Weather overview
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During many emergency responses weather will play some role, either as the trigger event e.g. a cyclone, heavy rain, extreme temperature (hot or cold), or to inform responders for longer term planning such as winterisation.
Both.
Situational.
If the response has been triggered due to a weather event then immediately, and these should then be updated once a day, particularly for floods where rainfall will have an impact. For longer term planning, creating products with monthly averages can be done well in advance.
Almost all responders, particularly urban search and rescue teams, pilots, logisticians and those involved with winterisation.
The weather will have a series of different effects for different users. For search and rescue teams and pilots, poor weather (high precipitation, cloud cover or wind) may hamper their ability to operate. Heavy rainfall may make roads impassable, hampering the work of logisticians trying to move aid using trucks. The lack of rainfall or extreme temperatures may impact on agriculture, making it difficult for crops to grow. The weather will also determine the type of shelter that is used in camps or temporary shelters, i.e. is there a need to provide shelter from extreme temperatures, heavy rain, snowfall, etc. Conversely there may be improvements in a response. A reduction in rain during flooding will put less strain on river systems that are close to or over capacity. It will also help improve road conditions. In areas of drought, rainfall will begin to help improve conditions by providing water that is much-needed. A rise in temperatures during cold weather events will put less strain on fuel for keeping warm, etc.
For cyclones and flooding produce maps showing rainfall and storm paths, including wind strength. These should be produced daily and updated as required.
For long-term planning produce monthly snapshots showing maximum and minimum temperatures and precipitation.
For a time series of products consider the scale and how it should be classified across the full time period. Look at the maximum and minimum extents of the range and use these for each period. Once the scale and classification have been calculated, use the same colour ramp in the symbology. Doing so makes it easier for the user to compare each month.
Daily rainfall:
Monthly averages:
Flood forecasting and modelling maps aim to show where there is a risk of flooding in an area based using precipitation, streamflow data and a range of other criteria. The time range and accuracy varies according to the models. You will see flood modelling predicting the flood extents as rain is falling or based on probability i.e. a 100 year flood event.
Both.
Baseline.
The maps that look at probability will be part of preparedness work done by the science and engineering communities as part of preparedness and insurance work. The short term forecasting will occur as the event unfolds.
All responders, but particularly those operating across the wider affected area, and including those working on assessment processes and response planning and coordination.
For governments planning responses the maps will be indicative of the risk and exposure to floods in specific areas allowing them to plan construction work to mitigate and also to give them an indication how much of a population might need evacuting or some form of assistance in the event of a flood.
The actual modelling of a flood is complex and requires a range of data which is unlikely to be found in the middle of a response. Beacuase of this it is better to look towards those organisations that create the models. In a response, or part of preparedness work additional datasets, such as population and infrastructure could be included to show who and what could be affected by a flood.
Predicted flood events
In the event of a cyclone or storm there is a threat of a storm surge and coastal flooding along coastal areas. It is affected my a number of factors including the depth (shallowness) of the water, land masses funnelling the water through a smaller gap and the tides. A storm surge on a high tide will have a higher impact.
Both.
Situational.
Modelling may have already been done as a preparedness activity by the national meteorological service and if available the data can be used in conjunction with the storm track as soon as possible.
All responders, but particularly those operating across the wider affected area, and including actors working on assessment processes and response planning and coordination.
With 40% of the global population living in coastal regions, storm surges can have a high impact on the population and properties. The map will help the decision makers understand what populations are exposed to the risk of a storm surge and take the necessary actions such as evacuating the population.
The storm surge data before the event will be modelled and will be indicative i.e. a surge might not occur at that specific location for that event. Post event there will be either recorded data from measuring stations, field assessments or remote sensing.
In the case of modelled data, a series of maps may need to be produced based on the different modelled storm surge heights. For post disaster maps, tt will be possible to indicate which areas have been affected from post disaster analysis. As with many of the storm related maps using the storm track is a useful indicator.
The following data types may be available from national or regional meteorological agencies:
Storm tracks: forecast and actual
Storm surge modelling
Storm surge observations
Storm surge remote sensing observations
Maps produced during a humanitarian response to storm events – typically tropical storms – focusing on the hazards and impacts that typically characterise such emergencies.
Both.
Situational.
Usually early on in the response, to provide initial predictive or actual impact information that can then highlight priorities for life-saving responses, and focus in-field damage and needs assessment on areas most likely to be affected.
All responders, but particularly those operating across the wider affected area, and including actors working on assessment processes and response planning and coordination.
Storm events may have multiple aspects of damage and impact, including the direct effects of high winds, rainfall and consequent flooding, storm surges and coastal flooding. Storms often affect large areas and compromise telecommunications. Therefore, predictors of physical damage and impact may be important for both the initial response and assessment planning. However, such predictors should be used with caution and should be triangulated as soon as possible with mapping of primary data such as field assessment reports.
Take care when labelling and annotating maps to distinguish between forecast, modelled and actual observations. Make sure to avoid confusion over both the date and time the forecast was issued, and the date and time to which the forecast applies. Caution should also be taken when showing the cone of uncertainty - this where the storm could go and not necessarily the whole area that will be affected or damaged.
The following data types may be available from national or regional meteorological agencies:
Storm tracks: forecast and actual
Storm surge data for selected coastal locations.
Accumulated rainfall for selected locations, or ideally as polygons
The wind speed probability maps is complimentary to any storm track map that may be produced. It provides an indication of expected wind speeds along the path of the storm.
Both.
Situational.
Before the cyclone or storm has made landfall. It will help with the planning of a response as it will indicate where the strongest winds are expected and therefore the areas that might be more prone to damage.
All responders, but particularly those operating across the wider affected area, and including actors working on assessment processes and response planning and coordination.
Storm events may have multiple aspects of damage and impact, including the direct effects of high winds, rainfall and consequent flooding, storm surges and coastal flooding.
Include the actual and forecasted storm track. The data often comes at three wind speeds and it is very easy to produce a map with a map frame for each of the wind speeds. Take care when labelling and annotating maps to distinguish between forecast, modelled and actual observations. Make sure to avoid confusion over both the date and time the forecast was issued, and the date and time to which the forecast applies.
The following data types may be available from national or regional meteorological agencies:
Storm tracks: forecast and actual
Wind speed probabilities
Maps produced during a humanitarian response to floods (including those caused by tropical storm events), focusing on the hazards and impacts that typically characterise such emergencies. Floods may affect wide areas, limiting access to communities and triggering large-scale population displacement. Maps in association with satellite imaging can visualise the extent of flooding and analyse the likely impact on communities. They are also used to plan needs assessments and a humanitarian response across multiple sectors.
Both.
Situational.
Usually early on in the response, to provide initial predictive or actual impact information that can then highlight priority areas for a life-saving response, and to focus in-field damage and needs assessment on areas most likely to be affected.
All responders, but particularly those operating across the wider affected area, and including those working on assessment processes and response planning and coordination.
Floods may be localised, but can also cover wide areas and render communities inaccessible. Initial response decisions including resource mobilisation should be taken in light of what can be inferred from remote sensing of the extent of the floods. However, such predictors should be used with caution, recognising that the reach of floods may continue to change rapidly, and should be triangulated as soon as possible with mapping of primary data such as field assessment reports.
Keep in mind that floodwater is not static and that maps should therefore be updated regularly.
Attempts to model predicted flooding using, for example, elevation contours, are unlikely to be reliable and should be avoided unless there is a proven methodology.
Prolonged water logging of ground, which may not show up as standing water on imagery, can have a severe humanitarian impact – so reliance on remote sensing alone should be avoided. Large 3W datasets can be mapped using Data Driven Pages (ESRI) or QGIS Atlas.
Remote sensed data from satellite imaging data providers such as UNOSAT. This should be requested as pre-analysed vector data (e.g. ‘flood polygons’) rather than raw imagery. Caution must however be used with such data, due to the unknown effectiveness of analysis.
Any available data from previous flood events may be helpful in identifying areas prone to flooding, although obviously such data should be interpreted with caution in the current situation.
Maps to assist in the planning for humanitarian responses that are expected to continue into the winter season. They help responders to plan for humanitarian responses under cold weather conditions, by identifying communities facilitate timely response to earthquake disasters, focusing on anticipated hazards and impacts of this type of event. Maps may be produced to coordinate urban search and rescue, to visualise access to affected areas, to analyse patterns of structural damage and assessed needs, and to plan a humanitarian response across multiple sectors.
Both.
Situational.
Disasters or complex emergencies may occur during wintertime, or humanitarian needs may be anticipated to continue into the cold season. Maps to assist in ‘winterisation’ may therefore be requested at an early stage of an emergency, well ahead of the onset of cold weather.
Humanitarian responders, particularly emergency shelter and camp coordination and management actors.
When population displacement has occurred or is threatened, the provision of climate-appropriate assistance is essential to avoid harm to vulnerable populations. It is particularly important to provide winterised shelter and also to reliably anticipate and plan for logistical access for relief assistance during winter months. Maps are essential for the spatial planning of winter relief operations.
If no historical temperature data is available, use elevation data as a proxy and annotate estimated winter low temperatures based on the lapse rate (approximately 6 degrees C per 1,000 metres elevation).
Overlay locations of vulnerable people, e.g. IDP camps, to highlight where winterisation programming is most likely to be a priority.
Topographic data with vectorised elevation to allow upland areas to be symbolised appropriately.
If available, historical average winter low temperature data and, if relevant, rainfall/snowfall data. This may be available from national or regional meteorological agencies.
Any data available on access to key routes during winter conditions.
