MREA2014 - Labelab

Transcription

MREA2014 - Labelab

Modellistica
previsionale
a
supporto di sistemi di rapid
mapping e controllo del territorio
costiero
e
marino
Ivan
Centro
sui
www.ravenna2015.it
Federico,
Cambiamenti
CMCC
euroMediterraneo
Climatici
www.ravenna2015.it
Outline
① CMCC
① Climate Changes evidence
② Modelling in coastal areas
③ Decision Support Systems
2
Outline
① CMCC
3
INTRODUZIONE AL CMCC
CMCC
• Centro euroMediterraneo sui Cambiamenti Climatici
• Divisioni:
OPA-CMCC
• da Aprile 2012: OceanLab
• da Gennaio 2015: OPA (Ocean Predictions and Applications)
Mission OPA
• Keywords: Modellistica numerica + Previsioni + Applicazioni
- Modellistica regionale, sub-regionale e costiera
- Produzione di previsioni dello stato del mare a breve termine
- Applicazioni e servizi nel campo della sicurezza marittima (i.e. sea
situational awareness, search-and-rescue, ship routing, oil spill modeling)
Studi e modellistica nella fascia costiera
(Oceanografia --> Fascia Costiera)
Modelli corrente-onda
(open sea  area costiera)
Modelli morfodinamici
(medio-lungo termine:
evoluzione linea di costa;
taratura con analisi
morfologica)
Hsms
Modelli di
propagazione del
moto ondoso
(sottocosta).
“Onde di progetto”
Progettazione opere a
mare, verifica stabilità,
sistemi di allerta, etc.
Shoaling, rifrazione,
riflessione, interazione
onda-onda, etc.
Hses
Hsml
Hsel
Clima meteomarino
medio “a largo”
(settori, frequenze di
apparizione)
Hi
- High resolution
- Data assimilation (boe)
- Dataset di simulazioni long-term
Clima meteomarino
estremo “a largo”
- Metodo di Goda
(Gumbell, Weibull, FT-II)
hs
hl
fascia costiera
Outline
① CMCC
Courtesy of Mannarini (CMCC)
CC evidence
It is certain that globally averaged LandSurface Air Temperature has risen since
the late 19th century and that this
warming has been particularly marked
since the 1970s.
For the entire Northern Hemisphere, the
trends in sea ice extent are –2.3 ± 0.5%,
–1.8 ± 0.5%, –6.1 ± 0.8% and –7.0 ±
1.5% per decade (very likely) in winter,
spring, summer and autumn, respectively
IPCC AR5 WG1 chapter02 “Observations:Atmosphere and Surface”,
IPCC AR5 WG1 chapter04: “Observations:Criosphere”
CC evidence
It is virtually certain that the upper
ocean (0 to 700 m) warmed from 1971
to 2010. The warming rate is 0.11°C
per decade in the upper 75 m,
decreasing to about 0.015°C per
decade by 700 m.
IPCC AR5 WG1 chapter03 “Observations:Ocean”
Courtesy of Mannarini (CMCC)
It is virtually certain that globally averaged
sea level has risen over the 20th century,
with a very likely mean rate between 1900
and 2010 of 1.7 mm/yr and 3.2 mm/yr
between 1993 and 2010.
Rischio crescente di
inondazione di aree costiere
Flooding a
Margherita di Savoia
Global Sea
Level Rise
(300mm in 100 yrs)
9
Outline
① CMCC
Southern Adriatic Northern Ionian coastal Forecasting System
Overview
• Mediterranean sea (Southern Eastern Italian coasts)
17.0
17.2
17.4
• Coastal modelling and forecasts
- SANI area (Puglia, Calabria, Basilicata)
40.4
40.4
• Linking open-sea to shelves to coasts
SANI area
1) Next Generation Modelling
2) Downscaling approach
T (°C)
17.0
17.2
bastest6bb_new1_reg4_10_tr4.bas
Mediterranean Forecasting System (MFS)
2517.4
Puglia
17
apnstd.str
22
18
19
Southern Adriatic Northern Ionian Forecasting System (SANIFS)
0.30
40
0.00
40
0.15
m/s
SANIFS
17
18
(Operational short-term forecasting system)
apnstd.str
Sea-conditions.com
Applications
Highresolution
coastal model
Decision
Support
System
Input data
SANIFS – Mar Grande, Taranto
MFS
ICZM policy maker
Oil spill activities
Search and rescue
Ship routing
SANIFS
m/s m/s
0.000 0.000
0.035 0.075
13 km
0.070 0.150
13 km
2 km
Mar Grande (Taranto, Puglia): commercial and industrial port
Applications
Highresolution
coastal model
Decision
Support
System
Input data
SANIFS – Isole Tremiti
Oil spill activities
Search and rescue
Ship routing
m/s
0.000
1 km
ICZM policy maker
0.125
13 km
0.250
13 km
SANIFS
MFS
m/s
0.000
0.075
0.150
Tremiti islands (Gargano, Puglia): touristic area
Model Implementation
Strategy
Model Validation
Forecasting System
Forecast Validation
17.0
17.2
17.4
17.0
17.2
17.4
16
SHYFEM model
42
40.4
42
15
40.4
3D unstructured-grid finite-element model
Hydrodynamics and tracers fields
16
17
18
19
20
21
sani10.grd
43
43
apnstd.str
17
18
17
18
16
41
40
39
40
40
42
42
41
apnstd.str
40
39
sani10.grd
38
38
15
16
17
18
19
20
21
apnstd.str
apnstd.str
Horizontal resolution: coastal 50-500 m; open-sea 3 km
Vertical resolution: 91 z-levels
The model has been initialized and
forced at the LOBCs by the MFS fields
Lateral open boundary conditions
y
SANIFS
T, S, z
ut
z MFS + z OTPS
x
MFS
TMFS / SMFS
x
Surface boundary conditions
ECMWF-12km (COSMOME-6km) field
Boundary sec on
z
SANIFS domain
MFS-OTPS
u t-MFS
The tides have been
imposed at the LOBCs
through the OTPS (OSU
Tidal
Prediction
Software) model.
Model Validation: SANIFS vs. observations – Coastal tidegauges (ISPRA)
Time-series
comparisons
between the simulated sea
level and the observed
height at the Italian tidegauges stations have been
performed.
h
[cm]
Vieste
02/06/2012
22/06/2012
02/06/2012
22/06/2012
02/06/2012
22/06/2012
Bari
h
[cm]
Taranto
Crotone
Otranto
Obs: Italian tigegauges
service provided by ISPRA
(Istituto Superiore per la
Protezione e la Ricerca
Ambientale, the Italian
Institute for Environmental
Protection and Research).
h
[cm]
Scatter plots of observed and
modeled (semidiurnal and
diurnal) tidal constituents in
terms of (a) amplitude [cm]
and (b) phase [deg] at the 5
coastal stations in SANI
domain.
DIFF (%)
Modelled tidal amplitudes [cm]
30
Vieste
AFS (Guarnieri et al., 2013)
SANIFS
10 20
10
5
0
M2
N2
Bari
Taranto
Crotone
Phase
Amplitude
15
S2
300
Modelled tidal phases [deg]
Tidal Analysis.
(TAPpy python toolbox)
200
100
K2
O1
Tidal constituents
P1
K1
AVG
Comparison with AFS (POM-based) model for Otranto tidegauge.
0
0
0
5
10
15
0
100
200
300
Observed
tidal amplitudes
[cm](ii) domain configuration (Otranto
Observedstrait);
tidal phases
[deg]
Improvements:
(i) higher
res. than AFS;
(iii) SBC:
surface pressure
Otranto
(a)
(b)
DIFF%amp =100
Ao - Am
Ao
DIFF (%)
20
Amplitude
10
0
M2
S2
DIFF%pha =100
P -P
180
o
m
DIFF (%)
20
O1
Tidal constituents
K1
AVG
Phase
10
0
M2
S2
O1
Tidal constituents
K1
AVG
Percentage error of
model for the most
significant
tidal
constituents
in
terms of amplitude
and phase.
Scatter plots of observed and
modeled (semidiurnal and
diurnal) tidal constituents in
terms of (a) amplitude [cm]
and (b) phase [deg] at the 5
coastal stations in SANI
domain.
DIFF (%)
Modelled tidal amplitudes [cm]
30
AFS (Guarnieri et al., 2013)
SANIFS
10 20
10
5
SANIFS
Vieste
2
Phase
Amplitude
15
0
M2
N2
Bari
300
Modelled tidal phases [deg]
Tidal Analysis.
(TAPpy python toolbox)
200
Root Mean100
Square error
S2 Sum K2
O1
Root
Square error
Tidal constituents
P1
K1
AVG
Otranto
DIFF%amp =100
0
0 tidegauge.
Comparison
with5 AFS (POM-based)
model 15
for Otranto
0
10
0
100
Observed tidal amplitudes [cm]
1.5
(a)
(b)
20
Amplitude
Ao - Am 110
Ao
0
M2
S2
P -P
180
o
m
DIFF (%)
0.520
DIFF%pha =100
200
300
Observed tidal phases [deg]
DIFF (%)
Crotone
RMS and RSS (cm)
Taranto
O1
Tidal constituents
K1
AVG
Phase
10
00
M2 M2
S2
S2N2
K2O1
K1
Tidal constituents
K1
O1
AVG
P1
Percentage error of
model for the most
significant
tidal
constituents
in
terms of amplitude
and phase.RSS
Q1
Validation: SANIFS vs. observations in Taranto Gulf - Mar Grande (MREA2014)
17 Grande
Mar
18
40
40
Coastal Scale
Large Scale
17
18
Marine Rapid Environmental Assessment 2014
Italian Navy Hydrographic Institute
Oceanographic cruise in Taranto Gulf
on Galatea
(Large scale, Coastal scale, Mar Grande)
(CTD, XBT, drifters, ADCP, Monitoring
System of the Sea in Mar Grande)
CMCC-INGV-UNIBO-CNR-POLIBA
apnstd.str
17 Grande
Mar
18
MREA2014
40
40
Coastal Scale
-Investigation of Taranto Gulf fields
-Real-time
data-assimilation
of
observations (in MFS) to improve
forecasts (also for nested model, e.g.
SANIFS)
Large Scale
17
18
Marine Rapid Environmental Assessment 2014
apnstd.str
ROLE of SANIFS
on Galatea
-Provide forecasting bulletins during
operations on board
-SANIFS covers with appropriate
resolution the three studied scales:
mesoscale (LS), shelf-coastal scale (CS)
and coastal-port scale (MG)
17 Grande
Mar
18
Coastal Scale
40
40
1 km
Large Scale
17
MREA2014
18
on Galatea
apnstd.str
CTD at different scales (LS, CS, MG)
XBT in LS campaign
ADCP transects
Drifters release
Automatic monitoring system in Mar Grande: CTD + ADCP
Validation: SANIFS vs. observations in Taranto Gulf (MREA2014)
17
Mar Grande
from MFS to MFS-MREA
18
CS1
LS2
from MFS-MREA
to SANIFS-MFS-MREA
Real-time data-assimilation
of observations (in MFS) to
improve forecasts (also for
nested model, e.g. SANIFS)
40
40
Coastal Scale
Large Scale
17
MREA2014
MFS
MFS-MREA
SANIFS-MFS-MREA
18
LS1 obs. assimilated in MFS
for CS1+LS2 forecasts
apnstd.str
on Galatea
DATES:
Oct.
OBSERVATIONS:
MG
LS1
1
2
CTD
XBT
3
4
5
CTD
Drifters
ADCP
CS1 LS2
6
7
8
9
10 11
CTD
XBT
2014
Validation: SANIFS vs. observations in Mar Grande (MREA2014)
Monitoring station
17.2
17 Grande
Mar
Meteo and water in
Mar Grande
- CTD -
18
Depth [m]
0.0
25.0
Coastal Scale
50.0
http://www.michelemossa.it/parag.
php?id=2&id_pag=15&id_parag=34
7
40
40
Timeseries of surface
temperature in Mar Grande.
Comparison between SANIFS
and obs. (hourly snapsnots
for 1-10 October 2014)
12:00 00:00
17.2
0 sec
0 00:00:00
level = 0
basin
SHYFEM - LBC - mean - 10days
sani64.bas
apnstd.str
Large Scale
17
MREA2014
18
apnstd.str
on Galatea
October
17.2
17 Grande
Mar
Automatic
monitoring station
18
Depth [m]
0.0
25.0
in Mar Grande for
currents
- ADCP -
50.0
http://www.michelemossa.it/par
ag.php?id=2&id_pag=15&id_par
ag=347
40
40
Coastal Scale
17.2
0 sec
0 00:00:00
level = 0
basin
sani64.bas
apnstd.str
Large Scale
Time series of velocity at z=-5m
17
18
Velocity (m/s)
0.1
obs
SANIFS
apnstd.str
0.05
0
5
5.5
6
6.5
7
time (days)
7.5
8
8.5
9
October
17.2
17 Grande
Mar
Automatic
monitoring station
18
Depth [m]
0.0
25.0
in Mar Grande for
currents
- ADCP -
50.0
http://www.michelemossa.it/par
ag.php?id=2&id_pag=15&id_par
ag=347
40
40
Coastal Scale
17.2
0 sec
0 00:00:00
level = 0
basin
sani64.bas
Large Scale
apnstd.str
u/v-velocity profiles
Time series of velocity at z=-5m
17
18
Velocity (m/s)
0.1
obs
SANIFS
apnstd.str
0.05
0
5
5.5
6
6.5
7
time (days)
7.5
8
8.5
9
October
Mar17 Grande
18
MREA2014
Coastal Scale
40
40
1 km
Large Scale
17
18
apnstd.str
Comparison between CTD and SANIFS results at different depths
MG scale
CTD in Mar Grande
Mar17 Grande
18
MREA2014
Coastal Scale
2
1
1 km
40
40
1
1
2
6
Large Scale
17
18
apnstd.str
MG scale
CTD in Mar Grande
Mar17 Grande
18
MREA2014
Coastal Scale
40
40
1
2
1 km
2
9
2
2
2
5
Large Scale
17
18
apnstd.str
MG scale
CTD in Mar Grande
Mar17 Grande
18
MREA2014
Coastal Scale
8
3
Large Scale
17
18
apnstd.str
40
40
1 km
1
3
7
1
4
MG scale
CTD in Mar Grande
Model Validation: Seasonal diagnostic – Current circulation
winter
spring
spring
winter
2 km
summer
summer
2 km
autumn
autumn
m/s
0.0
0.2
0.4
2 km
2 km
YEAR 2012
m/s
Monthly mean circulation
Impact of Adriatic circulation in Taranto Gulf
0.00
0.05
0.10
m/s
0.0
0.2
Coastal circulation in Gallipoli (touristic area in Ionian sea, Apulia). Impact of open-sea circulation.
0.4
Outline
① CMCC
START
SisTemi di rApid mapping e contRollo del Territorio costiero e marino
(Rapid mapping and “monitoring” system of marine and coastal environment)
START
Framework:
Coastal Situational Awareness (CSA): improve the awareness (and the
knowledge) of coastal environment, integrating the observed systems
(also in real time) with the operational modelling.
Main objective:
Development of products and services to provide:
•early warning and rapid mapping of extreme events (e.g. storm surge) in
Apulia coastal areas
•coastal erosion and flooding indicators
•support an integrated management of harbor areas
START
Flowchart and production chain of START services:
START
Decision Support systems:
1. DSS-COASTS: web and mobile systems dedicated to Apulia coastal
zones providing early warning and rapid mapping
a) Forecasting: sea-and-weather in coastal zones
b) Coastal protection:
-
Short term: extreme events (flooding and storm surge)
Medium and long term: sediment transport, coastal erosion indictors,
assessment of future scenarios, services based on ICZM criteria
2. DSS-HARBORS: web-gis and mobile systems dedicated to Bari and/or
Brindisi and/or Taranto providing early warning and rapid mapping
a)
b)
c)
d)
e)
Wave, hydrodynamics and sediment transport
Circulation in harbors and at the entrance
Sediments backlog
Safety navigation
Support to engineering for maritime structures in harbors
START
Early warning and rapid
mapping of extreme events
(e.g. storm surge)
Coastal erosion indicators
Early warning of extreme events
www.sea-conditions.com
Courtesy of Guarnieri (INGV)
Results – Accumulation rate along Italian coast
Accumulation rate (grcm-2yr-1)
Coupled Model
Image from Frignani et al.
2005, Marine Geology
Courtesy of Guarnieri (INGV)
Results: Sediment dynamics 2020-2030
The analysis of the evolution of the coast line since
the 60ies up to now shows a strong accumulation area
in the area immediately south-east of the
Buna/Bojana river. The comparison between the
scenario simulation and the present climate seems to
confirm the same tendency also for the future years.
accumulation
erosion
Source: Hydrographic Institute of the Serb Navy
accumulation
erosion
Conclusioni
•
Modellistica numerica (ad altissima risoluzione con
approccio oceanografico su scale spaziali più ampie) come
base per lo sviluppo di sistemi di supporto alle decisioni
nel campo della Gestione Integrata della Zona Costiera
•
La modellistica realistica ed integrata può dare un grande
supporto all’analisi degli impatti e alla loro mitigazione
•
Esistono esempi applicativi consolidati a scala di bacino del
mar Adriatico e di scenari futuri di cambiamento climatico
•
La modellistica a scala di bacino non è sicuramente
sufficiente
per
arrivare
al
dettaglio
costiero/ingegneristico, ma risulta fondamentale per
fornire le giuste condizioni iniziali e al contorno
Modelli corrente-onda
(open sea  area costiera)
Modelli morfodinamici
(medio-lungo termine:
evoluzione linea di costa;
taratura con analisi
morfologica)
Hsms
“Onde di progetto”
Progettazione opere a
mare, verifica stabilità,
sistemi di allerta, etc.
Geologia
Ingegneria
…
Costiera
Hses
Modelli di
propagazione del
moto ondoso
(sottocosta).
Shoaling, rifrazione,
riflessione, interazione
onda-onda, etc.
Hsml
Hsel
Clima meteomarino
medio “a largo”
(settori, frequenze di
apparizione)
Hi
- High resolution
- Data assimilation (boe)
- Dataset di simulazioni long-term
Clima meteomarino
estremo “a largo”
- Metodo di Goda
(Gumbell, Weibull, FT-II)
hs
hl
fascia costiera
Oceanografia
Costiera
Opere marittime mal progettate e/o eseguite …
Paola (CS) - Costa tirrenica della Calabria
Opere marittime mal progettate e/o eseguite …
San Lucido (CS) - sottoflutto rispetto a Paola (CS)
Oggi
Anni ’80
GRAZIE PER L’ATTENZIONE
www.ravenna2015.it
www.ravenna2015.it

MREA2014 - Labelab

Transcription

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