Added Valu lue In Index: Europe and Ext xtreme Events James - - PowerPoint PPT Presentation

β–Ά
added valu lue in index
SMART_READER_LITE
LIVE PREVIEW

Added Valu lue In Index: Europe and Ext xtreme Events James - - PowerPoint PPT Presentation

Oct 07, 2022 186 likes β€’386 views

A Spatial representation of f an Added Valu lue In Index: Europe and Ext xtreme Events James Ciarlo` , Erika Coppola, Adriano Fantini, Cosimo Solidoro, & Filippo Giorgi 1 Added Value Nested RCM simulations are indeed useful as

slide-1
SLIDE 1

A Spatial representation of f an Added Valu lue In Index: Europe and Ext xtreme Events

James Ciarlo`, Erika Coppola, Adriano Fantini, Cosimo Solidoro, & Filippo Giorgi

1

slide-2
SLIDE 2

Added Value

β€œNested RCM simulations are indeed useful as climate downscaling tools to the extent that they add valuable information to that produced by GCMs” Torma et al. (2015)

Topography (m) Torma et al. (2015)

2

slide-3
SLIDE 3

Kolmogorov- Smirnov Distance

maximum distance between two cumulative distribution functions

3

Torma et al. (2015)

slide-4
SLIDE 4

Where is the Added Value?

4

slide-5
SLIDE 5

Relative Probability Difference 𝐸𝑁𝑃𝐸 = Οƒ π‘„π‘βˆ†π‘€ βˆ’ Οƒ π‘„π‘ƒβˆ†π‘€ Οƒ π‘„π‘ƒβˆ†π‘€

5

Proposed Method

1. Interpolate to common grid [RCM] 2. Calculate difference in PDFs 3. … for EACH and EVERY individual grid-point!

slide-6
SLIDE 6

Probability Difference

6

slide-7
SLIDE 7

Probability Difference

7

OR: Relative Probability Difference [0 - 100%]

slide-8
SLIDE 8

Added value

π΅π‘Š = 𝐸𝐻𝐷𝑁 βˆ’ 𝐸𝑆𝐷𝑁

8

1. Interpolate to common grid [RCM] 2. Calculate difference in PDFs 3. Compare the differences Units depend on [Relative] Probability Difference

slide-9
SLIDE 9

Observation Data

Data-set Region Resolution Reference EURO4M Alps 5 km Isotta et al. (2014) Spain02 Spain 0.11Β° Herrera et al. (2015) SAFRAN France 8 km Vidal et al. (2010) ENG REGR UK 0.11Β° Perry et al. (2009) KLIMAGRID Norway 1 km Mohr (2009) PTHBV Sweden 4 km Johansson (2002) CARPATCLIM Carpathians 0.10Β° Szalai et al. (2013) REGNIE Germany 1 km Rauthe et al. (2013) GRIPHO Italy 12 km Fantini et al. (in progress) more data-sets may be included…

9

slide-10
SLIDE 10

10

Probabil ilit ity Dif ifference: EURO-CORDEX 12km

slide-11
SLIDE 11

Added Valu lue: EURO-CORDEX 12km

11

slide-12
SLIDE 12

Extreme q95-100 fraction

12

q95

slide-13
SLIDE 13

13

full PDF q95-100 fraction

slide-14
SLIDE 14

q95-100 fraction q0-5 fraction

14

q99.9-100 fraction q0-50 fraction q0-25 fraction

slide-15
SLIDE 15

π΅π‘Š = 𝐸𝐻𝐷𝑁 βˆ’ 𝐸𝑆𝐷𝑁

Adapting for Downscaling Signal

15

Historical Data: 𝐸𝑁𝑃𝐸 = Οƒ π‘„π‘βˆ†π‘€ βˆ’ Οƒ π‘„π‘ƒβˆ†π‘€ Οƒ π‘„π‘ƒβˆ†π‘€ Future Data: 𝐸𝑁𝑃𝐸 = Οƒ 𝑄

π‘”βˆ†π‘€ βˆ’ Οƒ π‘„β„Žβˆ†π‘€

Οƒ π‘„β„Žβˆ†π‘€ for EACH and EVERY individual grid-point!

Difference between RCM and GCM anomalies, compared with the corresponding region-average change in each model.

𝐸𝑇 βˆ†π‘„ = βˆ†π‘„π‘†π·π‘π‘— βˆ’ βˆ† ΰ΄€ 𝑄𝑆𝐷𝑁𝑗 βˆ’ (βˆ†π‘„π»π·π‘π‘˜ βˆ’ βˆ† ΰ΄€ π‘„π»π·π‘π‘˜)

Giorgi et al. (2016)

slide-16
SLIDE 16

Convective Permitting (3 km)

16

  • Russell Glazer, Emanuela Pichelli, Paolo Stocchi, Jose Abraham Torres Alavez

SE Europe Alps Carpathians

slide-17
SLIDE 17

CORDEX Domains

17

  • Moetasim Ashfaq, Melissa Bukovsky, Sushant Das, Russell Glazer, Francesca

Raffaele, Taleena Sines, Jose Abraham Torres Alavez, (Xuejie Gao?)

slide-18
SLIDE 18

Thank You for your attention!

Email: jciarlo@ictp.it

18

slide-19
SLIDE 19

References

  • Fantini A. et al. (2018). Assessment of multiple daily precipitation statistics in ERA-Interim driven Med-CORDEX and EURO-CORDEX

experiments against high resolution observations. Climate Dynamics, 51: 877-900.

  • Giorgi F. et al. (2016). Enhanced summer convective rainfall at Alpine high elevations in response to climate warming. Nature

Geoscience, 9: 584-589.

  • Herrera S. et al. (2015). Update of the Spain02 gridded observational dataset for Euro-CORDEX evaluation: assessing the effect of

the interpolation methodology. International Journal of Climatology, doi:19.1002/joc.4391

  • Isotta F.A. et al. (2014). The climate of daily precipitation in the Alps: development and analysis of a high-resolution grid dataset

from pan-Alpine raingauge data. International Journal of Climatology, 34: 1657-1675.

  • Johansson B. (2002). Estimation of areal precipitation for hydrological modelling. PhD Thesis. Earth Sciences Centre, Goteborg

University, Report nr. A76.

  • Kanamitsu M. & DeHaan L. (2001). The Added Value Index: A new metric to quantify the added value of regional models. Journal of

Geophysical Research, 116 (D11106): 1-10.

  • Kanamitsu, M. & Kanamaru H. (2007). Fifty‐seven‐year California Reanalysis Downscaling at 10 km (CaRD10). Part I: System detail

and validation with observations. Journal of Climate, 20: 5553–5571.

  • Mohr M. (2009). Comparisons of versions 1.1 and 1.0 of gridded temperature and precipitation data for Norway. Technical report
  • Met. No note 19.
  • Perry M. et al. (2009). The generation of daily gridded datasets of temperature and rainfall for the UK. Met Office Climate

Memorandum No. 24.

  • Rauthe M. et al. (2013). A Central European Precipitation Climatology – part I: generation and validation of a high resolution

gridded daily data set (HYRAS). Meteorologische Zeitschrift, 22: 235-256.

  • Rummukainen M. (2016). Added value in regional climate modelling. Climatic Change, 7: 145-159.
  • Szalai S. et al. (2013). Climate of the greater Carpathian region. Final Technical Report. www.carpatclim-eu.org
  • Torma C. et al. (2015). Added value of regional climate modelling over areas characterized by complex terrain – Precipitation over

the Alps. Journal of Geophysical Research: Atmospheres, 120: 3957-3972.

  • Vidal J.P. et al. (2010). A 50-year high-resolution atmospheric reanalysis over France with the Safran system. International Journal of

Climatology, 30: 1627-1644.

19