# Presentation: 124173

## North Atlantic Regional Centre

- S Pouliquen , V Thierry, C Coatanoan, F Gaillard, PM Poulain & al.

## Main activities

- Coordination of Float Deployments in the Atlantic
- Delayed Mode QC:
- Networking on the methodology : mainly between France and Germany
- Improve reference database in the North Atlantic
- Data sharing among the RDAC partners
- Improve climatology in the North Atlantic
- Data consistency at Basin level
- Warning: The method is still in development
- The goal is to point out suspicious profiles, not to propose and apply a new correction. Floats remain under the responsibility of the operator and the PI it “belongs” to.
- Mediterranean Sea Activities

## Float deployment coordination

- NARDAC performs a regular monitoring for deployment coordinationThe goal is to achieve a regular density of one float per 3*3 degree**Red** : the float density is correct

- January 2006

- September 2006

- planneddeployements

## Network monitoring

- NARDAC performs a regular monitoring for all deployed floats

## 2007-2008 deployments forecast

- Netherlands 4-8 in 2007
- France 40-50 in 2007 & 2008
- Germany : ??? 2007  30-50/year starting 2008
- UK: 6 in 2007 ?
- Italy 0 2007 ?? 2008
- Spain ???
- Ireland ???
- Norway ???
- EURO-Argo: a proposal is under construction to get funds for a European contribution to ARGO of about 250/year. Should be a trial year  in 2008-2009

## Delayed Mode Activities

- Close collaboration between France and Germany on delayed mode processing methods
- Starts of CTD collection on Atlantic for RDAC partners (France, Germany, Canada)

## Data consistency over North Atlantic

- P. Galaup, V. Thierry, C. Coatanoan, E. Autret, F. Gaillard,
- Sismer and Laboratoire de Physique des Océans Brest, France

## Dataset

- 	Coriolis dataset:
- 		ARGO profilers, CTD/XBT, buoys and moorings
- 	Good and probably good data are fed as input to the analysis system
- 		0 < QC < 3
- 	1 analysis /week from January 2001 to December 2005 with a temporal window of +/- 21 days
- 	CORA-RT : analysis with only real-time data
- 	CORA-DM : ARGO real-time profiles are replaced by delayed-mode profiles when available

## Configuration

- Reference:  Levitus 98 adapted by MERCATOR
- Horizontal grid: 1/2°
- 59 levels (5 to 2000 m)
- gaussian covariances C(dx, dy, dt)
- LS = 300 km, MS  ~ Rossby Radius

## ARGO Dataset consistency

- Comparison of CORA-RT and CORA-DM
- 	As in real-time and operational mode, residuals from the analysis are used to detect suspicious profiles / profilers
- 	The method has been tested on the North-Atlantic : 20°N-70°N, 80°W-10E
- 	Two analyses have been performed:
- 		1. using 77 DM floats from the DAC Coriolis
- 		2. using 149 DM floats from various DACs

## Local differences between CORA-RT and CORA-DM

- Impact of the DM data :
-  new information consistent with RT data
-  new information in a frontal zone induces large differences

- Salinity field at 600m depth on the 16th of June 2004

- Cora-DM

- Cora-DM- Cora-RT

## Residuals analysis

- RT data - climatology DM data - climatology
- CORA-RT residuals
- CORA-DM residuals

- 1900073 (1600 -1950 m)

## Residuals analysis

- 1900077

- T

- S

## Few floats have mean residuals greater than 0.01 PSU.
None of them are problematic : short life time, salinity and temperature anomaly correlated, Med water influence, etc..

- None of them are problematic : short life time, salinity and temperature anomaly correlated, Med water influence, etc..

- Identification of suspicious profiles / profilers

-  Screening residuals time-series
-  Greater attention to floats with	- delayed-mode data with a QC=2	- large mean residuals over their life time

## Case 1: suspicious profiles

## Case 1: Suspicious profiles

- Among the 11500 delayed mode profiles that enter the analysis system, less than 5 were bad
- 		 the DMQC processing is rather good
- However, for the overall quality of the ARGO data set, it is worth being able to detect them
- The analysis system allows to do it in a rather efficient way

## Case 2: suspicious offset

- Few profilers exhibits a negative ‘suspicious’ offset :
- 4900133 (corrected)
- 4900135 (not corrected)
- 4900136  (     “               )
- 4900227 (     “               )
- 4900497 (     “               )

## Case 2 : suspicious offset

- They all are located in the same area

## Case 2 : suspicious offset

- This float has been corrected (red curve), but the Boehme&Send (2005) method proposes a different correction (blue or black curves), consistent with the residuals deduced from the objective analysis.

- DMQC with DM data (MEDS)

- DMQC with RT data

-  4900133

## Case 2 : suspicious offset

- In all cases, the Boehme&Send method suggest a correction of order 0.02 psu or more.

## Case 2 : suspicious profilers

- Given the fact that 5 or 6 profilers show the same offset of order 0.02 psu, it is likely that the measurements are true.
- Those floats are from MEDS  and  we don’t know yet how MEDS corrected these floats. Hypothesis are :
- they may have used neighboring ARGO floats and data from the Bedford cruises in the reference database, they also use Wong et al.’s software
- both the reference database and the software are different at Coriolis
- So, knowing the current conditions near Newfoundland, we are able not to correct good profiles but we are not able to correct profiles that need a correction....

## Conclusions On ARGO Dataset consistency

- We were among the first users of the delayed mode data: some problems in the D files have been identified and resolved
- From those first analyses, general statistics show that the delayed mode dataset in the North-Atlantic is rather good
- Few “bad” profiles with a 0<QC<3 have been found
- very low percentage of the delayed-mode profiles
- the analysis system allow to detect them in a rather efficient way
- The analysis is able to detect “suspicious” profilers. They will be “reconsidered” by they PI and operator. DM data with a QC=2 will be consider with greater attention.
- This study reveals the importance of the reference database (and of the software ?) to propose the adequate correction.

## Perspectives On ARGO Dataset consistency

- More work is necessary
- to fully understand and exploit the results of the analyses
- to adapt the analysis system to the consistency problem in
- improving the initial climatology to eliminate bias due to the age of the climatology
- increasing the number of neighboring floats in each analysis to reduce the weight of 1 float compared to the other
- to transfer/adapt the method for an operational use

## Improved Climatology for North Atlantic  (E Autret and F Gaillard)

- Take advantage of a dataset (Coriolis FTP files):
- homogeneous (format and QC)
- Extended (ARGO profilers, CTD/XBT, buoys and moorings)
- Use an operational tool (Coriolis Analysis System)
- Codes adapted to Coriolis datasets
- Configuration (grid, statistics, reference climatology)
- Tunable parameters
- To Perform the re-analysis of the ARGO period (2000-2005)

## Dataset 2000-2005

- Download of Coriolis data base: 23/01/2006
- Use 0<QC <3
- High frequency data averaged (over 1 day)
- The ARGO array has been gradually setting up:
- Very poor in 2000
- Temperature improved in 2001
- Salinity in late 2002
- Nearly nominal since mid 2003
- Most data are now provided by ARGO

## Data distribution over space

- The Atlantic from 20S to 70N is not evenly sampled : The 20N and 20S bands  and latitudes > 65N are less observed (except for Norwegian sea)
- The seasonal bias is moderate
- North-East Atlantic is the best sampled area

## The 2000-2005 mean

- Computing the mean seasonal cycle:
- To take into account the strong variations of the quality of the estimation over time, a weighting is applied to each monthly field before computing the mean:
-  Err_min = 50; Err_max = 99;
- Tjune = sum(pdsi*Tijune)
- Comparing the mean with previous climatologies:
- Comparison is done with:
-  WOA01_V2 at 1⁄4° interpolated on our analysis grid

## The annual mean

## Anomalies/WOA01-V2 (1/4°)

**Notes:**
En surface : un réchauffement général, accentué sur la côte est du Groenland. Ce réchauffement est accompagné d’une salinification sauf en mer de Norvège et dans une bande autour de 10°N. 
A 400 m : Un réchauffement au Nord de 30°N sauf en mer de Norvège et sur le trajet Nord du Gulf-stream et son prolongement vers la dérive Nord-Atlantique. Une tendance générale au refroidissement au sud de 30°N, avec cependant alternance de signe par bandes de latitude. Les zones de réchauffement sont en général associées à une salinisation mais on remarque un net signal d’eau douce en mer du Labrador. 
A 1000 m : Réchauffement et salinisation de la partie Nord-Est du bassin, associé à l’eau méditerranéenne. Désalinisation de la partie ouest, associée au réchauffement de la mer du Labrador et à un refroidissement entre 30 et 50°N. Réchauffement au sud de 35°N, avec salinisation entre 20 et 30°N et désalinisation de la bande 10°S-10°N. 
A 1400 m : le signal est semblable à celui décrit à 1000m. 

## Conclusion on Climatology activity

- Coriolis dataset
- Since 2003 the full 0-2000m layer is well covered for T and S by ARGO profilers
- High latitude and shelves remain problematic
- Mean 2000-2005 /WOA01-v2
- Surface : water is warmer and saltier (except 10°N fresher)
- At 400 m : Gulf Stream and North Atlantic Current are cooler and fresher (at least in the western basin). Labrador sea is fresher. NE Atlantic is warmer and saltier.
- At 1000/1400 m: Labrador sea is warmer and fresher. Eastern basin is Warmer and saltier. Central (40N-40W) basin is colder and fresher. Tropics are warmer and mostly fresher
- 2000-2005 inter-annual variability at basin scale can be accessed with this dataset