Dependence of skill and spread of the ensemble forecasts on the type of perturbation and its relationship with long-term
- PDF / 17,614,787 Bytes
- 24 Pages / 595.276 x 790.866 pts Page_size
- 25 Downloads / 155 Views
RESEARCH ARTICLE - ATMOSPHERIC & SPACE SCIENCES
Dependence of skill and spread of the ensemble forecasts on the type of perturbation and its relationship with long‑term norms of precipitation and temperature Grzegorz Duniec1 · Andrzej Mazur1 Received: 14 January 2020 / Accepted: 31 July 2020 © The Author(s) 2020
Abstract A new computing cluster has been operating since 2016 at the Institute of Meteorology and Water Management – National Research Institute. Increasing computing power enabled the implementation of ensemble prediction system forecasts in the operational mode and the use of a new computer for research purposes. As part of the priority project on “Study of Disturbances in the Representation of Modeling Uncertainty in Ensemble Development” and the earlier project entitled “COSMO Towards Ensemble in Km in Our Countries), implemented in the Working Group 7 (Predictability and Ensemble Methods) as part of the COSMO modeling consortium, specific studies were carried out to test ensemble forecasts. This research concerned the impact of variability of physical fields characterizing the soil surface (a selected parameter determining evaporation from the soil surface and soil surface temperature) using various methods of perturbation. Numerical experiments were completed for the warm period (from June to September) 2013. Keywords Meteorological model · Ensemble prediction system · COSMO · Perturbation schemes · Long-term norms Abbreviations IMWM-NRI Institute of Meteorology and Water Management – National Research Institute EPS Ensemble prediction system COSMO Consortium for small-scale modeling SPRED Study of disturbances in the representation of modeling uncertainty in ensemble development COTEKINO Cosmo towards ensemble in km in our countries APSU Ameliorating perturbation strategy and usage of ensemble systems TLE-MVE Time-lagged ensemble—model-varied ensemble
* Grzegorz Duniec [email protected] Andrzej Mazur [email protected] 1
Institute of Meteorology and Water Management – National Research Institute, 61 Podleśna street, 01673 Warsaw, Poland
Introduction Under the current state of knowledge, it is not possible to prepare a perfect forecast of the state of the atmosphere. However, one can determine to what extent the forecast is reliable. Some of the tools used to determine the "confidence" of the forecast are ensemble forecasts—a set of forecasts, starting from the space of initial states, defined with accuracy within the measurement error. Since 2015, a new (at this time, actually) computing cluster has been operating in IMWM-NRI. Linux cluster "Grad" ("Hail" in Polish) consists of six management nodes, each with two eight-core CPUs and of 139 computation nodes, with two ten-cores CPUs each. The overall performance according to HP-Linpack test achieved 61 Tflops, i.e., approximately 25 times higher in comparison with the prior machine. This increased computing power has enabled the IMWM-NRI to introduce the EPS for operational forecasts since the end of 2016.There are various m
Data Loading...
