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Title: Institute%20of%20Meteorology%20and%20Water%20Management

Institute of Meteorology and Water Management
Extreme agrometeorological events early warning
and monitoring with use of satellite
information PIOTR STRUZIK Institute of
Meteorology and Water Management Kraków, POLAND
Institute of Meteorology and Water Management
  • Presentation outline
  • Introduction agrometeorological hazards.
  • Hazards and satellite data use
  • Drought
  • Floods
  • Fire hazards.
  • Heavy storms and extreme precipitation
  • 3. Conclusions.
  • 4. Recommendations (to be discussed)

  • Agriculture disasters
  • Agricultural disasters may not be as dramatic as
    a volcanic eruption or a hurricane, but they are
    by far the most damaging. Worldwide, drought
    alone has been responsible for millions of deaths
    and has cost hundreds of billions of dollars in
  • Different climatic events can trigger crop
    failures including
  • excess rainfall leading to flood damage or crop
  • heat waves,
  • drought,
  • fire,
  • unexpected cold snaps,
  • severe storms,
  • climate-related disease outbreaks,
  • insect invasions.

But also
Large-scale weather phenomena affect agriculture
world-wide by changing rainfall patterns El
Niño, La Niña (El Niño costs about 2 billion in
agricultural losses in the USA) Pacific Decadal
Oscillation. Regional (small scale) weather
phenomena Excessive rainfalls/ lack of
rain, Storms hail, strong wind, tornadoes, Fire
both natural and man induced, Flooding, Insects
and diseases favorable conditions
  • Satellite remote sensing provides a way to
    monitor worldwide agriculture.
  • Measurements of radiation balance and
    evapotranspiration provide information on energy
    and water exchange at the surface (pre-drought
    conditions, fire risk).
  • Cloud-cover, rainfall patterns, storm detection,
    fire detection, are useful both for warning and
    monitoring of extreme events
  • Vegetation/thermal index measurements
    (NDVI/EVI/VCI/TCI) record vegetation state and
    possible anomalies
  • High- and moderate-resolution sensors provide
    images of crop areas (pre-disease risk assessment
    / post disease damage assessment)

  • To consider actual and potential use of satellite
    information for agrometeorological hazards
    monitoring we have to look at
  • Types of Agromet Disasters
  • Phases of a Disaster
  • Effects of Disasters
  • Prevention, Mitigation
  • and Preparedness

fire management
detection and response
post-fire assessment.

Fire monitoring systems (space-based)
fuel biomass condition (living or dead)
biomass quantity moisture content vertical
and horizontal structure (continuity).
weather impact wind velocity, wind
direction, relative humidity,
precipitation, temperature.
topographic factors aspect (steepness,
orientation and position) of the terrain
elevation shape of the terrain (for
example, ridge, canyon, flat terrain).
Forest fire risk in Poland
Fires in Quebec Smoke continued to pour from
fires in the Quebec province of Canada on June 2,
2005. Scores of fires have been burning in the
area since the end of May. According to reports
from the Canadian Interagency Forest Fire Center,
at least 20 of the 83 fires burning as of June 2
were out of control. Nearly all the fires were
started by lightning.
Fires in Northern Territory, Australia In the
northern parts of Australias Northern Territory,
April and May are months when people conduct
planned burning in order to reduce underbrush and
prevent more damaging fires later in the dry
season. This image of Northern Territory captured
by the MODIS on NASAs Aqua satellite on May 17,
2005, shows many fires (marked in red) burning in
the region around Darwin. About 150 to 175
kilometers east and southeast of Darwin, the
fires are burning in the Kakadu National Park,
part of the ancestral lands of the country's
Aboriginal people. The traditional, often
ceremonial, burning that occurs at this season is
part of the relationship of people with the
landscape that has gone on in the region for
thousands of years.
Fires and Smoke in North Korea On May 3, 2005,
the Moderate Resolution Imaging Spectroradiometer
(MODIS) on NASAs Aqua satellite captured this
image of smoke pouring from dozens of fires
(marked in red) in North Korea. These fires could
be related to agricultural burning however, the
huge plumes of smoke blowing eastward from some
of the coastal fires suggest that those blazes
are forest or other wildland fires. Much of the
Korean Peninsulas precipitation falls between
June and September during the wet monsoon
phase. Therefore, these fires are burning at one
of the driest times of the year.
  • Drought
  • Drought is the most important weather-related
    natural disaster.
  • During 1967-1991, droughts affected 50 percent
    of the 2.8 billion people who suffered from all
    natural disasters and killed 35 percent of the
    3.5 million people who lost their lives to
    natural disasters.
  • We cannot avoid drought, and our predictions will
    never be perfect, but we can reduce its impacts.
  • Large-scale intensive droughts have been observed
    on all continents, leading to
  • - massive economic losses
  • - destruction of ecological resources
  • - food shortages
  • - starvation for millions of people
  • Reducing Drought Consequences
  • - Drought prediction
  • - Monitoring and early warning
  • - Assessment of impacts
  • - Response

Satellite information use
Drought Monitoring and Early Warning Rainfall,
surface wetness and temperature monitoring
multi-channel and multi-sensor data sources from
geostationary platforms (such as GOES, METEOSAT,
INSAT, GMS) and polar orbiting satellites (such
as NOAA, DMSP SSMI) have been used, or are
planned to be used. Estimated parameters are
precipitation intensity, amount, and coverage,
atmospheric moisture and winds, and surface
(soil) wetness (sometimes). Vegetation
monitoring vegetation condition monitoring is
currently possible, ranging from NOAA AVHRR data
at 1.1km resolution in a daily revisit, to
environmental satellites (LANDSAT etc.) in on in
a 8-16 day revisit with 10-30 m resolution. The
normalized difference vegetation index (NDVI) and
its anomalies (VCI), temperature condition index
(TCI) derived from the satellite data is accepted
worldwide for regional monitoring. Assessment of
drought impact high-resolution satellite sensors
from LANDSAT, SPOT, IRS, (among others) are being
used for the assessment of impacts in a few
areas, but in most cases this is not a
country-wide activity.
  • Satellite use for drought management support
  • GOES, METEOSAT, INSAT, GMS are used for
  • NOAA/AVHRR, IRS/WiFS, SPOT4/Vegetation are used
    for monitoring and early warning
  • DMSP/SSMI and IRS-P4 MSMR data should be
    investigated, together with the existing
    approaches, as a drought information
    evaluated for monitoring
  • LANDSAT,IRS,SPOT is used for GIS based drought
    management system

Drought in Brazil Rio Grande do Sul, the part
of Brazil in the center of this image, is one of
Brazils richest states. The state is Brazils
largest rice producer, second largest wheat
producer, and third largest corn and soybean
producer. During the summer of 2004/2005, this
heavily agricultural region plunged into severe
drought, its worst in 35 years. Little rain fell
between December and March, the summer months in
the Southern Hemisphere, and the cost to
agriculture could measure in the billions,
according to local news reports.
The image, a composite of data collected by
NASAs Moderate Resolution Imaging
Spectroradiometer (MODIS), shows where vegetation
was less dense and healthy than normal between
March 22 and April 6, 2005, compared to data
collected during the same period between 2000 and
Drought in East Africa Six successive years of
poor rain have left Eastern Africa in severe
drought. Rain typically falls between February
and June, and 2005 looked promising when rains
started to fall in January. The promise dried up,
however, when the rains stopped, leaving the
latter half of March and the first half of April
dry. The cumulative impact of poor rainfall on
plants is visible in this vegetation anomaly
image. The image was created using data collected
by the Advanced Very High Resolution Radiometer
between April 11, and April 20, 2005, compared to
average conditions.
Drought on the Iberian Peninsula As May draws to
a close, Spain and Portugal are entering the
summer dry season already parched from a
record-dry winter. Between November 2004 and
March 2005, Spain experienced its driest winter
since records began in 1943, reported the Spanish
Meteorological Institute. Portugal is
experiencing its worst drought in 25 years. The
U.S. Department of Agricultures Foreign
Agricultural Service estimated rainfall totals
for both Spain and Portugal to be as much as 75
percent below average between September and
Drought in Poland - 1993
2nd half of July 2nd half of August
3rd decade of September
Vegetation indices
Floods Floods are among the most devastating
natural hazards in the world, claiming more lives
and causing more property damage than any other
natural phenomena. Within the USA, an average of
more than 225 people are killed and more than
US3.5 billion in property is damaged by heavy
rain and flooding each year. As a result, floods
are one the greatest challenges to weather
starting on April 20, 2005 Romania worst flood
since 50 years (several dams were broken)
  • Remote sensing management cycle
  • Prevention where history, corporate memory and
    climatology are important,
  • Mitigation that insulates people or
    infrastructure from hazards,
  • Pre-flood, which is the preparation and forecast
    stage where remote sensing is essential,
  • Response (during the flood) where actions to be
    taken is of key importance and weather NOWCASTS
    (0 - 3 hour prediction of precipitation) using
    remote sensing is extremely useful,
  • Recovery, (post flood) which is the postmortem
    stage where damage assessment procedures are
    taken, but also numerical weather prediction and
    hydrological models are validated.

  • The potential of high and low resolution polar
    orbital Earth Resource Satellites have been shown
    to be an excellent tool for providing
    hydrological information including the
    quantification of catchment physical
    characteristics, such as topography and land use,
    and catchment variables such as soil moisture and
    snow cover. There have been many demonstrations
    of the operational use of these satellites for
    detailed monitoring and mapping of floods and
    post-flood damage assessment
  • Infrastructure status
  • Land use
  • Vegetation
  • Soil Moisture
  • Snow pack
  • DEM pre- and post-flood
  • Flood development of Flood peak
  • Damage assessment
  • Bathymetry pre- and post-flood

Piechowice reservoir destroyed in 1997 flood.
Limnigraf destroyed during 1997 flood - Olawa
Remote sensing information in operational
hydrology and flood warning and monitoring 1.
Compared to other natural hazards, flooding is
the most widespread and most damaging natural
risk in Europe. 2. Large river basins cross the
national borders. 3. Close co-operation between
between different countries is necessary. 4.
Integration of different sources of information
satellite, radar, models, ground observations. 5.
There is still lack of direct link between
satellite products providers and the end-user
involved with hydrological models. 6. The
EUMETSAT Hydrological SAF is proposed for
development of operational products related to
Hydrological model
Example of successful use of METEOSAT IRVIS
derived precipitation in hydrological modelling.
Floods in Hungary and Serbia in April 2000 SAR
satellite image
Among many weather phenomena, one of the most
dangerous and causing greatest damages are storms.
  • 1. Storms are phenomena of relatively small
    spatial (5 - 200 km) and temporal (0.5-6 h)
  • 2. Storm forecasting is most problematic and the
    error is highest (hydrostatic models).
  • 3. Storms are frequently connected with
  • heavy precipitation,
  • strong wind, frequently damaging,
  • lightnings,
  • hail,
  • tornadoes.

  • Direct effect of mentioned phenomena is very
  • flush floods (water or mud floods),
  • fires of the houses, farm buildings, technical
    infrastructure as a result of lightnings
  • buildings and forest damages as a result of
    strong wind (hurricane),
  • crop and property damages due to hail storms.

In extreme conditions those cases are cumulating
on relatively small area, leading to tremendous
material losses, or even to human live loss.
After a storm in Pisz 04.07.2002 (fot. Skapski)
Development of flash flood as a result of severe
storm (Switzerland)
Satellite image of tornado track and resulting
12 July 1984 Munich hailstorm (caused total
economical loss of 3 mln DM)
Available remote sensing information for
detection and monitoring of storms (in
Europe) 1. Meteorological radars. 2. Lightning
detection systems. 3. Geostationary satellite
Meteosat-7 (until end of 2005). 4. System Rapid
Scan from Meteosat-6 satellite. 5. NOAA polar
orbiting satellites. 6. Geostationary satellite
MSG (since 2004 operational).
  • In near future
  • European polar orbiting satellite Metop (Feb.
  • American NPOESS satellites (first 2008-2009).
  • 3. GPM (Global Precipitation Mission) planned
    2008, postponed to 2010 2015,

  • Use of satellite information
  • Determination of the area of intensive
    convection leading to storm development and
    connected intensive precipitation - atmospheric
    stability indices.
  • Detection of storm cells and determination of
    its actual phase (developing, decaying) -
    geostationary satellite data Meteosat (MSG).
  • Following of storm trajectories and nowcasting
    of its future development - Meteosat (MSG).
  • Determination of rain intensity, rainfall amount
    - blended methods (different sensors).

Early detection of the area where intensive
convection is expected. Atmospheric stability
indices 1. Available from the NWP model
(mezoscale). 2. Determined from satellite
vertical sounding - TOVS/NOAA information. 3.
Determined from geostationary satellite MSG
(every 15 min). More then 20 different stability
indices is in use, based on vertical distribution
of temperature, moisture, dew point temperature,
potential temperature, mixing ratio etc.
like CAPE, Showalter, Adedokun, Lifted Index,
Telfer, KI, KO, TotalTotals and many others.
Atmospheric stability indices allow for
forecast/nowcast of convective phenomena a few
hours in advance.
Sequence of satellite images
K Index
3 persons killed 6 injured Big damages of
infrastructure Crops damaged or completely
flushed out from the fields In certain areas 60
mm/h precipitation rate was recorded
Locusts Plague Northwest and Western Africa
Swarms of locusts can contain as many as 80
million locusts per square kilometer, and may
cover several square kilometers. An adult locust
can eat its own weight in food every day, a small
part of a typical swarm can eat as much food as
2,500 people in a single day. The locust
outbreak of 2004 began in Morocco and Algeria in
northwestern Africa. While the locusts can't be
seen in satellite imagery, the conditions that
support them are clearly visible.
In the lower image, a composite of data collected
between August 28 and September 4, 2004, pockets
of green in southern Mauritania, Senegal, Mali,
and Burkina Faso show where the locusts are
finding food and breeding. The most recent
information from FAO shows that these are indeed
the areas where the locusts are concentrated.
CONCLUSIONS 1. Satellite data proven, that can be
treated as useful tool in disaster management
(including agrometeorological). 2. Satellite
information cannot be treated as separate tool,
its advantage is in use together with appropriate
models (as model inputs and/or parameters). Fancy
images are nice but decision making process is
based on proper interpretation of actual and
forecasted situation. 3. User requirements are
growing together with development of more
detailed models. Development of new satellites
and its sensors is much slower process. Early
recognition of potential user demands is
essential. 4. Access to satellite products is
better in developed countries while their value
is highest in less developed countries with
scarce ground observation network.
  • Recommendations for the future (for discussion)
  • In geographic areas where rapid response is
    required, an operational satellite wildland fire
    detection and monitoring system with an ultimate
    fire detection time of 5 minutes, a repeat time
    of 15 minutes, a spatial resolution of 250
    meters, a maximum of 5 false alarms is required.
  • Assimilation of satellite data into coupled
    ocean/atmosphere/land models used for drought
  • altimeter measurements of ocean topography, with
    the quality of TOPEX/POSEIDON, to be used as a
    starting field in coupled-model El Nino
    predictions (Jason mission ?)
  • Development of methods for the integration of
    satellite, in-situ and GIS data for input into
    models (hydrological, fire risk )
  • Development of multi-sensor/satellite integration
  • Addition of microwave sensor on geostationary
  • Improve satellite rainfall estimation techniques
  • Estimation of soil moisture and snowpack
    characteristics from high resolution microwave
  • Increase temporal frequency of polar orbiting
    satellite data acquisitions.
  • Decrease time required to acquire and deliver
    remotely sensed data.
  • Lower the cost of remotely sensed data.
  • Education/Training to build local capability.
  • International coordination of data acquisitions.