TAMIR PLATFORM DOCUMENTATION

Using the platform

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This is the main view of TAMIR platform.

Full screen of TAMIR platform.
Full screen of TAMIR platform.

Try selecting one episode from the episode selector in the navigation bar (by default it will show the first one).

Navigation bar of TAMIR platform.
Navigation bar of TAMIR platform.

Once you have selected an episode, click the button on the left side to expand the sidebar.

Sidebar of TAMIR platform.
Sidebar of TAMIR platform.

There, you will find the different layers available. For each one of them you can show or hide them (eye icon), modify their opacity (slider) and show their description and palette colors.

When you have selected the desired layers you can pay attention to the frame selector at the bottom.

The first block has a frameselector adapted to the different leadtimes shown:

Frame selector of TAMIR platform with leadtimes.
Frame selector of TAMIR platform with leadtimes.

For the second and third blocks, a regular frame selector allows you to select different time steps, with the left part of the bar (in white) showing past time steps with the products estimated from observations, and the right part of the bar (in red) showing forecasts.

Frame selector of TAMIR platform.
Frame selector of TAMIR platform.

List of episodes

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The list of case studies presented in the TAMIR platform is the following:

  • Helsinki (Finland), 12 Aug 2017 (convective multi-hazard)

    Case corresponding to the summer thunderstorm Kiira, which left significant impacts over Finland (major forest damages due to strong wind gusts and heavy rain, electricity cut, hundreds of 112 calls and large number of interventions in southern Finland,...).
  • Valencia (Spain), 10-15 Sep 2019 (flash floods)

    Period of flooding: 12 September 2019 at 0200 UTC – 15 September 2019 at 1600 UTC

    Regions affected: Valencia, Spain (12 September 2019, at 0200-0900 and 1900-2000 UTC ), Balearic Islands (12 September 2019 at 0500 UTC), Castilla La Mancha (12 September 2019 at 0600 UTC), Murcia (12th September 2019 at 0900-1100 and 13 September 2019 at 0000-0400), Madrid (15 September 2019 at 1200 UTC), Castilla y Leon (15 September 2019 at 1600 UTC ). Other regions affected without specific timing information: Alicante, Albacete, Almeria, Malaga

    Heavy rain began on 11 September 2019 and persisted for several days, totals in Valencia exceeded 400 mm. In total there were 6 fatalities and 3,500 people were evacuated (FloodList, 2019).

    Location of the case (Valencia, Spain) in a map.
    Location of the case (Valencia, Spain) in a map.
  • Spain-France, 21-23 Oct 2019 (flash floods)

    Period of flooding: 22 October 2019 at 1700 UTC - 23 October 2019 at 1700 UTC

    Regions affected: Catalonia and Mallorca, Spain (22 October 2019 at 1700 UTC - 23 October 2019 at 0200 UTC), Var, Hérault, Aude, France (23 October 2019, 0500 - 1700 UTC)

    A weather system brought heavy rain firstly to north-eastern Spain on the 22nd October 2019 before moving into southern France the next day. Some areas of Spain received over 200 mm of rain within 24 hours on the 22nd October, with a similar amount falling the next day in France, most of this was concentrated within a 3 hour period. In Catalonia, Spain there were 1,228 calls for assistance, 2 fatalities and 2 other people were reported missing (FloodList, 2019a). In France 1,000 people were rescued by the fire service, flood impacts were reported in the regions of Hérault, Bouches-du-Rhône, Var and Aude (FloodList, 2019b).

    Location of the case (France and Spain) in a map.
    Location of the case (France and Spain) in a map.
  • Zagreb (Croatia), 24 Jul 2020 (flash floods)

    Period of flooding: 24 July 2020 at 1200 UTC - 25 July 2020 at 0600 UTC

    Regions affected: Ličko- senjska (24 July 2020, 1200 - 1500 UTC), Zagreb (24 July 2020 at 1900 UTC - 25 July 2020 at 0000 UTC), Varaždinska (25 July 2020, 0500 - 0600 UTC)

    Flash flooding associated with heavy rain occurred in Zagreb, Croatia on the evening of the 24 July 2020. Some areas received over 80 mm of rain in 3 hours, there were 350 interventions by the fire service and one fatality (Vujnovic, 2020). Reports of flash flooding were also received in other parts of Croatia, these were caused by storms associated with the same large scale synoptic pattern. The timeline of flash flood reports shows that most of the events occurred on 24 July 2020 between 2100-2200, there was an earlier instance of flash flooding in the coastal region of Ličko-senjska between 1300-1400.

    Location of the case (Zagreb, Croatia) in a map.
    Location of the case (Zagreb, Croatia) in a map.
  • Scotland (UK), 10-12 Aug 2020 (flash floods)

    Period of flooding: 11 August 2020 at 1700 UTC - 12 August 2020 at 0600 UTC

    Regions affected: Borders (11 August 2020 , 1700 - 1900 UTC ), Fife (11 August 2020, 1900 - 2100 UTC), West Lothian (11 August 2020, 1900 - 2100 UTC), Perth (11 August 2020 at 2330 UTC - 12 August 2020 at 0100), Stonehaven - Aberdeenshire (12th August 2020, 0400 - 0600 UTC)

    Thunderstorms and heavy rain began in the late afternoon of the 11th August 2020 in the Scottish borders where a major road south of Edinburgh was washed out. The rain moved north into Fife with flooding reported in Kirkcaldy and Cardenden. In Perth >100 properties were affected by flooding and a landslide in Stonehaven caused the derailment of a train leading to fatalities. SEPA report

    Location of the case (Scotland) in a map.
    Location of the case (Scotland) in a map.
  • Lisbon (Portugal), 20 Feb 2021 (flash floods)

    Period of flooding: 20 February 2021, 1000 - 1600 UTC

    Regions affected: Lisbon, Portugal

    A convective storm related to storm Karim brought heavy rain to Lisbon region. The district of Cascais was the worst affected with 48.2 mm falling in 6 hours. More information

    Location of the case (Lisbon, Portugal) in a map.
    Location of the case (Lisbon, Portugal) in a map.

Description of the TAMIR layers

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The layers are organised in four blocks:

  • First block: Flash flood forecast summary (0-120h)

    Three products are generated within the TAMIR project.

    • Seamless precipitation accumulations

      Precipitation accumulations forecasted for the upcoming 5 days. The product is displayed as a summary for four lead time aggregation windows: (0-6h], (6-24h], (24-48h], (48-120h].
      The precipitation accumulations have been obtained by seamless blending of the (i) 20-members ensemble of 1-h accumulation generated with the algorithm for probabilistic nowcasting by extrapolation of radar observations SBMcast (Berenguer et al., 2011) applied to the gauge-adjusted OPERA radar composites over Europe (2 km, 15 minutes; Park et al. 2019), and (ii) 51-members ensemble of 1-h accumulation forecasts obtained by Numerical Weather Prediction with the ECMWF Ensemble Prediction System (EPS).
      The blending technique (Wong et al. 2009) is applied for the first 6 hours, and applies a phase shift and bias correction to blend radar nowcasts into NWP using a hyperbolic tangent weighting function. For lead times beyond 6 hours, the product relies only on the NWP forecasts.
      The displayed accumulations correspond to the forecasts obtained with the control member.

      Forecasted precipitation
      Seamless precipitation forecasts.
    • Flash flood impact over sub-catchment

      Flash flood impact level forecasted for the upcoming 5 days. The product is displayed as the maximum impact level within the sub-catchments for four lead time aggregation windows: (0-6h], (6-24h], (24-48h], (48-120h].
      The forecasted impact level is estimated over the drainage network by intersecting a flash flood hazard forecast with the exposure layer on a risk matrix on the 1-km river network. Each sub-catchment is shaded according to its maximum impact for each lead time range, with darker colours showing greater impact.

      Flash flood hazard probability.
      Flash flood impact matrix.
      Flash flood impact map.
      Flash flood impact map.
    • Exposure

      Total combined relative exposure of population, health facilities, education facilities, transport and energy generation in each 1km grid cell. Higher values, shown by darker shades, represent greater combined exposure.

      Exposure map.
      Exposure map.
  • Second block: Animated Flash Flood nowcasting

    The flash flood nowcasts up to 6 hours are animated with 1 hour window to show the evolution of near-future situation awareness.

    • Seamless 1h precipitation accumulation forecast

      1-h precipitation accumulations forecasted for the upcoming 6 hours obtained by seamless blending of the (i) 20-members ensemble of 1-h accumulation generated with the algorithm for probabilistic nowcasting by extrapolation of radar observations SBMcast (Berenguer et al., 2011) applied to the gauge-adjusted OPERA radar composites over Europe (2 km, 15 minutes; Park et al. 2019), and (ii) 51-members ensemble of 1-h accumulation forecasts obtained by Numerical Weather Prediction with the ECMWF Ensemble Prediction System (EPS).
      The blending technique (Wong et al. 2009) is applied for the first 6 hours, and applies a phase shift and bias correction to blend radar nowcasts into NWP using a hyperbolic tangent weighting function.
      The displayed accumulations correspond to the forecasts obtained with the control member.

      Seamless 1h accumulation forecast map.
      Seamless 1h accumulation forecast map.
    • Flash flood hazard

      Flash flood hazard level forecasted over the river network (1-km resolution).
      The flash flood hazard level is estimated at each point of the drainage network based on catchment-aggregated rainfall accumulations calculated from the seamless precipitation forecasts.
      The flash flood hazard is estimated by comparing in real time the catchment-aggregated rainfall with reference values derived from climatology: (i) from 8-year gauge-adjusted OPERA dataset, and (ii) from a dataset of 20-year reforecasts obtained with ECMWF Integrated Forecast System (IFS).

      Flash flood hazard map.
      Flash flood hazard.
    • Flash flood impact over the river network

      Flash flood impact level forecasted for the upcoming 6 hours. The product is displayed over the drainage network (1-km resolution) every 1 hour.
      The forecasted impact level is estimated by combining the flash flood hazard forecasts with exposure information to highlight areas at risk of high impacts.

      Flash flood impact palette.
      Flash flood impact matrix.
      Flash flood impact map.
      Flash flood impact map.
    • Flash flood impact over sub-catchment

      Flash flood impact level forecasted for the upcoming 6 hours. The product is displayed as the maximum impact level within the sub-catchments every 1 hour.
      The forecasted impact level is estimated over the drainage network by combining the flash flood hazard forecasts with exposure information to highlight areas at risk of high impacts, and is summarized in the sub-catchments for quicker overview of the affected areas.

      Flash flood impact palette.
      Flash flood impact matrix.
      Flash flood impact map.
      Flash flood impact map.
    • Exposure

      Total combined relative exposure of population, health facilities, education facilities, transport and energy generation in each 1km grid cell. Higher values, shown by darker shades, represent greater combined exposure.

      Exposure map.
      Exposure map.
  • Third block: Flash flood past 24-h summary

    To overview what has actually happened in a previous day, several auxiliary estimates based on the observations are displayed.

    • Precipitation accumulation (24h)

      Daily precipitation accumulation estimated from gauge-adjusted OPERA radar composites.

      24h precipitation accumulation palette.
      24h precipitation accumulation.
    • Rain gauge accumulation (24h)

      Daily rain gauge accumulations reported from WMO SYNOP gauges over Europe and AEMET over Spain.

      Rain gauge accumulation 24h map.
      Rain gauge accumulation 24h map.
    • Flash flood hazard summary (24h)

      Maximum flash flood hazard in each 1 km grid cell during the previous 24 h.
      The flash flood hazard level is estimated at each point of the drainage network based on observed catchment-aggregated rainfall accumulations.
      The flash flood hazard is estimated by comparing in real time the catchment-aggregated rainfall with reference values derived from a climatology of 8-year gauge-adjusted OPERA dataset.

      Rain gauge accumulation 24h map.
      24-h flash flood hazard summary.
    • Flash flood impact summary over the river network (24h)

      Maximum flash flood impact category in each 1 km grid cell during the previous 24 h.
      This is calculated by blending hourly observed precipitation from the OPERA radar mosaic with ECMWF short range precipitation forecasts. The forecasted impact level is estimated over the drainage network (with a resolution of 1 km) by combining the flash flood hazard estimates with exposure information to highlight areas at risk of high impacts.

      Flash flood impact summary map.
      Flash flood impact summary map.
    • Flash flood impact summary over sub-catchment (24h)

      Maximum flash flood impact category in each 1 km grid cell during the previous 24 h and summarized in the sub-catchments for quicker overview of the affected areas.
      The forecasted impact level is estimated over the drainage network by combining the flash flood hazard estimates with exposure information to highlight areas at risk of high impacts, and is summarized in the sub-catchments for quicker overview of the affected areas.

      Flash flood impact summary map.
      Flash flood impact summary map.
  • Fourth block: Convective multi-hazard nowcasting

    To overview what has actually happened in a previous day, several auxiliary estimates based on the observations are displayed.

    • Radar reflectivity

      Reflectivity is the variable measured by radars. It relates to rain rate, R, through a relationship of the kind Z=aRb (where a and b are parameters that depend on the type of precipitation).

      Reflectivity
      Reflectivity
    • Hazard probability nowcast

      This layer is a weather radar-based nowcasting product for multi-hazards caused by thunderstorms (heavy rainfall, wind gusts, hail, and lightning).

      The product combines a cell-based storm nowcast model with a machine learning classification which estimates the hazard level of convective storm based on historical meteorological observations and emergency calls following the concepts described by Rossi et al. (2013) and Tervo et al. (2019).

      It uses meteorological data from various sources, e.g., weather radar, ground observations, Numerical Weather Prediction (NWP) models, re-analysis data and lightning observations. The performance of the classifier has been verified against past cases and has been observed to perform reasonably well. The trained classification model is then used to classify thunderstorms in real-time as observed by weather radar based only on the meteorological and other real-time data. Probabilistic nowcasts for the future location of the classified thunderstorms for the coming 5-60 minutes are being produced using an ensemble method based on Kalman filter model (Rossi et al. 2015).

      The product generation can be described with following steps. The storm cells are identified from the radar reflectivity field, described as ellipses. The cells are then classified with the machine-learning scheme utilizing the history information of the past storms, the given value is defined from the meteorological observations every 5 minutes. The classified multi-hazard cells are presented as product layer, their nowcast with one-hour lead time is provided considering the spatial uncertainty with “haziness” of the ellipse increasing with the lead time:

      Multi-hazard product for thunderstorms shown in stages.
      Multi-hazard product for thunderstorms shown in stages.

      The hazard severity classification (color-coded ellipses) for the identified storm cells and the radar reflectivity field as a background. Black is classified as no significant hazard and orange with severe hazard.
      The hazard severity classification (color-coded ellipses) for the identified storm cells and the radar reflectivity field as a background. Black is classified as no significant hazard and orange with severe hazard.

      The nowcasted hazard of the storm cells depicted as ellipses. Black is classified as no significant hazard and red with extreme severe hazard.
      The nowcasted hazard of the storm cells depicted as ellipses. Black is classified as no significant hazard and red with extreme severe hazard.

References

  • Berenguer, M., Sempere-Torres, D., Pegram, G.G., 2011. SBMcast - An ensemble nowcasting technique to assess the uncertainty in rainfall forecasts by Lagrangian extrapolation. J. Hydrol 404, 226-240. https://doi.org/10.1016/j.jhydrol.2011.04.033

  • Park S., Berenguer, M., Sempere-Torres, D., 2019. Long-term analysis of gauge-adjusted radar rainfall accumulation at the European scale. J. Hydrol. 573, 768-777. https://doi.org/10.1016/j.jhydrol.2019.03.093

  • Wong, W.K., Yeung, H.Y., Wang Y.C., and Chen, M., 2009. Towards the Blending of NWP with Nowcast - Operation Experience in B08FDP. WMO Symposium on Nowcasting, 30 Aug - 4 Sept 2009, Whistler, B.C., Canada. [Link]

  • Rossi, P.J., Hasu, V., Halmevaara, K., Mäkelä, A., Koistinen, J., Pohjola, H., 2013. Real-Time Hazard Approximation of Long-Lasting Convective Storms Using Emergency Data. J. Atmos. Oceanic Technol. 30, 538–555. https://doi.org/10.1175/JTECH-D-11-00106.1

  • Rossi, P.J., Chandrasekar, V., Hasu, V., Moisseev, D., 2015. Kalman Filtering–Based Probabilistic Nowcasting of Object-Oriented Tracked Convective Storms. J. Atmos. Oceanic Technol. 32, 461–477. https://doi.org/10.1175/JTECH-D-14-00184.1

  • Tervo, R., Karjalainen, J., Jung, A., 2019. Short-Term Prediction of Electricity Outages Caused by Convective Storms. IEEE Transactions on Geoscience and Remote Sensing 57, 8618–8626. https://doi.org/10.1109/TGRS.2019.2921809