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gutierjm edited this page Jun 18, 2014 · 9 revisions

Practice 1A. Validating seasonal forecast (System4 vs ECA) focusing on a point of interest.

In this practice we will work at a point level, choosing a location of particular interest to analyze System4 seasonal forecasts. Details on different stations are given in https://github.com/SantanderMetGroup/downscaleR/blob/master/inst/datasets/observations/GSN_Iberia/stations.txt Tasks to be done: 1) choosing a target season (e.g. MAM, i.e. 3:5), 2) loading the data using loadECOMS (https://meteo.unican.es/trac/wiki/EcomsUdg/RPackage/Examples/pointSelection) and loadStations, 3) obtaining seasonal mean/aggregated values, 4) plotting the observed and predicted inter-annual series, 5) validating the results (correlation, BSS for probabilistic-based tercile prediction). Key points: How to manage different members.

Practice 1B. As practice 1A but for a region (System4 vs WFDEI) Tasks to be done: As in Task 1A, but considering also the re-gridding of predictions (System4 -> 0.75 deg) and observations (WFDEI -> 0.5 deg). https://meteo.unican.es/trac/wiki/EcomsUdg/RPackage/Examples/continentalSelection Key points: Validating spatial aggregated predictions or aggregating the valuation at a gridbox level.

downscaleR - Santander MetGroup (Univ. Cantabria - CSIC)

  1. Package Installation
  2. Data manipulation with transformeR
  3. Bias Correction
    1. Calibration and cross validation
      1. Working with a moving window
    2. Bias correction of climate change projections
    3. Bias correction of seasonal forecasts
    4. How to contribute with new bias correction methods
  4. Downscaling: Perfect Prognosis Approach
    1. Preparing predictor data
    2. Training and cross-validation
    3. Downscaling climate change projections
    4. Downscaling seasonal forecasts
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