Evaluation of Atmospheric Fields from the ECMWF Seasonal Forecasts over a 15-Year Period

2005 ◽  
Vol 18 (16) ◽  
pp. 3250-3269 ◽  
Author(s):  
Geert Jan van Oldenborgh ◽  
Magdalena A. Balmaseda ◽  
Laura Ferranti ◽  
Timothy N. Stockdale ◽  
David L. T. Anderson
Keyword(s):  
Teleconnection Pattern ◽  
Seasonal Forecasts ◽  
Sea Level Pressure ◽  
Weather Forecasts ◽  
Enso Teleconnections ◽  
Medium Range ◽  
Data Points ◽  
System 2 ◽  
System 1 ◽  
Better Than

Abstract Since 1997, the European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts with ensembles of a coupled ocean–atmosphere model, System-1 (S1). In January 2002, a new version, System-2 (S2), was introduced. For the calibration of these models, hindcasts have been performed starting in 1987, so that 15 yr of hindcasts and forecasts are now available for verification. The main cause of seasonal predictability is El Niño and La Niña perturbing the average weather in many regions and seasons throughout the world. As a baseline to compare the dynamical models with, a set of simple statistical models (STAT) is constructed. These are based on persistence and a lagged regression with the first few EOFs of SST from 1901 to 1986 wherever the correlations are significant. The first EOF corresponds to ENSO, and the second corresponds to decadal ENSO. The temperature model uses one EOF, the sea level pressure (SLP) model uses five EOFs, and the precipitation model uses two EOFs but excludes persistence. As the number of verification data points is very low (15), the simplest measure of skill is used: the correlation coefficient of the ensemble mean. To further reduce the sampling uncertainties, we restrict ourselves to areas and seasons of known ENSO teleconnections. The dynamical ECMWF models show better skill in 2-m temperature forecasts over sea and the tropical land areas than STAT, but the modeled ENSO teleconnection pattern to North America is shifted relative to observations, leading to little pointwise skill. Precipitation forecasts of the ECMWF models are very good, better than those of the statistical model, in southeast Asia, the equatorial Pacific, and the Americas in December–February. In March–May the skill is lower. Overall, S1 (S2) shows better skill than STAT at lead time of 2 months in 29 (32) out of 40 regions and seasons of known ENSO teleconnections.

Did the ECMWF Seasonal Forecast Model Outperform Statistical ENSO Forecast Models over the Last 15 Years?

2005 ◽  
Vol 18 (16) ◽  
pp. 3240-3249 ◽  
Author(s):  
Geert Jan van Oldenborgh ◽  
Magdalena A. Balmaseda ◽  
Laura Ferranti ◽  
Timothy N. Stockdale ◽  
David L. T. Anderson
Keyword(s):  
El Niño ◽  
Statistical Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Forecast Model ◽  
Seasonal Forecasts ◽  
Weather Forecasts ◽  
Forecast Models ◽  
System 2 ◽  
System 1

Abstract The European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts since 1997 with ensembles of a coupled ocean–atmosphere model, System-1 (S1). In January 2002, a new version, System-2 (S2), was introduced. For the calibration of these models, hindcasts have been performed starting in 1987, so that 15 yr of hindcasts and forecasts are now available for verification. Seasonal predictability is to a large extent due to the El Niño–Southern Oscillation (ENSO) climate oscillations. ENSO predictions of the ECMWF models are compared with those of statistical models, some of which are used operationally. The relative skill depends strongly on the season. The dynamical models are better at forecasting the onset of El Niño or La Niña in boreal spring to summer. The statistical models are comparable at predicting the evolution of an event in boreal fall and winter.

scholarly journals A new framework for probabilistic seasonal forecasts based on circulation type classifications and driven by an ensemble global model

2018 ◽  
Vol 15 ◽  
pp. 183-190 ◽  
Author(s):  
Gianni Messeri ◽  
Riccardo Benedetti ◽  
Alfonso Crisci ◽  
Bernardo Gozzini ◽  
Matteo Rossi ◽  
...  
Keyword(s):  
Sea Level ◽  
Geopotential Height ◽  
Circulation Type ◽  
Seasonal Forecasts ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Circulation Types ◽  
Temperature And Precipitation ◽  
Medium Range ◽  
New Framework

Abstract. In the last years coupled atmospheric ocean climate models have remarkably improved medium range seasonal forecasts, especially on middle latitude areas such as Europe and the Mediterranean basin. In this study a new framework for medium range seasonal forecasts is proposed. It is based on circulation types extracted from long range global ensemble models and it aims at two goals: (i) an easier use of the information contained in the complex system of atmospheric circulations, through their reduction to a limited number of circulation types and (ii) the computation of high spatial resolution probabilistic forecasts for temperature and precipitation. The proposed framework could be also useful to lead predictions of weather-derived parameters, such as the risk of heavy rainfall, drought or heat waves, with important impacts on agriculture, water management and severe weather risk assessment. Operatively, starting from the ensemble predictions of mean sea level pressure and geopotential height at 500 hPa of the NCEP – CFSv2 long range forecasts, the third-quantiles probabilistic maps of 2 m temperature and precipitation are computed through a Bayesian approach by using E-OBS 0.25∘ gridded datasets. Two different classification schemes with nine classes were used: (i) Principal Component Transversal (PCT9), computed on mean sea level pressure and (ii) Simulated Annealing Clustering (SAN9), computed on geopotential height at 500 hPa. Both were chosen for their best fit concerning the ground-level precipitation and temperature stratification for the Italian peninsula. Following this approach an operative chain based on a very flexible and exportable method was implemented, applicable wherever spatially and temporally consistent datasets of weather observations are available. In this paper the model operative chain, some output examples and a first attempt of qualitative verification are shown. In particular three case studies (June 2003, February 2012 and July 2014) were examined, assuming that the ensemble seasonal model correctly predicts the circulation type occurrences. At least on this base, the framework here proposed has shown promising performance.

scholarly journals Evaluation of Coupled Model Forecasts of Ethiopian Highlands Summer Climate

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Mark R. Jury
Keyword(s):  
Crop Yields ◽  
Coupled Model ◽  
Maximum Temperature ◽  
Seasonal Forecasts ◽  
Early Season ◽  
Ethiopian Highlands ◽  
Climate Forecasting ◽  
Medium Range Forecast ◽  
Medium Range ◽  
Better Than

This study evaluates seasonal forecasts of rainfall and maximum temperature across the Ethiopian highlands from coupled ensemble models in the period 1981–2006, by comparison with gridded observational products (NMA + GPCC/CRU3). Early season forecasts from the coupled forecast system (CFS) are steadier than European community medium range forecast (ECMWF). CFS and ECMWF April forecasts of June–August (JJA) rainfall achieve significant fit (r2=0.27, 0.25, resp.), but ECMWF forecasts tend to have a narrow range with drought underpredicted. Early season forecasts of JJA maximum temperature are weak in both models; hence ability to predict water resource gains may be better than losses. One aim of seasonal climate forecasting is to ensure that crop yields keep pace with Ethiopia’s growing population. Farmers using prediction technology are better informed to avoid risk in dry years and generate surplus in wet years.

scholarly journals An Examination of Tropical Cyclone Position, Intensity, and Intensity Life Cycle within Atmospheric Reanalysis Datasets

2012 ◽  
Vol 25 (10) ◽  
pp. 3453-3475 ◽  
Author(s):  
Benjamin A. Schenkel ◽  
Robert E. Hart
Keyword(s):  
Life Cycle ◽  
North Pacific ◽  
Strongly Correlated ◽  
Sea Level Pressure ◽  
Climate Forecast System Reanalysis ◽  
Weather Forecasts ◽  
The North ◽  
Medium Range ◽  
The Mean ◽  
Modern Era

Abstract The following study examines the position and intensity differences of tropical cyclones (TCs) among the Best-Track and five atmospheric reanalysis datasets to evaluate the degree to which reanalyses are appropriate for studying TCs. While significant differences are found in both reanalysis TC intensity and position, the representation of TC intensity within reanalyses is found to be most problematic owing to its underestimation beyond what can be attributed solely to the coarse grid resolution. Moreover, the mean life cycle of normalized TC intensity within reanalyses reveals an underestimation of both prepeak intensification rates as well as a delay in peak intensity relative to the Best-Track. These discrepancies between Best-Track and reanalysis TC intensity and position can further be described through correlations with such parameters as Best-Track TC age, Best-Track TC intensity, Best-Track TC location, and the extended Best-Track TC size. Specifically, TC position differences within the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), ECMWF Interim Re-Analysis (ERA-I), and Modern Era Retrospective-Analysis for Research and Applications (MERRA) exhibit statistically significant correlations (0.27 ≤ R ≤ 0.38) with the proximity of TCs to observation dense areas in the North Atlantic (NATL) and western North Pacific (WPAC). Reanalysis TC intensity is found to be most strongly correlated with Best-Track TC size (0.53 ≤ R ≤ 0.70 for maximum 10-m wind speed; −0.71 ≤ R ≤ −0.53 for minimum mean sea level pressure) while exhibiting smaller, yet significant, correlations with Best-Track TC age, Best-Track TC intensity, and Best-Track TC latitude. Of the three basins examined, the eastern North Pacific (EPAC) has the largest reanalysis TC position differences and weakest intensities possibly due to a relative dearth of observations, the strong nearby terrain gradient, and the movement of TCs away from the most observation dense portion of the basin over time. The smaller mean Best-Track size and shorter mean lifespan of Best-Track EPAC TCs may also yield weaker reanalysis TC intensities. Of the five reanalyses, the smaller position differences and stronger intensities found in the Climate Forecast System Reanalysis (CFSR) and Japanese 25-year Reanalysis (JRA-25) are attributed to the use of vortex relocation and TC wind profile retrievals, respectively. The discrepancies in TC position between the Best-Track and reanalyses combined with the muted magnitude of TC intensity and its partially nonphysical life cycle within reanalyses suggests that caution should be exercised when utilizing these datasets for studies that rely either on TC intensity (raw or normalized) or track. Finally, several cases of nonphysical TC structure also argue that further work is needed to improve TC representation while implying that studies focusing solely on TC intensity and track do not necessarily extend to other aspects of TC representation.

Dynamical downscaling of precipitation in Iceland 1961–2006

2010 ◽  
Vol 41 (3-4) ◽  
pp. 153-163 ◽  
Author(s):  
Ólafur Rögnvaldsson ◽  
Jóna Finndís Jónsdóttir ◽  
Haraldur Ólafsson
Keyword(s):  
Dynamical Downscaling ◽  
Atmospheric Flow ◽  
Weather Forecasts ◽  
Model Driven ◽  
Ice Caps ◽  
Mm5 Model ◽  
Simulated Precipitation ◽  
Medium Range ◽  
Liquid Precipitation ◽  
Better Than

Atmospheric flow over Iceland has been simulated for the period January 1961 to July 2006, using the mesoscale MM5 model driven by initial and boundary data from the European Centre for Medium Range Weather Forecasts (ECMWF). Firstly, the simulated precipitation is compared to estimates derived from mass balance measurements on the Icelandic ice caps. It is found that the simulated precipitation compares favourably with the observed winter balance, in particular for Hofsjökull, where corrections to take liquid precipitation and/or winter ablation into account have been made, and for the outlet glaciers Dyngjujökull and Brúarjökull. Secondly, the model output is used as input to the WaSiM hydrological model to calculate and compare the runoff with observed runoff from six watersheds in Iceland. It is found that model results compare favourably with observations. Overall, the MM5 V3–7 is somewhat better than the MM5 V3–5. The V3–7 is drier than V3–5 on upstream slopes.

scholarly journals Design and Performance Analysis of New Ultra-Supercritical Double Reheat Coal-Fired Power Generation Systems

Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 238
Author(s):  
Ming Yang ◽  
Liqiang Duan ◽  
Yongjing Tong
Keyword(s):  
Heat Transfer ◽  
Power Generation ◽  
Reference System ◽  
Simulation Software ◽  
Coal Consumption ◽  
System 2 ◽  
System 1 ◽  
Power Generation Systems ◽  
New System ◽  
Better Than

In order to solve the existing problems of large mean heat transfer temperature differences of regenerative air heaters and high superheat degrees of regenerative extraction steam in double reheat coal-fired power generation systems, two new design schemes of ultra-supercritical double reheat cycles are proposed, which can realize the deep boiler-turbine coupling among the heat transfer processes of air, feeding water and regeneration extraction steam on the base of the principle of energy level matching. A typical 1000 MW ultra-supercritical double reheat cycle system is selected as the reference system and the overall system model is built by using the Ebsilon simulation software. The performances of two new systems are analyzed by using both the exergy method and energy equilibrium method. The results show that net output powers of both new systems 1 and 2 increase by 6.38 MW and 6.93 MW, respectively, and the standard coal consumptions of power generation decrease by 1.65 g/kWh and 1.79 g/kWh, respectively. The off-design performances of new systems and the reference system are analyzed, and the results show that performances of two new systems are better than that of the reference system. The system flow of the new system 2 is more complex compared with that of the new system 1. Generally speaking, the performance of new system 1 is better than that of new system 2. On the basis of new system 1, new system 3 is further optimized and its full operating condition performance characteristics are analyzed. The standard coal consumption rate of new system 3 is reduced about 1 g/kWh at higher load, and around 0.2 g/kWh at low load.

scholarly journals Statistical Bias Correction Modelling for Seasonal Rainfall Forecast for the case of Bali Island

2018 ◽  
Author(s):  
Dedi Lealdi ◽  
Sri Nurdiati ◽  
Ardhasena Sopaheluwakan
Keyword(s):  
Prediction Model ◽  
Bias Correction ◽  
Agricultural Sector ◽  
Quantile Mapping ◽  
Weather Forecasts ◽  
Agriculture Sector ◽  
Rainfall Forecast ◽  
Medium Range ◽  
Systematic Biases ◽  
Better Than

Rainfall is an element of climate which is highly influential to the agricultural sector. Rain pattern and distribution highly determines the sustainability of agricultural activities. Therefore, information on rainfall is very useful for agriculture sector and farmers in anticipating the possibility of extreme events which often cause failures of agricultural production. This research aims to identify the biases from seasonal forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) rainfall forecast and to build a transfer function in order to correct the distribution biases as a new prediction model using quantile mapping approach. We apply this approach to the case of Bali Island, and as a result, the use of bias correction methods in correcting systematic biases from the model gives better results. The new prediction model obtained with this approach is better than ever. We found generally that during rainy season, the bias correction approach performs better than in dry season.

scholarly journals Yearly evolution of Euro-Atlantic weather regimes and of their sub-seasonal predictability

2021 ◽  
Author(s):  
Nicola Cortesi ◽  
Verónica Torralba ◽  
Llorenó Lledó ◽  
Andrea Manrique-Suñén ◽  
Nube Gonzalez-Reviriego ◽  
...  
Keyword(s):  
Annual Cycle ◽  
Winter Season ◽  
Skill Score ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Sea Level Pressure ◽  
Weather Regimes ◽  
Start Dates ◽  
Weekly Frequency

AbstractIt is often assumed that weather regimes adequately characterize atmospheric circulation variability. However, regime classifications spanning many months and with a low number of regimes may not satisfy this assumption. The first aim of this study is to test such hypothesis for the Euro-Atlantic region. The second one is to extend the assessment of sub-seasonal forecast skill in predicting the frequencies of occurrence of the regimes beyond the winter season. Two regime classifications of four regimes each were obtained from sea level pressure anomalies clustered from October to March and from April to September respectively. Their spatial patterns were compared with those representing the annual cycle. Results highlight that the two regime classifications are able to reproduce most part of the patterns of the annual cycle, except during the transition weeks between the two periods, when patterns of the annual cycle resembling Atlantic Low regime are not also observed in any of the two classifications. Forecast skill of Atlantic Low was found to be similar to that of NAO+, the regime replacing Atlantic Low in the two classifications. Thus, although clustering yearly circulation data in two periods of 6 months each introduces a few deviations from the annual cycle of the regime patterns, it does not negatively affect sub-seasonal forecast skill. Beyond the winter season and the first ten forecast days, sub-seasonal forecasts of ECMWF are still able to achieve weekly frequency correlations of r = 0.5 for some regimes and start dates, including summer ones. ECMWF forecasts beat climatological forecasts in case of long-lasting regime events, and when measured by the fair continuous ranked probability skill score, but not when measured by the Brier skill score. Thus, more efforts have to be done yet in order to achieve minimum skill necessary to develop forecast products based on weather regimes outside winter season.

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