PEEX-Modelling-Platform (PEEX-MP) Overview
As the societal impacts of hazardous/ unfavorable weather and other environmental pressures grow, the need for integrated predictions which can represent the numerous feedbacks and linkages between sub-systems of our environment is greater than ever. This has led to development of a new generation of high resolution coupled prediction tools to represent the two-way interactions between different components of the environment. For example a new generation of online integrated Atmospheric Chemical Transport (ACT) and Meteorology (Numerical Weather Prediction, NWP and Climate) models represent the interactions between different atmospheric processes including chemistry (both gases and aerosols), clouds, radiation, boundary layer, emissions, meteorology and climate. In parallel, coupled environmental prediction at km-scale which includes feedbacks between the atmosphere, land surface, coastal areas and oceans aim to better represent the interactions in the water cycle, to provide tools for improved natural hazard response or water management, for example. Global Earth system models simulate the atmosphere, cryosphere, biosphere, and oceans, allowing investigation of interactions and feedbacks within and between these different spheres, including how these affect climate and biogeochemistry on timescales of hours to millennia.
Different aspects of integrated model development, evaluation and understanding are considered within the PEEX Modelling Platform (PEEX-MP).
The platform presents a strategy for best use of current generation modeling tools to improve process understanding and improve predictability on different timescales within the PEEX domain, and also presents potential future developments. A number of application areas of new integrated modelling developments are expected to be considered, including:
- improved NWP and chemical weather forecasting (CWF) with short-term feedbacks of aerosols and chemistry on meteorological variables;
- two-way interactions between atmospheric pollution/ composition and climate variability/ change;
- better prediction of atmosphere and/or ocean state through closer coupling between the component models to represent the two-way feedbacks and exchange of the atmospheric and ocean boundary layer properties;
- more complete/ detailed simulation of the hydrological cycle, through linking atmospheric, land surface, ecosystems, hydrological and ocean circulation models;
- improved simulation of biosphere and C-cycle response to high latitude environmental change.
The PEEX-MP focuses on new generation of integrated models and is based on the seamless Earth System Modelling (ESM) approach to evolve from separate model components to seamless meteorology-composition-environment models to address challenges in weather, climate and atmospheric composition fields whose interests, applications and challenges are now overlapping.
The highly coupled nature of the atmosphere-land-ice-ocean system at high latitudes and the rapid nature of ongoing changes within and of interactions between these components, means that a highly coupled system capable of considering non-linear interactions across a range of timescales is highly desirable. “Seamless” is considered in relation to, at least, two aspects:
- at the process-scale where it refers to the coupling within a model of meteorology and composition processes to represent, for example, the two-way interactions between composition and radiative processes or microphysics, or the consistent treatment of water vapour; and,
- in terms time-space-scales where it refers to the absence of discontinuities in model behaviour when used at multiple temporal or spatial resolutions to have, for example, consistent treatment of black carbon for air quality and climate applications.
In more general sense the approach considers several dimensions of the seamless coupling, including (see Figure):
- Time scales: from minutes and nowcasting to decadal and centennial (climate) time-scale;
- Spatial scales: from street-level to global scale (dowscaling and upscaling);
- Processes: physical, chemical, biological, social;
- Earth system elements/ environments/ components: atmosphere, hydrosphere, lithosphere/ pedosphere, ecosystems/ biosphere;
- Different types of observations and modelling as tools: data processing and assimilation, validation and verification;
- Links with health and social consequences, impact, assessment, and services and end-users.
- The PEEX-MP is characterized by a complex integrated ESM approach, in combination with specific models of different processes and elements of the system, acting on different temporal and spatial scales. The ensemble approach is taken to the integration of modeling results from different models, participants and countries. PEEX utilizes the full potential of a hierarchy of models: scenario analysis, inverse modeling, and modeling based on measurement needs and processes. The models are validated and constrained by available in-situ and remote sensing data of various spatial and temporal scales using data assimilation and top-down modeling. The analyses of the anticipated large volumes of data produced by available models and sensors will be supported by a dedicated virtual research environment developed for these purposes.
As the part of the PEEX initiative, a hierarchy/ framework of modern multi-scale models for different elements of the Earth system, integrated with the observation system, is needed. This will both support the PEEX observational system, and help answer the PEEX scientific questions. Moreover, the models will inform development of the in-situ monitoring component of the PEEX Research Infrastructure by providing information on regions where specific processes or interactions may be important to measure with new observational capability.
See more in:
Baklanov A., Mahura A., Arnold S.R. , Spracklen D.V. , Makkonen R., Petäjä T., V-M. Kerminen, H.K. Lappalainen, S. Zilitinkewich, M. Kulmalaet & PEEX-MP Team (2017): PEEX Modelling Platform for Seamless Environmental Prediction. Manuscript in preparation.
Baklanov A., Schlünzen K. H., Suppan P., Baldasano J., Brunner D., Aksoyoglu S., Carmichael G., Douros J., Flemming J., Forkel R., Galmarini S., Gauss M., Grell G., Hirtl M., Joffre S., Jorba O., Kaas E., Kaasik M., Kallos G., Kong X., Korsholm U., Kurganskiy A., Kushta J., Lohmann U., Mahura A., Manders-Groot A., Maurizi A., Moussiopoulos N., Rao S. T., Savage N., Seigneur C., Sokhi R. S., Solazzo E., Solomos S., Sørensen B., Tsegas G., Vignati E., Vogel B., Zhang Y., (2014): Online coupled regional meteorology chemistry models in Europe: current status and prospects. Atmos. Chem. Phys., 14, 317-398, doi:10.5194/acp-14-317-2014.
WWRP (2015): Seamless Prediction of the Earth System: from Minutes to Months, http://library.wmo.int/pmb_ged/wmo_1156_en.pdf, WMO-No. 1156, ISBN 978-92-63-11156-2