Black Sea Update
Heather Cannaby, Baris Sahlihoglu, Akif Korkmaz and Ekin
Akoglu
Middle East Technical University, Institute of Marine Sciences
1. Hindcast modelling
Simulations completed
Validation of hindcast simulations
Analysis of hindcast output
2. Use of scenarios and future climate scenarios
Assessment of IPSL forcing for the Black Sea region
Downscaling
Planned forecast simulations and multi-driver scenarios
3. Coupling to higher trophic levels
Ecosm with Ecopath and GOTM
Presentation Outline
Technical details of physical model
Princeton Ocean Model (pom2k)
0
Horizontal grid ~ 5km regular array (142x88)
-50
46
-100
-200
Vertical grid: 26 sigma levels, compressed towards upper 200 m
-400
-600
44
-800
-1000
Initialisation: Spun up from climatology using atmospheric climatological forcing
-1200
42
-1400
-1600
-1800
-2000
Forcing: 28
‐ ERA40 atmospheric (6‐hours data) ‐ Climatic river input (9 in total) ‐ Straits discharges (Bosporus/Kerch)
Model reanalysis
Data assimilation: 1971‐1993: Optimal Interpolation of temperature and salinity deviations from climatic mean onto model grid at monthly time scales (1971‐1992)
1992‐2001: Altimetry SSH anomalies assimilated into model as temperature and salinity 30
47
32
34
36
38
40
-2200
Dnieper
Dniestr
46
Strait of Kerch
Danube
45
44
Kodori
43
Inguri
42
Rioni
Kizil-Irmak
Strait of Bosporus
41
Eshil-Irmak
Sakarja
27
29
31
33
35
37
39
41
BIMS_ECO, BIMS_CIR (Oguz et al, 2001)
• Pelagic food web model
• Nutrient cycling (nitrogen)
• Vertical grid extends to 200 m (26 z‐levels with 2 m resolution near the surface and 20 m near the lower boundary).
• Horizontal grid as in Circulation model.
Tropic level‐0
N ‐ nitrate A – ammonium DON‐ Dissolved inorganic nitrogen
D ‐ Labile pelagic detritus
Tropic level‐1
Ps ‐ small (<10 μm) phytoplankton
Pl – large (> 10 μm) phytoplankton Tropic level‐2
Zs – microzooplankton
Zl – mesozooplankton
Zn ‐ opportunistic heterotrophic dinoflagellate Noctiluca scintillans
Za ‐ gelatinous carnivore Aurelia aurita
Zm‐ gelatinous carnivore Mnemiopsis leidyi
Hindcasts simulations completed
(POM with BimsEco)
•ERA40 with CTD assimilation (1971-1993)
•ERA40 with altimetry assimilation (1992-2001)
•ERA40 no assimilation (1980-999)
•IPSL forcing no assimilation (1980-1999)
1. Hindcast simulations
Physical model Validation (temporal variability)
Physical model Validation (accuracy/spatial variability)
15415(1062) CTD casts
Analysis of model output
Paper prepared for submission to special volume in Progress in Oceanography
“OCEAN STRATIFICATION EFFECTS”
(organised following WG at last IMBER meeting)
“Interannual to multidecadal trends and variability of the water column
structure of the Black Sea (1970-2000)”
Background..
Shallow anoxic interface leads to unique biogenchemical cycling.
Interannual variability in the depth and thickness of the suboxic zone leads to
changes in biogeochemical processes (e.g. release of nitrate from nitricline
region)
Mixed‐layer depth properties
• SST warming trend = 0.7 C
• SSS freshening trend = 0.4
• MLD shallowing trend = 6.3 m
• Increase in stability of seasonal thermocline
• 3 distinct periods:
1970s – Warm and saline
1980s – Cool and fresh
1990s – Warm and fresh
Water column stability and the Cold Intermediate Layer
• Increase in stability of super pycnocline water column due to increase in stability of seasonal thermocline and increase in stability maxima at base of CIL
• Despite relatively cool conditions during the 1990s the freshening trend resulted in an increasingly stable water column
• Implications for water column ventilation and biogeochemical cycling across the anoxic interface
CIL properties
CIL characteristics varied considerably between 1980s and 1990s
Mean thickness and temperature of the CIL: 1971‐1984: 39 m and 7.5 °C 1985 – 1993: 49 m and 7.3 °C
Conclusions
Shallowing of mixed‐layer depths and increasing stability of seasonal thermocline over past 4 decades
Distinct decadal variability in depth of winter mixing Implications for:
‐ Deep water ventilation ‐ Depth of suboxic interface
‐ Biogeochemical cycling
Problems with hindcast simulations….
The model needs to describe very different environments during simulation period
(both in terms of biogeochemical cycling and trophic structure)
Problems requiring attention
Introduction of Invasive species
Mnemiopsis Leidyi (comb jelly, first record 1982)
Beroe ovata (Moon jelly, observed since 1997)
(Ecosystem model runs conducted so far have not included Beroa which
predates on Mnemiopsis.)
Nitrogen based model
(Nitrate is not necessarily the only limiting nutrient throughout the
period of interest)
Nutrient resuspension
IPSL A1B2 SST projections for Black Sea
• Increasing SST trend of 3.7 C
• Warmest decade 2080-2090
• 33% increase in heat content of upper 300 m
2. Use of scenarios
(Asessment of IPSL forcing for Black Sea region)
ERA40 versus IPSL forcing
• Approx. identical heat gain between 1970 and 1999
• Decadal and smaller scale variability in the surface
heat flux is not represented
• ERA40 data shows a trend towards increased
freshwater input to the basin where as IPSL data
shows an opposite trend
IPSL hydrographic data assessment
IPSL (blue)
Obs. (black)
Assim. (red)
T
S
D
Not possible to use the IPSL
model data to form initial
conditions for forecast runs
SST
The IPSL SST record shows annual mean
values persistently ~1.8 °C cooler than
observations.
Comparison of IPSL and ERA40 winds to remotely sensed wind fields
IPSL(u)
IPSL(v)
ERA40(u)
ERA40(v)
CCMP(u)
CCMP(v)
Minimum
-29.30
‐11.32
‐6.05
‐4.75
‐17.66
‐20.27
Maximum
53.17
16.39
5.38
7.5
17.4
17.4
Mean
11.77
2.5
1.08
1.18
2.78
2.66
• Wind speeds are more than 100% greater in CCMP data set than ERA40
• Extreme values are more than 300% greater in the CCMP data set.
• IPSL LU20C2 mean wind speeds are ~350% larger than remotely sensed wind field
Statistical Down‐scaling: Cumulative distribution function transform method
We use the Cross‐Calibrated, Multi‐
Platform Ocean Surface Wind Velocity (CCMP) data set • Period 2080-2099
• IPSL surface forcing (with down scaled wind fields)
• Initial conditions taken from climatology appropriate to
current time (with 5 year spin up)
• 1990-2000 ecosystem structure
• 1990-2000 riverine nutrient inputs (+/- 25%)
(Planned forecast simulations)
1D HTL model for Black Sea under development
Ecopath with Ecosim (EwE)
• Ecopath - a static, mass-balanced snapshot of the system; Ecosim - a
time dynamic simulation module for policy exploration
• General Ocean Turbulence Model (GOTM)
• BimsEco (pelagic foodweb model with 10 aggregated compartments)
3. Coupling to higher trophic levels
Structure of EwE Black Sea model
(recoded in FORTRAN for Black Sea – generic FORTRAN version
being produced)
Includes 12 fish species and dolphins
Coupling EwE with GOTM
• Ecopath with Ecosim was recoded verbatim in FORTRAN and
used to build up an optimal complexity higher-trophic-level
model for the Black Sea.
• The model was fit to historical data.
• The EwEinFORTRAN model of the Black Sea was compared to
the same setup in EwE to validate the code implementation.
• A generic EwEinFORTRAN, which is capable to handle any type
of EwE model configuration, e.g. different multistanza setups
etc., and testing it with various different EwE models.
Development of 1-D model coupled to GOTM
EwEinFORTRAN
HTL module
Oguz et al., 2001
LTL module
Thank you for your attention
Technical details of physical model
Princeton Ocean Model (pom2k)
0
Horizontal grid ~ 5km regular array (142x88)
-50
46
-100
-200
Vertical grid: 26 sigma levels, compressed towards upper 200 m
-400
-600
44
-800
-1000
Initialisation: Spun up from climatology using atmospheric climatological forcing
-1200
42
-1400
-1600
-1800
-2000
Forcing: 28
‐ ERA40 atmospheric (6‐hours data) ‐ Climatic river input (9 in total) ‐ Straits discharges (Bosporus/Kerch)
Model reanalysis
Data assimilation: 1971‐1993: Optimal Interpolation of temperature and salinity deviations from climatic mean onto model grid at monthly time scales (1971‐1992)
1992‐2001: Altimetry SSH anomalies assimilated into model as temperature and salinity 30
47
32
34
36
38
40
-2200
Dnieper
Dniestr
46
Strait of Kerch
Danube
45
44
Kodori
43
Inguri
42
Rioni
Kizil-Irmak
Strait of Bosporus
41
Eshil-Irmak
Sakarja
27
29
31
33
35
37
39
41
BIMS_ECO, BIMS_CIR (Oguz et al, 2001)
• Pelagic food web model
• Nutrient cycling (nitrogen)
• Vertical grid extends to 200 m (26 z‐levels with 2 m resolution near the surface and 20 m near the lower boundary).
• Horizontal grid as in Circulation model.
Tropic level‐0
N ‐ nitrate A – ammonium DON‐ Dissolved inorganic nitrogen
D ‐ Labile pelagic detritus
Tropic level‐1
Ps ‐ small (<10 μm) phytoplankton
Pl – large (> 10 μm) phytoplankton Tropic level‐2
Zs – microzooplankton
Zl – mesozooplankton
Zn ‐ opportunistic heterotrophic dinoflagellate
Noctiluca scintillans
Za ‐ gelatinous carnivore Aurelia aurita
Zm‐ gelatinous carnivore Mnemiopsis leidyi