Climate Change scenario viewer for adapteCCa.es

Climate Change scenario viewer for adapteCCa.es

Proyecciones regionales de Cambio Climático sobre España

As part of the adapteCCa.es project, Predictia has developed a new visualization tool for climate change scenarios over Spain. This viewer allows to visualize and download data of the last generation of regional climate change projections over Spain. Two kinds of projections are available: those produced with statistical methods, which are part of the spanish Plan Nacional Para la Adaptación al Cambio Climático (PNACC), as well as projections produced with regional models of the atmosphere inside the european branch of the international meta-project CORDEX (Euro-CORDEX).

AdapteCCa.es is a platform devoted to information consulting and interchange on the matter of adaptation the climate change. It was created as an initiative of the Oficina Española del Cambio Climático, la Fundación Biodiversidad and its equivalents in the spanish autonomous communities.

Key features

Data visualization
Use of Geographic Information Systems standards
Last generation Regional Climate Change Projections
Climate Indices for different sectors
Data download

Context and main goals

This viewer has been developed on the framework of the PNACC and the project LIFE SHARA Sensibilización y Conocimiento para la Adaptación al Cambio Climático. The goal of LIFE SHARA is to improve the governance of the adaptation to climate change, and also to increase the resiliency of Spain and Portugal. This project is coordinated by the Ministerio de Agricultura y Pesca, Alimentación y Medio Ambiente, through the Fundación Biodiversidad, with the technical direction of Oficina Española de Cambio Climático. Other partners are AEMET, the Organismo Autónomo de Parques Nacionales, through the Centro Nacional de Educación Ambiental (CENEAM) and the Agencia Portuguesa de Medio Ambiente.

The goal of the viewer is to easily provide access to the last generation of regional climate change projections over Spain. In order to achieve this, the user is kept unaware of the specific data formats used by the models (for example, netCDF). Also, some of the transformation operations most demanded by the final users are offered: spatial filtering, temporal aggregation, computation of specific indexes or anomaly computation.

Available data

Data of the most updated regional climate change projections over Spain have been added to the viewer. Additionally, two sources of observational data have been added as a reference:

  • Gridded data (~11 km resolution) of regional climate change projections (dynamical downscaling), produced in the framework of the international project of Euro-CORDEX. It consist on an ensemble of simulations with 16 combination of different global and regional models.
  • Point data (stations) of climate change projections (statistical downscaling) produced by AEMET
  • Observed point data (stations) from AEMET
  • Observed gridded data (~11 km resolution) produced by the University of Cantabria (Spain011)

Two futuros scenarios are available, corresponding to the Representative Concentration Pathways RCP8.5 and RCP4.5, apart form the reference period (historical).

Variables available

A set of standard climate variables is available, like temperature, precipitation, humidity and wind speed. Adittionally, the user can access a set of climate indices derived from these variables, which are of special interest for many impact sectors. It follows a complete list of the variables and indices currently available in the viewer:

  • Minimum temperature
  • Maximum temperature
  • 5th percentile of daily minimum temperature
  • 95th percentile of daily maximum temperature
  • Nº of days with the minimum temperature < 0ºC
  • Nº of days with the minimum temperature > 20ºC
  • Nº of warm nights
  • Nº of warm days
  • Heat wave length
  • Cooling Degree Days
  • Heating Degree Days
  • Precipitation
  • Nº of days with precipitation < 1mm
  • 95th percentile of daily precipitation
  • Maximum precipitation in 24h
  • Maximum number of consecutive days with precipitation <1 mm
  • Nº of days with rain
  • Wind speed
  • Maximum wind speed
  • Relative humidity

It is possible to visualize all these variables either with a yearly frequency or filtered for one season. It is also possible to visualize the anomaly (the difference respect to the mean of a reference period) and the relative anomaly.

Visualization elements

Thanks to Geographical Information Systems technologies, it is possible to visualize the information over an interactive map which feeds from a WMS server with support from climate data. Aditionally, it is possible to represent the temporal evolution of the variables as a plume which, by including data of an ensemble of projections, allows to visualize the uncertainty in the future evolution of the variable. The uncertainty, defined as the dispersion of the data of the projection ensemble considered, can also be visualized by using boxplots.

Spatial filtering of the information

One of the most important functionalities is the ability to select and visualize the data of a specific region. In the viewer, the user can select a region from some predefined sets, or define a custom one by plotting a polygon over the map. The region sets currently available are the following:

  • Autonomous Communities
  • Provinces
  • Municipalities
  • Hydrographic basins
  • Hydrographic sub-basins
  • Places of proposed community relevance (LIC)
  • Areas of special protection for birds (ZEPA)
  • Agricultural regions
  • Grid of the Euro-CORDEX project
  • AEMET precipitation stations
  • AEMET temperature stations

Technologies used

The viewer uses several modules to provide the previously described functionalities:

  • A WMS served based on the ADAGUC system.
  • A component which downloads and processes climate projections implemented with python using packages like xarray. This component is responsible of processing steps like converting units, temporal aggregation, climate indices computation and concatenation of simulations for the generation of multi-modelo fast-access netCDF files.
  • A back-end component based on Java and components of Spring project that provides different web services for accesing the information including functionalities like, for example, spatial filtering, report generation and handling background processes for large downloads.
  • A PostgreSQL database with support for spatial data by using the PostGIS module.
  • A front-end web component, which allows to visualize the information with the different components previously described. It uses several javaScript libraries like Leaflet, jQuery and HighCharts.

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