1.0 - Observations

We have access to several Italian observational datasets provided by the University of L'Aquila for:

• temperature
• precipitation
• water level
• discharge

1.1 - Observations

Outliers

1.2 - Observations

FIRST-STAGE FILTERING

FLAGGING

FLAG CHECKING

CLEANED DATASET!

1.3 - Observations

Possible first-stage filtering procedures

• Removal of extreme values > 200 mm/h
• Removal of isolated > 100 mm/h reports
• Removal of complete months with > 1800 mm (2.5 mm/h)
• Removal of continuous identical values
• ...?

Rauthe et al. 2013; A Central European precipitation climatology–Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS)

Isotta et al. 2013; The climate of daily precipitation in the Alps: development and analysis of a high‐resolution grid dataset from pan‐Alpine rain‐gauge data

Perry et al., 2009; The generation of daily gridded datasets of temperature and rainfall for the UK

Hiebl et al., 2017; Daily precipitation grids for Austria since 1961—development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling

1.4 - Observations

Possible flagging procedures

• Mean + n*SD threshold
• Median + n*IQR threshold
• Peaks in the values distribution
• Isolated dry/wet event flagging
• Low correlation of close stations
• ...?

Rauthe et al. 2013; A Central European precipitation climatology–Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS)

Isotta et al. 2013; The climate of daily precipitation in the Alps: development and analysis of a high‐resolution grid dataset from pan‐Alpine rain‐gauge data

Perry et al., 2009; The generation of daily gridded datasets of temperature and rainfall for the UK

Hiebl et al., 2017; Daily precipitation grids for Austria since 1961—development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling

1.5 - Observations

• Visual comparison of maps/videos
• Visual comparison of close timeseries
• Comparison with daily datasets (EURO4M-APGD, E-OBS, ...)
• Comparison with hourly datasets (PERSIANN, ...)
• ...?

Rauthe et al. 2013; A Central European precipitation climatology–Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS)

Isotta et al. 2013; The climate of daily precipitation in the Alps: development and analysis of a high‐resolution grid dataset from pan‐Alpine rain‐gauge data

Perry et al., 2009; The generation of daily gridded datasets of temperature and rainfall for the UK

Hiebl et al., 2017; Daily precipitation grids for Austria since 1961—development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling

Possible flag-checking procedures

1.6 - Observations

Results so far...

(by applying first-stage filtering procedures only)

1.7 - Observations

FILTERED

ORIGINAL

1.8 - Observations

Monthly averages

1.10 - Observations

1.9 - Observations

2.0 - Regional Climate Models

RCMs will be used later in the project to provide gridded input data to the CHyM hydrological model for future projections under climate change scenarios.

• Continue ongoing EURO-CORDEX simulations on Argo and on Marconi
• Test and validate post-processing scripts provided by eXact-lab (still ongoing)

2.1 - Regional Climate Models

We have assessed the performance of 9 RCMs over 9 regions for precipitation:

• High resolution observations
• Several metrics, with focus on extreme precipitation
• We found consistent added value in higher-resolution modelling (12km vs 50km) for most regions and most models

2.2 - Regional Climate Models

I performed more than 100 model simulations over the EURO-CORDEX domain in both Argo and CINECA's Marconi A1/A2

• Model tuning
• Performance assessment
• PRACE proposal 2016153590 approved

3.0 - Cetemps Hydrological Model

CHyM Is a distributed (gridded) hydrological model. Peculiarities:

• Can build DEM from various sources, smoothing by cellula automata algorithms
• Can use several kind of inputs, such as station observations, gridded model data, etc.
• Designed to work on any domain
• NetCDF output

3.1 - Cetemps Hydrological Model

Successes so far:

• Model now working on all test domains
• Model code and design has been streamlined (thanks to Fabio di Sante!)

• We can reproduce past results (Coppola et al. 2013) on our test domain (western Po basin)
• HR DEMs working (at low model res)

3.2 - Cetemps Hydrological Model

CHyM-OP reproduced domains:

3.3 - Cetemps Hydrological Model

CHyM-OP reproduced domains:

3.4 - Cetemps Hydrological Model

3.5 - Cetemps Hydrological Model

So far:

• Performed ~2000 model simulations to find the best configuration for the river network reconstruction
• Identify and compare the reconstruction of the Po river with different metrics: mean distance, basin area, distance Q95...

3.6 - Cetemps Hydrological Model

3.7 - Cetemps Hydrological Model

5.0 - CA2D hydraulic model

After using LISFLOOD-FP, we switched to the food inundation model from Dottori and Todini, 2011

5.1 - CA2D hydraulic model

Problems!

• Excessive flooding in low RPs
• Not enough difference between RPs

Solutions?

• Higher resolution (~50m)
• Better DEMs (HydroSHEDS)
• ?

6.0 - Visualization

An R/Leaflet tool for flood, river, DEM, basin and station visualization

6.3 - Visualization

Click_edit: an R/Shiny tool for WYSISYG editing of NetCDF files