Transcript Fog forecasting at FMI

Fog forecasting at FMI
- forecaster’s view
Vesa Nietosvaara
Photo: Jenni Teittinen
Contents
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Introduction
Climatology
Rules of thumb
Localizing fog
Satellite information
Model support
Observations
Real life
Case studies
Introduction
• At FMI fog is forecasted for:
– General public in the media (overview)
– Aviation forecasts (as precisely as possible)
– Marine forecasts (overview -precise)
• The central service at 6th floor takes care of
most of the general and marine weather
forecasting
• Regional services: especially aviation
forecasting
Climatology
• Stratus and fog very common in Finland.
The probability of St/fog is at its maximum
during late spring and winter.
• For example, in southern and central
Finland fog is observed roughly 15-25% of
the days in winter.
• In summer the fog probability is only 510%.
More climatology
• “Fog axis” at upslopes of Salpauselkä (100
km north of south coast)
• Northern Finland hills: often foggy
(Rovaniemi airport)
• Duration of fog:
– advection fog Oct-Dec: even days
– Radiation fog: early summer vs. late summer:
in early summer not so frequent, but more
persistent!
Rules of thumb
• The basic rules known to each forecaster:
– For example, the requirements for the formation of
radiation fog
– Advection fog rules
– Plus a lot of silent knowledge, especially at the
aviation forecasting !
• Local knowledge and experience (based on
climatology):
- Air streams, wind directions favourable for fog
formation
Wind direction vs. fog probability
• A climatological study
within COST 722 is
being done currently
at FMI (Jukka
Julkunen, Rovaniemi)
• Fog climatology for
~10 selected airports
in Finland.
Localizing the fog
• Less and less manual SYNOPs and METARs.
• More automatization.
► fog mapping purely based on observations is very
coarse and unreliable.
• Satellite observations are crucial:
• MSG used, but not yet as effectively as we wish
• AVHRR traditionally the most used instrument
• Our experience is that even few observations
combined with satellite images allow a satisfactory
start for fog analysis
• A good mesoanalysis of the fog is needed!!
Satellite information
• Some examples of available satellite products at
FMI:
• AVHRR:
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daytime 0.6 + 0.9 + 10.8 μm combinations
daytime 0.6 + 1.6 + 10.8 μm combinations,
night-time 3.7 + 10.8 + 12.0 μm combinations,
night-time 3.7 – 10.8 μm difference images.
• Meteosat-8:
– As NOAA, but difference images not yet implemented
– Individual images: very little use
– MTP still the most used source of information !?
General experiences
• AVHRR superb in northern latitudes even
in Seviri era
• Gaps in passes during the afternoon and
night are problematic
• The 15-minute-interval for Meteosat-8 is
extremely valuable for nowcasting
purposes
Some other examples of the use of
satellite information
• Fog sheets and their relation to daytime
convection..
• Dissipation of fog
Fog sheets and their relation to
daytime convection..
Dissipation of fog
Model support
• The general forecasters work mostly with this
kind of model output when forecasting fog…
Model support
• Or with this kind of products…
Model support
• …or with anything they find from the
internet ...
http://meteo.icm.edu.pl
Model support
• But no real fog model is currently
available.
Surface observations
• While classical observations have
decreased, new observational data has
become available
– Ceilometers
– Mast obs
• Sounding data not adequate for fog
analysis purposes
• Even weather radar network can be used
in some cases
Real life
• Forecasters are aware of especially
difficult fog forecasting issues:
– Spring/early summer fog banks at sea
– Fog forming or not forming just prior to
sunrise?
– How to actually forecast the dissipation of the
fog?
– Evaluating visibility is very very difficult.
Case studies
• Irene Suomi: local fog case 8.9.2002 at
Gulf of Finland
• Leena Upola: fog case in northern Lapland
4.9.2003
Photo: Jenni Teittinen 8.9.02, Kruunuvuorenselkä
Case Study:
Marine Fog on the Coast of Helsinki
8.9.2002
``Yhtä sakeaa sumua olen kohdannut 35 vuoden aikana vain kolmasti.'‘
PORKKALANNIEMI 8.9.02
``Kun laiva oli miekassa, lähestyi tutkalla tehdyn havainnon mukaan etelästä purjevene, joka väisti kohti
rantaa (kadotti paikan todennäköisesti). Meiltä ei sitä optisesti sumun takia nähty, vain tutkalta. Jälkeenpäin
kuultiin, että kaksi purjevenettä oli harhautunut rantaan. Molemmissa oli ollut pakolaisia!!!! Auttamaan tullut
polisiisvene ajoi sekin kivikkoon! '' KUSTAANMIEKKA 8.9.02
``Koko Kruunuvuorenselkä oli paksussa sumussa, näkyvyys 50 m. Itse etenin kohti Hevossalmea tutkaa
hyväksi käyttäen. Koko Kruunuvuorenselkä oli täynnä veneitä, noin 20. Osa oli neljän, viiden veneen
ryhmissä paikallaan'' KRUUNIVUORENSELKÄ 8.9.02
Introduction
Dramatic and unexpected marine fog
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the inlet of Kustaanmiekka was closed by Helsinki Vessel Traffic Service for
about an hour in 8.9.2002 afternoon because several boats had got lost in
the ship lane
tens of boaters were caught by the fog during the day: several alarm notices
to the Maritime Rescue Co-ordination Centre in Helsinki (MRCC Helsinki)
weather conditions inland: warm and sunny late summer day
fogs fairly rare on Finnish coastal seas in autumn because surface waters
are typically warm after the summer
Case Study: Marine Fog on the Coast of Helsinki, 8.9.2002
Introduction
Methods and Goals of the Study
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Where and when? – mapping of the evolution of fog
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satellite data
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“in situ” observations (synoptic weather stations, boats, ships, the Coast Guard, etc.)
Why? – determination of physical conditions
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sea surface temperature (from satellite images processed by SYKE)
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meteorological factors (synoptic weather stations, soundings, mast observations)
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origin of the foggy air: reversed model run with SILAM dispersion model
Predictability? – consideration of the forecasting aspects
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as a meteorologist
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from the viewpoint of HIRLAM (HIgh Resolution Limited Area Model)
Case Study: Marine Fog on the Coast of Helsinki, 8.9.2002
Synoptic Weather Conditions
Case Study: Marine Fog on the Coast of Helsinki, 8.9.2002
Observed Fog Areas
8.9.2002 at 9 a.m. ± 1 h (local time)
8.9.2002 at 3 p.m. ± 1 h (local time)
Case Study: Marine Fog on the Coast of Helsinki, 8.9.2002
Observed Fog Areas
8.9.2002 at 6 p.m. ± 1 h (local time)
9.9.2002 at 9.09 a.m. (local time)
Case Study: Marine Fog on the Coast of Helsinki, 8.9.2002
Sea Surface Temperature
(Source: Suomen ympäristökeskus, SYKE)
Wind roses:
Inkoo Bågaskär
Helsinki Harmaja
28.8.-2.9.02
2.9.-8.9.02
Case Study: Marine Fog on the Coast of Helsinki, 8.9.2002
The Fog at Helsinki
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at 4 p.m.: fog patches on a
narrow zone parallel to the
coast (yellow)
later in the evening the fog
area becomes wider
at 6 p.m.: fog is observed
also at Harmaja and Isosaari
(grey)
wind direction changes ca
360 degrees within a day:
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land/sea breeze
phenomenon
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strengthening high pressure
there is correlation between
the width of the foggy area
and the wind direction
Case Study: Marine Fog on the Coast of Helsinki, 8.9.2002
Forecasting as a Meteorologist
Significant factors in fog
formation:
Difficulties in forecasting the
afternoon fog:
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sea surface temperature pattern:
due to upwelling, the sea surface
temperature was lower at the Finnish
coast compared to the other parts of
the Gulf of Finland and Baltic Sea
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the air had travelled a long distance
above warm sea before arriving in the
Finnish Coast
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strengthening high pressure and
related weakening of wind
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marine fogs fairly rare on autumn
sunny and warm weather was
expected inland => difficult to
estimate what will happen to the fog
during the day on a narrow zone of
cold sea surface
no indications of a dramatic fog
situation on satellite images
between 9 a.m. and 9 p.m. (local time)
only one synoptic weather station
(Kirkkonummi-Mäkiluoto) reported fog
at observation times
Case Study: Marine Fog on the Coast of Helsinki, 8.9.2002
Conclusions
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Fog evolution 7.-9.9.2002
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initial formation at night 7.-8.9.2002
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partial dissipation around noon
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movement and extent of fog patches in the afternoon determined by the local changes
in wind field
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gradual dissipation at Finnish coast during the following night as the wind turned to
north
Typical features of marine fog formation
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sea surface temperature pattern: sharp change in horizontal because of upwelling in
the northern Gulf of Finland
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foggy air travelling a long distance over warm water before arriving in the area of cold
sea surface
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strengthening of high pressure and related weakening of wind
Conclusions
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Forecasting: meteorologist
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sea surface temperature in major role in this case but also in any
marine fog case
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meteorologists need more tools to observe the fog => more
cooperation with other authorities?
Forecasting: HIRLAM
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progress from ENO to the new version
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results fairly good with climatological sea surface temperature =>
how about the effects of upwelling?
Occasionally fog in early morning
4.9.2003
Satellitepicture (NOAA 345),
(the first picture in this morning)
• Western Lapland is cleared up.
In north-western part some
upper clouds, developing
showers? (near the upperthrough)
• In eastern Lapland the
cloudcover is thinning, but low
stratus can be distinguished in
black colour.
• Green dots are EFRO and
EFPU
4.9. 02.18z
Wind forecast
• almost the same
wind speed at
EFRO and at EFPU
• weak wind helps
the fog formation
Military Metars in Pudasjärvi
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040250z 24004kt 4000 br few005 sct058 08/08 Q1007=
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040320z 24004kt 4000 br sct006 bkn062 08/08 Q1007=
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040350z 29005kt 5000 br bkn004 sct060 08/08 Q1008=
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040400z 29006kt 2000 dz ovc003 08/08 Q1008=
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040410z 29006kt 0800 fg ovc003 08/08 Q1008=
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040420z 28004kt 0500 45fg ovc002 09/08 Q1008=
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040450Z 27005kt 0300 fg ovc002 09/08 Q1008=
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040520z 28004kt 0400 fg vv002 09/08 Q1008=
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040550z 28005kt 0400 fg vv002 09/08 Q1009=
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040602Z 26004kt 3000 br OVC002 08/08 Q1009=
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040620Z 26004kt 8000 VV001 08/08 Q 1009=
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040650Z 23003kt 9999 sct003 bkn010 09/07 Q1009=
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040720z 21004kt 9999 sct010 10/9 Q 1009=
Conclusions
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The model and radar products are displayed in a way
which does not help in forecasting stratus.
Infrared or interpreted satellitepictures and surface
observations are useful in large scale: cloud edge is
approaching, a rough estimate of cloudbase.
Metar-observations twice in hour: almost realtime data,
but air temperature and dewpoint temperatures are
rounded off and information is lost, which is troublesome
when we are near saturation.
In this particular case we were able to say, that fog/stratus
is coming and dispersing in the accuracy of (+/- )3 hours
It isn’t nearly enough, what we are promised to do:
Limits for amending are very near each other in poor
weather!
Summary
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better realtime observations from ground to 1500ft
(significant cloud base): masts and profilers, low level
soudings?
Serviceable, practical tool especially for radiation fog
situation, where fog is developing at the same time in the
whole district, not advecting.
Practical = visual, graphic, easy to outline. It also tries to
warn in situations learned with experience (”rule of
thumb”):
Rapid temperature change, change in radiation balance,
(scattering/coming upper cloud), changing separation
between air temperature and dew-point temperature.