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Introduction

ECOCLIMAP Second Generation is the latest version of ECOCLIMAP, produced at 300m-resolution and following a new philosophy.

First, the land cover map is directly composed of the vegetation and urban types used in ISBA and TEB: each grid point of the map represents a pure type, either inland water bodies, or sea and ocean, or one vegetation type or one urban type. In other words, the notion of "cover" or ecosystem of homogeneous land cover type containing several fractions of vegetation types is abandoned.

This novelty leads to simplify the interpretation of the map inside the SURFEX code.

Secondly, the vegetation primary parameters (LAI, ground depths, height of trees, visible and near infrared soil and vegetation albedos), that are defined and averaged by cover in classic ECOCLIMAP, are now given to the PGD step throught the namelist NAM_DATA_ISBA. Consequently, they can be uniform values or input maps coming from satellite data, for example.
Some default maps or values of these parameters are provided with the current version of ECOCLIMAP-SG. However, each user can use his own maps of parameters according to his specific case, he can also add new maps for parameters that are not externalized by the namelist in the default version.

To reduce the amount of memory needed to store these maps, and also to speed up their reading in SURFEX PGD, they were manually compressed following a made in-house method.

Legend of the land cover map and technical documentation

The land cover types represented in ECOCLIMAP-SG land cover map are:

1. sea and oceans
2. lakes
3. rivers
4. bare land
5. bare rock
6. permanent snow
7. boreal broadleaf deciduous
8. temperate broadleaf deciduous
9. tropical broadleaf deciduous
10. temperate broadleaf evergreen
11. tropical broadleaf evergreen
12. boreal needleleaf evergreen
13. temperate needleleaf evergreen
14. boreal needleleaf deciduous
15. shrubs
16. boreal grassland
17. temperate grassland
18. tropical grassland
19. winter C3 crops
20. summer C3 crops
21. C4 crops
22. flooded trees
23. flooded grassland
24. LCZ1: compact high-rise
25. LCZ2: compact midrise
26. LCZ3: compact low-rise
27. LCZ4: open high-rise
28. LCZ5: open midrise
29: LCZ6: open low-rise
30: LCZ7: lightweight low-rise
31: LCZ8: large low-rise
32: LCZ9: sparsely built
33: LCZ10: heavy industry

The detailed documentation of the method to build the land cover map and the maps of primary parameters is available lower.
This documentation is completed by this second one (19/06/18).

The scripts mentionned in previous documentation are all included in the package liste.tar.gz available here.
To the second documentation corresponds the package of scripts liste2.tar.gz.

A special directory is dedicated to the realization of the maps of parameters: save_scripts_param.tar.gz.
In this directory, the file make_all_fields_param.sh allows to build the maps of parameters without the Kalman filter; the txt file process_kalman.txt explains how to reproduce the creation of the maps with the Kalman filter.

How to download ECOCLIMAP-SG

Given the amount of externalized data needed to run ECOCLIMAP-SG, they were dropped off on an external ftp site: ftp.umr-cnrm.fr

To get the data, you need to connect to this ftp site as:
user: ecoclimap
password: ecoclimap

There, you will find the ECOCLIMAP-SG/V0 directory, containing the following files:

  • COVER: contains COVER_ECOSG_2010_V0.*.tgz, the ECOCLIMAP-SG land cover map input files for SURFEX
    Warning: formerly named ecosg_final_map.dir.gz and ecosg_final_map.hdr.gz.
    NB: When several versions are available, be careful to always use the latest one.
  • HT: contains HT_ECOSG_2010_V0.*_c.tgz, the compressed map for the heights of trees
    Warning: formerly named new_ht_c.dir.gz and new_ht_c.hdr.gz.
    NB: When several versions are available, be careful to always use the latest one.

================= The new datasets below are provided without missing data =================

  • LAI:
  • The new LAI_SAT dataset replaces the old LAI/300M dataset.
    => Each dataset contains 36 couples of compressed files .dir/.hdr, one couple for each 10-day period.
    => These LAI datasets come from the 2014-2016 CGLS LAI data at 300m-resolution.
    => The two datasets are similar but the new one is provided without missing data.
    Warning: these datasets are centered on 2015. There is a time difference with the other data centered on 2010.
  • The new LAI_KAL dataset replaces the old LAI/1KM dataset.
    => Each dataset contains 36 couples of compressed files .dir/.hdr, one couple for each 10-day period.
    => The new dataset comes from the 2008-2012 CGLS LAI data at 1km-resolution while the old dataset comes from the 1999-2016 CGLS LAI data at 1km-resolution.
    => Both of them brought to 300m resolution following the method explained in Munier et al. (2018), that uses a Kalman filter to separate the contributions of each vegetation type present in the 1km-pixel.
    => The new dataset is provided without missing data.

S. Munier, D. Carrer, C. Planque, F. Camacho, C. Albergel, J. C. Calvet, 2018. Satellite Leaf Area Index: global scale analysis of the tendencies per vegetation type over the last 17 years. Remote Sensing, 10(3), 424. doi:10.3390/rs10030424.

  • ALB:
  • The new ALB_SAT dataset replaces the old ALBNIR_SNOWFREE/ALBVIS_SNOWFREE dataset.
    => Each dataset contains 2*36 couples of compressed files .dir/.hdr, two couples for each 10-day period (white-sky albedo over visible and near-infrared wavelengths).
    => These albedo datasets come from the 2008-2012 CGLS albedo data at 1km-resolution, excluding the effect of snow.
    => The two datasets are similar but the new one is provided without missing data.
  • The new ALB_KAL dataset (excluding the effect of snow) replaces the old ANS/ANV/AVS/AVV dataset (not suitable for SURFEX because including the effect of snow).
    => Each dataset contains 2*2*36 couples of compressed files .dir/.hdr, four couples for each 10-day period (white-sky soil albedo and white-sky vegetation albedo, over visible and near-infrared wavelengths).
    => The new dataset comes from the 2008-2012 CGLS albedo data at 1km resolution, excluding the effect of snow while the old albedo dataset comes from the 1999-2016 CGLS albedo data at 1km resolution, including the effect of snow.
    => Both of these datasets brought to 300m resolution following the method explained in Carrer et al. (2014), that uses a Kalman filter to separate the contributions of the soil and each vegetation type present in the 1km-pixel.
    => The new dataset is provided without missing data.
    Note: ANS means "albedo of the soil in the near infrared", ANV "albedo of the vegetation in the near infrared", AVS "albedo of the soil in the visible", AVV "albedo of the vegetation in the visible".

D. Carrer, C. Meurey, X. Ceamanos, J. L. Roujean, J. C. Calvet, S. Liu, 2014. Dynamic mapping of snow-free vegetation and bare soil albedos at global 1km scale from 10-year analysis of MODIS satellite products. Remote Sensing of Environment, 140, 420-432.

Note that if you run a PGD with ECOCLIMAP-SG, you need to choose the LAI and albedo datasets to use. To be consistent, you can combine LAI_KAL and ALB_KAL or LAI_SAT and ALB_SAT (giving the same files for soil and vegetation albedos).

================= The new datasets above are provided without missing data =================

NB: All the files need to be unzipped ("gunzip [file].gz" or "tar xzvf [file].tgz") to be used as input in SURFEX.

Currently, we use uniform values for the root depth and the ground depth, because we don't have maps for these parameters.

How to install and to use ECOCLIMAP-SG in SURFEX V81 or higher

If you want to run a PGD with ECOCLIMAP-SG in SURFEX V81 or higher, you will first need to activate, in addition to the LECOCLIMAP key, a new namelist key :

&NAM_FRAC
LECOCLIMAP = T,
LECOSG = T
/

Then, you need to link all the input files you want to use in the run directory.

After that, you will need to refer to the correct name in:

&NAM_COVER
YCOVER = 'COVER_ECOSG_2010_V0.0'
YCOVERFILETYPE = 'DIRECT'
/

And finally, you will need to update your namelist NAM_DATA_ISBA with the names of the files you use for the primary parameters.

Here two examples:

In these examples, you will find the values we used for the soil depths during the tests. If you want values closer to classic ECOCLIMAP, you can use the defaults by not specifying any.
You also can notice that the type for the compressed maps of parameters is not "DIRECT" but "DIRTYP".

How to visualize an compressed input map

If you want to visualize one of the compressed input data file, you can use the uncompress tool.
A README file (included in the archive) explains how to use the tool.

How to contact us

You can send an e-mail to the following addresses:

  • surfex-support(at)meteo.fr
  • diane.tzanos(at)meteo.fr