4th General Assembly, University of Bern, 12-13 December 2017

The 4th and last General Assembly of the ERA-CLIM2 project (GA4), held at the University of Bern on 12-13 December 2017, was attended by about 30 people. GA4 followed GA1 held in November 2014 at ECMWF, GA2 held in December 2015 at EUMETSAT and GA3 held in January 2017 at the University of Vienna. During the meeting, the project's work was revised, and key results were discussed.

ERA-CLIM2 started in January 2014 with the aim to improve capacity for producing state-of-the-art climate reanalyses that extend back to the early 20th century. In particular, it aimed to provide a substantial contribution to rescue and prepare the observations and to advance the data-assimilation systems required to generate operational reanalysis, such as the ones planned by the Copernicus Climate Change Service (C3S).

The ERA-CLIM2 activities have been grouped into four main themes:
- Observation data rescue and post-processing (mainly WP3)
- Data assimilation methods (mainly WP2)
- Reanalysis production (mainly WP1 and WP5)
- Evaluation and uncertainty estimation (mainly WP4)

At GA4, all aspects of the project were reviewed (the GA4 presentations can be accessed following the links below).

The last 12 months of the project have seen the production of CERA-SAT, which covers 9 years of the satellite era (2008-2016), and the completion of the land and carbon climate reanalyses, CERA-20C/Land and CERA-20C/Carbon. These reanalyses were driven by the coupled ocean, sea-ice, land and atmosphere climate reanalysis of the 20th century, CERA-20C. Furthermore, more data have being rescued and post-processed, and have been delivered and copied to relevant data bases so that they can be used in future reanalysis (e.g. in the C3S ERA5 reanalysis under production, and in the future C3S ERA6 reanalysis). Advances in the assimilation methods developed within the project have also been integrated in the software depositories, and are ready to be tested in future reanalyses' productions. All the project's deliverables are expected to be completed on-time and with the required high-level quality by the end of the project.

Presentations

Welcome and Introduction
R Buizza

ERA-CLIM2 4th General Assembly
Welcome and Introduction - PDF icon              

Overview WP1/WP5
P Laloyaux

Overview WP1 (reanalysis production) and WP5 (service developments) - PDF icon

Biogeochemical reanalysis
C Perruche

WP1 – Task 1.1: Global 20th century analysis - Production of the ocean carbon component - PDF icon

CERA-SAT
D Schepers

CERA-SAT: Proof-of-concept coupled reanalysis of the satellite era - PDF icon

Land Carbon analysis
P Peylin/N Vuichard

WP1: Land carbon reanalysis - ORCHIDEE driven by CERA-20C - PDF icon

CERA-SAT ocean component and further developments
E de Boisseson

CERA-SAT ocean component and further developments - PDF icon

Tropical cyclone representation
Y Kosaka

CERA-20C: Assimilation of TC best track - PDF icon

Improving the use of historical surface and upper-air observations
P Dahlgren

Improving the use of historical surface and upper-air observations in reanalysis - PDF icon

Overview of WP2
M Martin

ERA-CLIM2 WP2 introduction - PDF icon

SST assimilation developments
D Lea and J While

Assimilation using large scale EOF error covariances - PDF icon

Sea-ice assimilation developments
C-E Testut

ERA-CLIM2 Project:Mercator Ocean Contributions to WP2.2 - PDF icon

Ensemble B in NEMOVAR
A Weaver

Ensemble B in NEMOVAR - PDF icon

Ensemble covariances in coupled DA
A Storto

The CMCC contribution to ERA-CLIM2: Experiments with coupled covariances and other activities - PDF icon

Impact of 4DVar and research into fully coupled
A  Vidard

Impact of 4DVar and research into fully coupled - PDF icon

Land carbon optimisations
P Peylin

Toward a couple Carbon – Climate reanalysis of the 20th Century - PDF icon

Strengths/weaknesses in existing coupled DA, coupled error covariances and model drift/bias correction
K Haines/X Feng

WP2.5 – Strengths/weaknesses in existing coupled DA, coupled error covariances and model driB/bias correction - PDF icon

Variational bias correction of sea surface temperature observations
J While/M Martin

Variational bias correction of Sea Surface Temperature observations - PDF icon

WP3 Overview and accomplishments
S Brönnimann

WP3 Overview and accomplishments - PDF icon

RIHMI Input for WP3 within ERA CLIM2 Project
A Sterin

RIHMI INPUT FOR WP3 WITHIN ERA CLIM2 PROJECT - PDF icon

Data Rescue, QC and a metadatabase: FCiências.ID's contribution to WP3
M A Valente

Data Rescue, QC and a metadatabase:FCiências.ID's contribution to WP3 - PDF icon

Upper air data rescue Météo-France's contribution to WP3
S Jourdain

Météo-France’s contribution to WP3:Upper-Air Data Rescue - PDF icon

Snow in situ and satellite data
J Pulliainen

Task 3.3: Boundary constraints and external forcing - PDF icon

Satellite data records for reanalysis
J Schulz

Satellite Data Reprocessing at EUMETSAT - PDF icon

Met Office contribution to WP3 in 2017
N Rayner

Met Office contribution to WP3 in 2017 - PDF icon

Overview of WP4
L Haimberger

Quantifying and reducing uncertainties - PDF icon

Uncertainties and bias corrections for radiosonde temperatures
L Haimberger

Homogenized radiosonde temperature data for climate reanalyses - PDF icon

Bias corrections for radiosonde humidity
M Blaschek

BIAS CORRECTIONS FOR RADIOSONDE HUMIDITY - PDF icon

Quality control for observations
M A Valente

Quality Control for Observations - PDF icon

ERA20C and Cera-20C precipitation in comparison to GPCC daily and monthly analyses
M Ziese

ERA-20C and CERA-20C precipitation in comparison to GPCC daily and monthly analyses - PDF icon

Uncertainties associated to the land carbon balance; comparison between ORCHIDEE and CTESSEL
P Peylin

Uncertainties associated to the land carbon balance; comparison between ORCHIDEE and CTESSEL - PDF icon

Comparison with other reanalyses, Trends and low frequency variability
L Haimberger

Low frequency variability and trends, Reanalysis Intercomparison - PDF icon

Comparisons of ERA reanalyses with the station Upper Air data
A Sterin

COMPARISONS OF ERA REANALYSES WITH THE STATION UPPER AIR DATA - PDF icon

Uncertainties in energy budgets
L Haimberger & M Mayer

 

Uncertainties in (energy) budgets - PDF icon