Diapositiva 1

1
Contribution of Medspiration/GHRSST products to
Mediterranean applications of SST
Rosalia Santoleri (1)
Bruno Buongiorno Nardelli (1) Nadia Pinardi
(2)

• CNR - Istituto di Scienze dellAtmosfera e del
  Clima sezione di Roma
• Istituto Nazionale di Geofisica e Vulcanologia

r.santoleri_at_isac.cnr.it
2
Outline

• Mediterranean SST processing chain at GOS its
  products
• Use of SST in the MFS Mediterranean ocean
  forecasting system
• Dissemination to users
• Future Plans

3
MED-SST ProductsGOS involvement in national and
international projects/programmes
Mediterranean Forecasting System
Adricosm Medspiration Mersea PRIMI
GODAE Global High Resolution SST Pilot Project
(GHRSST-PP)
4
CNR-ISAC-GOS SST processing chain (operative
since October 1998) has been designed to provide
SST data for assimilation in the MFS forecasting
model. MFS_SST are daily optimally Interpolated
Sea Surface Temperature (OISST) maps produced in
near real time at 5 Km resolution (1/16x1/16
MFS model grid)
The same OI scheme has also been used to perform
a Re-Analysis (RAv0) of AVHRR Pathfinder SST time
series, from 1985 to 2005 by CNR-GOS in
collaboration with ENEA. This product has also
been used to build up a Med SST climatology
Since July 2006, In the framework of MERSEA,
CNR-ISAC also produces multi-sensors OISST maps
merging a variety of sensors (AVHRR, MODIS,
SEVERI, AATSR) as contribution to the
GODAE/GHRSST-PP
http//gos.ifa.rm.cnr.it/
5
The Mediterranean GOS L4 SST processorf l o w c
h a r t
MF AVHRR acquisition Atlantic buffer zone
west Med
ISAC AVHRR acquisition Entire Mediterranean
Night-time SST using MF algorithm Cloud detection
Night-time SST using Pathfinder algorithm Cloud
detection
SST daily composite binning on model
grid (1/16x1/16)
SST daily composite binning on model
grid (1/16x1/16)
Data merging ISAC
L2P GHRSST Products
Data quality controll
Optimal Interpolation
Data delivery
6
GOS SST Multi-senosorsProcessing Chain LOGICAL
VIEW
7
Input Data EXT.DAT.001 all the L2P night
time data available from GHRSST ATS_NR_2P,
ENVISAT AATSR near real time SSTskin
data AVHRR18_G, AVHRR NOAA-18 GAC derived SST
data AVHRR18_L, AVHRR NOAA-18 LAC derived SST
data AVHRR17_G, AVHRR NOAA-17 GAC derived SST
data AVHRR17_L, AVHRR NOAA-17 LAC derived SST
data NAR18, AVHRR NOAA-18 derived SST
data NAR17, AVHRR NOAA-17 derived SST
data SEVIRI, MSG-SEVIRI derived SST data MODIS_A,
EOS AQUA MODIS derived SST data MODIS_T, EOS
TERRA MODIS derived SST data EXT.DAT.002
AVHRR L2 SST from NOAA18 NOAA17 acquired and
processed by CNR-ISAC Rome HRPT station
8
Data Merging

• Reference sensor ?merged files
• Interpolation uses in input merged files (1 SST
  map per day)
• The reference sensor (assumed with zero bias
  against in situ SST) is used for the adjustment
  of the SST values measured by the other sensors.
  The reference sensors were selected on the basis
  of sensors evaluation, they are
• ATS_NR_2P NAR17 (MODIS_T, 4 micron)
• Evaluation of the bias between reference sensor
  and the other sensors is performed on collated
  pixels on a daily basis (only if sufficient
  co-located pixels are found)
• Merging procedure selects valid pixels using
  first high resolution L2P data the sensor
  sequence listed below
• ATS_NR_2P , NAR17, MODIS_T, NAR18 ,
  MODIS_A, AVHRR17_L, AVHRR18_L, SEVIRI, AVHRR18_G,
  AVHRR17_G

9
Sensors Evaluation
10
SST INTERPOLATION by Optimal Interpolation
L 180 km t 7 days
Medspiration results
The Interpolation is performed in space and time,
using a time series of daily SST maps (1 SST
map per day)
The scheme drives a multi-basin analysis to
avoid data propagation across land, from one
sub-basin to the other.
NRT OISST map is produced every day at 6 am.
Delayed OISST map is produced every day after 7
days
The outputs are follows GHRSST convetion (netCDF,
Climate and Forecast (CF) Metadata convention
versione 1.0)
11
CNR-ISAC-GOS L4_processors configuration
MFS (AVHRR in input) MFS (L2P in
input)
MBE-0.26 C Rms0.52 C
MBE-0.11 C Rms0.52C
MBE-0.08 C Rms0.46 C
12
(No Transcript)
13
(No Transcript)
14
(No Transcript)
15
(No Transcript)
16
(No Transcript)
17
The warm summer 2006
The 2006 SST anomaly was monitored in near
real time by the GOS SST Processing system
daily SST anomaly respect to the 1985-2004
climatology
Time series of SST mean in the West Med
18
MFS Monitoring System

• Multiparametric buoys (M3A) in Ligurian, Adriatic
  and
• Cretan Sea
• XBT VOS/SOOP
• ARGO FLOAT (MedArgo)
• Daily SST from satellite interpolated in RT on
• the model grid (1/16x1/16)
• SLA from satellite (Jason1, GFO, ENVISAT and T/P)
• Open ocean monitoring by gliders
• Scatterometer daily winds analysis on a grid of
• 1/2x1/2 (soon a new real time analysis ready)

19
Basin scale forecasting system

• NUMERICAL MODEL
• Horizontal resolution 1/16x1/16
• Vertical resolution 72 unevenly spaced
• levels
• Numerical code OPA 8.2
• Close boundaries in the Atlantic ocean
• Free surface parameterization
• Asyncrhronously coupled with ECWF
• analyses or forecasts atmospheric fields

• DATA ASSIMILATION SCHEME
• SOFA reduced order Optimal Interpolation scheme
• Intermittent (24hr) assimilation of
• Satellite SLA
• Vertical profiles (T S)
• Satellite SST

20
The present day MFS (SYS3) weekly assimilation
system
21
Air-sea Physics and SST assimilation

• surface solar radiation computed from
  astronomical formulas - Reed (1977)
• net longwave flux formula - Bignami (1995)
• sensible and latent heat flux- Kondo (1975)
• wind stress calculated from Hellerman and
  Rosensenstein formula
• Water flux relaxation to monthly mean
  climatology from MedAtlas

• 6 hours analyses and forecast surface state
  variables from ECMWF 0.5 x 0.5 degrees air and
  dew point temperature, mean sea level pressure,
  clouds, 10 m winds

• The net heat flux is corrected by a relaxation
  (constant coefficient at this point, 20
  W/m2/degC) to satellite SST (T) each model time
  step with the following formula

22
DT evaluation of the basin scale
forecast comparison with indipendent buoy data
Temperature VALENCIA ALBORAN
23
Forecast production and broadcast

• Every day a 10 days forecast is produced in Real
  Time (11hr delay)
• Once a week, 15 past days analyses are produced
  with the assimilation of all available data
  (SST contribution)
• Every day a Web Bulletin is published (SST
  contribution)
• Every month an electronic monthly bulletin is
  released on the web site
• describing the results of the MFS system for the
  previous month together with anomalies and
  climatic indices (SST contribution)
• Every day the model data ( GOS SST data) are
  available through a dedicated ftp to users
• 
  www.bo.ingv.it/mfs

24
MFS disseminate daily forecasts to 11 nested
models
ESEOO
POSEIDON
25
(No Transcript)
26
(No Transcript)
27
(No Transcript)
28
(No Transcript)
29
(No Transcript)
30
(No Transcript)
31
(No Transcript)
32
Summary of SST Dissemination to Mediterranean
Users

• Primary user of SST is the MFS at INGV
• National forecasting Systems and MOON operational
  system throughout MOON MoU (31 centres)
• Research and educational users (gt 200)
• Research studies, cruises planning, etc
• Commercial Users
• ENI-AGIP, Telespazio
• Environmental Agency
• EEA (SST contribution Climate change report 2008,
  contribution to the monthly bulletin in
  discussion)
• UNEP/MAP (draft of the monthly bulletin is
  already proposed) MoU is in discussion
• Agreement with Italian Meteorological service for
  use the SST in their broadcast system is under
  discussion

33
Conclusion and Future plans

• The Satellite Observing System of the
  Mediterranean Sea provides NRT, DT, and
  re-analysis satellite products in agreement with
  the requirements of the MCS core products
• This system will be the MOON component of the
  SST-TAC of MCS in the framework of MyOcean
• The CNR processing SST chains will be modified to
  provide also Black Sea products in accordance
  with the MyOcean requirements
• In the framework of National Projects (Adricosm
  PRIMI)
• new multi-sensors UHR SST products will be
  developed for the Italian Sea (Adriatic, Sicily
  Channel, Tyrrhenian Sea at 1 Km resolution)
• the new SST products will be assimilation in the
  Adriatic, Sicily Channel forecasting models
• The SST assimilation scheme will modified to take
  into account that the characteristics satellite
  SST (e. g. restoring coefficient depending on
  wind intensity regime, e.g. Artale et al. JGR
  2002 )