutbreaks of Saharan dust that, besides serious problems in public health andagriculture, can considerably reduce the visibility (Carlson and Prospero, 1972). A
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remote sensing based procedure is operationally used to forecast such events (Rpodaset al., 2001). It uses images provided by theTotal Ozone Mapping Spectrometer (TOMS)aboard Nimbus-7. The instrument is able to detect ultraviolet absorbingaerosols, such as dust or ash plumes, from the difference between the observed and theRayleigh scattering (Torres et al., 1998).

The remaining problems are the lack of information on the aerosol height, and theundetectability of aerosols below 1 km or in cloudy conditions. The TOMS product isused in combination with the isentropic trajectories supplied by HIRLAM.

In the background of theEUMETSAT SAF on Support to Nowcasting and Very ShortRange Forecasting (NWC SAF), lead by the INM,Mto-Franceis currentlydeveloping some products that will be based onMeteosat Second Generation (MSG) data: a cloud mask, a cloud classification algorithm (including dust) and cloud toptemperature and height images. They will be available by mid-2003. The higher periodicity of the images (15 minutes) will improve the fog watching.

Finally, it has to be pointed that satellite images and other remote sensing productsreach an excellent value in combination with ground observations for the analysis of typical meteorological structures associated with fog occurrence. Such analyses may provide some conceptual models (Cano et al, 2001a; Cano et al., 2001b) very useful for operational forecasters.

4. 3D models

At present, the INM operationally runs the HIRLAM model at 0.2 and 0.5-degreeresolutions. It has been decided to keep an unchanged version during 2-3 years.

For this reason, the current versiondoes not contain the lastdevelopments that have beenincorporated into the HIRLAMreference system. It is expected toshift to a new version in 2003.

Fig. 8. Surface as mosaic of tiles (Avissar andPielke, 1989)

Some changes that will be

introduced in the new version maylead to decisive improvements in theshort-range fog forecasts, either through the direct model outputs or through post-process products.These improvements will mainlycome from:

A new surface treatment (Avissar and Pielke, 1989), including new climate files vegetation, soil texture-, fully re-coded surface analysis package (Navascus et al.,2001), soil scheme for 3 land fractions (Rodrguez et al, 2001), post-process

providing 2-m temperature and humidity and 10-m wind over different tiles.
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The new boundary layer scheme will be based on a wet CBR scheme, allowingturbulence-condensation interaction. It will include the treatment of shallowconvection.

New routines for convection and condensation: the convection will be based on theKain-Fritsch scheme (Kain and Fritsch, 1990) and the large-scale condensation onthe Rasch-Kristjansson scheme, which includes the microphysics of the processes(Rasch and Kristjansson, 1998).

A better horizontal resolution (probably 0.15 and 0.05 degrees) will be able toresolve lower scale processes. Especially relevant will be the improvement in therepresentation of the orography, very smoothed in the current version.

Some other developments are at present under consideration:

Fig. 9a. Representation of the orography (0.5-degree resolution).

Fig. 9b. Representation of the orography (0.05-degree resolution).

Fig. 10. ELDAS EU project (Developmentof a land dataassimilation system)

Analysis of hydrometeors and soil/surface variables

Mesoscale Data Assimilation System, allowing the dataassimilation from different sources (conventionalobservations, radar, satellite, aircraft data,)

Soil moisture data assimilation (ELDASEU project)

Operational forecasters in Spain use McIdas system for information management. At present, direct HIRLAMoutputs at sigma-levels are not ingested into the system. The benefit of using these outputs at the lowest levels for fogforecasting is under consideration. The advantage of directmodel outputs seems to be obvious when statistical methodsare used.

On the other hand, the new version will provide some fields (i. e. soil water contents)that probably might be useful for the initialisation of statistical methods or post-process products.
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Plans for periodical non-operational runs of the new HIRLAM version have beenissued. It will allow assessing the possible role of the new information sources (i. e.new fields) in the forecasting operativity and therefore considering its ingestion into theMcIdas system.

5. 1D models

At present, the INM is developing a 1D model especially aimed to fog forecasting(Terradellas and Cuxart, 2001). Although, there is only an experimental version of it,the model is run every 6 hours for the Madrid-Barajas airport.

By the moment, the column is initialised from the HIRLAM analysis. A module tocombine radiosonde, profiler and HIRLAM data is under development. The fact that aradiosonde is daily released at 1800 UTC from the Madrid airport will be very usefulwhen the model become operational. Plans to run it for other sounding stations have been issued.

The model is based on the CBR turbulence scheme (Cuxart et al., 2000a) that uses theturbulent kinetic energy as forecasting magnitude. It is expected to substitute the present dry turbulence scheme by a new one allowing interaction between turbulenceand condensation.

Fig. 11. 24 hour run of the 1D model. Temperature (left) and wind direction (right)forecasts without climatological forcings (up) and with climatological forcings (down)

The horizontal structure of the atmospheric fields, necessary to evaluate some terms of the movement equations is calculated from the HIRLAM analysis and forecasts. Inorder to doing so, the HIRLAM outputs at the four nearest grid-points are ingested bythe 1D model.
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In the present version, the ground heat and moisture fluxes are read from HIRLAM. Onthe other hand, the momentum flux is calculated using the Monin-Obukhov theory. Asimplified surface heat balance equation is being tested.

Since small-scale structures not resolved by the operational HIRLAM model (0.2-

degree resolution), especially katabatic flows, play a very important role in the fogdevelopment (Cano et al., 2001b), they are being simulated in the 1D model through thesubstitution, under suitable conditions, of HIRLAM advections or mass divergence byother values estimated from climatological considerations.

Plans for future improvements are based in the progressive substitution of differentroutines by others from the HIRLAM reference system.

Since the model is in a development phase, its skill has not been evaluated yet.

6. The FOG SI index

The FOG stability index, a tool developed by the US Air Weather Service, is applied bysome forecasting groups as a checklist item. It is never used as the only decisionmethod. It seems to be able to discriminate the fog occurrence in some areas andmeteorological situations, especially during the winter season (Guerrero and Jans,1996). Its expression is:

FSI = (Tsfc-T850) + (Tsfc-Td,sfc) + w850 (1),

where Tsfc,T850 are the surface and 850-hPa air temperature, Td,sfcthe surface dew point(in C) and w850the wind (in knots).

7. Statistical methods

A method based on Kalman filters is operationally used in the INM for short andmedium-range temperature forecasts (extreme and main synoptic-hour temperatures).The short-term forecasts are performed by filtering the HIRLAM outputs. Forecasts of other numerical magnitudes using the same method are also available, although notcompletely validated yet (Del Pino, 2001). A similar method is at present under

development for visibility forecasting.The Kalman filters establish a comparison between observations and model outputsduring a certain period. Since the numerical models do not provide a visibility forecast,the method will present some differences with respect to the already implemented ones,making use of other variables that are supposed to be related to visibility.

A method based on a neural network (back-propagation algorithm) is experimentallyused in fog occurrence forecasting for Valladolid and Salamanca airports. The network uses observational data (temperature, dew point and wind speed at 1800 UTC), predicted cloudiness at 0600 UTC, persistence and night duration as predicting

variables. First verification tests for the Valladolid airport show highly encouragingresults.
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A method based on the analogy between different meteorological configurations isoperationally used at the INM for quantitative precipitation forecasts. The basichypothesis is that similar configurations cause a similar amount of precipitation. Themethod works with a reference database containingECMWFreanalyses and

observational data from 1979 to 1997 (Fernndez et al., 2001). At present, the possibility of developing a similar tool for other variables, the fog occurrence betweenthem, is being analysed.

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en Madrid y Castilla-La Mancha. V Simposio Nacional de Prediccin del INM, Madrid, (proc.).(*) Cano, D., Casado, J., Palacio, I., Tllez, B., Terradellas, E. and Cuxart, J., 2001b.Importancia de losflujos catabticos en las predicciones para el aeropuerto de Madrid-Barajas. V Simposio Nacional de Prediccin del INM, Madrid, (proc.).

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meteorolgicas en superficie. V Simposio Nacional de Prediccin del INM, Madrid (proc.).Derrien, M., Farki, B., Harang, L., Legleau, H., Noyalet, A., Pochic, D. and Sairouni, A., 1993.

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(*) Garca-Pertierra, M. M., 1999.Clasificacin nubosa (AVRR) de noche. IV Simposio Nacional dePrediccin del INM, Madrid., (proc., 339-343).

(*) Guerrero, M. J. and Jans, A., 1996. Aplicabilidad del ndice FOG SI a la prediccin de nieblas enel aeropuerto de Son San Juan, Palma de Mallorca. III Simposio Nacional de Prediccin delINM, Madrid, (proc., 401-408).

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(*) in Spanish
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