Royal Dutch Meteorological Institute; Ministery Of Infrastructure And The Environment

 

 

PROCEED project

PROCess-based sEamless development of useful Earth system predictions over lanD (PROCEED)


 

The lack of observations to constrain the model complexity over land has determined, so far, the development of different prediction systems for different time scales. While benefit from daily verification, the models that are developed for short time-scales (Weather to seasonal climate predictions) include only that part of the surface and near-surface variability for which observations are available and that can be suitably modelled/initialized in order to positively contribute to the forecasts (verification-based approach). Therefore, to limit prediction errors, short time-scale models do not include those processes related to vegetation and their seasonal, interannual and sub-grid variability.There is no scientific basis to draw artificial boundaries between synoptic-scale numerical Weather forecast, seasonal prediction, ENSO prediction, decadal prediction and climate change. The Earth System exhibits a wide range of dynamical, physical, biological, and chemical interactions involving spatial and temporal variability continuously spanning all weather/climate scales. Therefore, the gaps between the models used for short-term prediction and the latest developments in modelling the land surface are believed to considerably limit the current level of performance and usefulness of predictions.

 

 

Objectives

  1. Develop novel observational constraints to land-climate interactions and feedbacks: Develop a comprehensive array of up-to-date state-of-the-art land data by exploiting latest developments in land monitoring services. The emerging land data sets will allow derivation of a novel set of observational constraints on land-climate interactions and biophysical feedbacks.
  2. Understand the land limitations that are affecting current prediction models: Identify the specific unresolved land surface-vegetation processes that affect the predictions from the short subseasonal-to-seasonal time-scales and that need to be adequately represented to overcome the limitations of the system across scales.
  3. Enhance Earth System predictions across scales by obtaining a practicable seamless development of verifiable land surface processes: Introduce in a seamless way those land vegetation processes that improve the performance and usefulness of the predictions by overcoming the artificial boundaries between short term and longer term climate predictions over land. By one hand, we want to extend the selected processes from the longer to the shorter time scales. In return, the verification at the short time-scales will provide knowledge back to the longer time-scales to better constrain the land processes (See Picture below).
  4. Exploit performance/usefulness of improved Earth System predictions over land. Provide valuable information to end-users thanks to the improved predictions over land. By actively collaborating with power grid operators in Europe contribute in developing robust climate services for the energy sector.

 

 

MARIE SKLODOWSKA CURIE ACTIONS European Contract H2020-MSCA-IF-2015 704585

Granted Researcher: Andrea Alessandri (KNMI) Institution: KNMI – Royal Netherlands Meteorological Institute

Partner Organization: ECMWF – European Centre for Medium-range Weather Forecasts

Two Years Project – Start date 1 January 2017

Advisory committe: Bart van den Hurk (KNMI), Gianpaolo Balsamo (ECMWF), Franco Molteni (ECMWF)

 

 

Work Plan & Packages

The overall strategy of the workplan is outlined in following Figure, showing the graphical presentation of the work packages with their main interdependencies. The different activities described in the WPs are closely connected and the information will flow from one WP to another as reported in the figure.


A fundamental contribution within PROCEED will be brought by the new climate and land surface observed data that will be collected and analysed in WP1. WP1 will provide the knowledge to go beyond state-of-the-art in WP2, where a verification-based analysis will be applied to evaluate the performance and current limitations of the latest version of the ECMWF forecasting system13. The gain in potential predictability across scales that is obtained representing new land vegetation processes in an extended version of the ECMWF seasonal prediction system, developed for climate variability/change research22, will be assessed in WP3. The synergy between verification-based and process-based analyses will be exploited in WP4 where the seamless development of the prediction system will be performed. Finally, in WP5 the evaluation of forecast improvements will be performed across scales with particular focus to the usefulness for the energy sector. The overall strategy of the work plan is outlined in Figure 1, showing the graphical presentation of the work packages with their main interdependencies. The different activities described in the WPs are closely connected and the information will flow from one WP to another as reported in the figure. The activities of the 5 work packages is detailed below:

WP1) Develop novel observational constraints to land-climate interactions and feedbacks.
Milestone 1.1: Delivery of datasets for analysis, model initialization and evaluation that will also serve WP2, WP3, WP4 and WP5. (Month 4)
Deliverable 1.1: Report/scientific paper on the novel observational constraints to land-climate interactions and feedbacks (Month 6).

WP2) Verification-Based analysis: performance and limitations of ECMWF prediction system over land.
Deliverable 2.1: Report/scientific paper on the performance and limitations of State-of-the-Art forecasts over land from latest ECMWF prediction system (Month 12).

WP3) Process-Based analysis: land vegetation processes contribution to potential predictability in the ECMWF system.
Milestone 3.1: Delivery of a set of potential predictability experiments with newly introduced land vegetation processes (Month 10).
Deliverable 3.1: Report/scientific paper(s) on the evaluation of the potential contribution of land vegetation processes to potential predictability (Month 15).

WP4) Process based seamless development of climate predictions over land.
Milestone 4.1: Delivery of a new version of the prediction system with a seamless development of the land surface-vegetation processes (Month 16).

WP5) Improved Earth System predictions across scales: skill and value for the energy sector.
Milestone 5.1: Phase 1 of the improved Earth System predictions across scales completed (Month 15).
Milestone 5.2: Delivery of the full set (Phase 2) of improved Earth System predictions across scales (Month 20).
Deliverable 5.1: Report/scientific paper(s) on the evaluation of improved Earth System predictions across scales: forecasts skill and value for energy predictions (Month 24).

 

 

Work performed and achievements

(Updated April 2017)

Follow this link to access report on the Milestone 1.1 achievement

 

Peer-Reviewed Publications

  1. A. Alessandri, F. Catalano, M. De Felice, B. Van Den Hurk, F. Doblas Reyes, S. Boussetta, G. Balsamo, and P. Miller, 2016: Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth, Clim. Dyn, doi:10.1007/s00382-016-3372-4, link to-readcube document http://rdcu.be/kJuG

  2. A. Alessandri, M. De Felice, F. Catalano, J-Y. Lee, B. Wang, D-Y. Lee, J-H. Yoo, A. Weisenheimer, 2017: Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users, Clim. Dyn., In Press. http://tinyurl.com/GrandMME-Alessandrietal2017