scholarly journals Investigating the Factors That Contribute to African Easterly Wave Intensity Forecast Uncertainty in the ECMWF Ensemble Prediction System

2019 ◽  
Vol 147 (5) ◽  
pp. 1679-1698
Author(s):  
Travis J. Elless ◽  
Ryan D. Torn
Keyword(s):  
Large Scale ◽  
Ensemble Prediction ◽  
Prediction System ◽  
African Easterly Waves ◽  
Ensemble Prediction System ◽  
Easterly Waves ◽  
Convectively Coupled Equatorial Waves ◽  
Easterly Wave ◽  
Equatorial Wave ◽  
Diabatic Processes

Abstract Although there have been numerous studies documenting the processes/environments that lead to the intensification of African easterly waves (AEWs), only a few of these studies investigated the effect of those processes or the environment on the predictability of AEWs. Here, the large-scale modulation of AEW intensity predictability is evaluated using the 51-member ECMWF ensemble prediction system (EPS) during an active AEW period (July–September 2011–13). Forecasts are stratified based on the 72-h AEW intensity standard deviation (SD) to evaluate hypotheses for how different processes contribute to large forecast SD. While large and small SD forecasts are associated with similar baroclinic and barotropic energy conversions, forecasts with large SD are characterized by higher relative humidity values downstream of the AEW trough. These areas of higher humidity are also associated with higher precipitation and precipitation SD, suggesting that uncertainty associated with diabatic processes could be linked with large AEW intensity SD. Although water vapor is a strong function of longitude and phase of convectively coupled equatorial waves, the cases with large and small SD are characterized by similar longitude and wave phase, suggesting that AEWs occurring in certain locations or convectively coupled equatorial wave phases are not more or less predictable.

scholarly journals On the Impact of the Choice of Global Ensemble in Forcing a Regional Ensemble System

2016 ◽  
Vol 31 (2) ◽  
pp. 515-530 ◽  
Author(s):  
Florian Weidle ◽  
Yong Wang ◽  
Geert Smet
Keyword(s):  
Large Scale ◽  
Ensemble Forecasting ◽  
Ensemble Prediction ◽  
Lateral Boundary Condition ◽  
Limited Area ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
Driving Model ◽  
Environmental Prediction ◽  
The Impact

Abstract It is quite common that in a regional ensemble system the large-scale initial condition (IC) perturbations and the lateral boundary condition (LBC) perturbations are taken from a global ensemble prediction system (EPS). The choice of global EPS as a driving model can have a significant impact on the performance of the regional EPS. This study investigates the impact of large-scale IC/LBC perturbations obtained from different global EPSs on the forecast quality of a regional EPS. For this purpose several experiments are conducted where the Aire Limitée Adaption dynamique Développement International–Limited Area Ensemble Forecasting (ALADIN-LAEF) regional ensemble is forced by two of the world’s leading global ensembles, the European Centre for Medium-Range Weather Forecasts’ Ensemble Prediction System (ECMWF-EPS) and the Global Ensemble Forecasting System (GEFS) from the National Centers for Environmental Prediction (NCEP), which provide the IC and LBC perturbations. The investigation is carried out for a 51-day period during summer 2010 over central Europe. The results indicate that forcing of the regional ensemble with GEFS performs better for surface parameters, whereas at upper levels forcing with ECMWF-EPS is superior. Using perturbations from GEFS lead to a considerably higher spread in ALADIN-LAEF, which is beneficial near the surface where regional EPSs are usually underdispersive. At upper levels, forcing with GEFS leads to an overdispersion of ALADIN-LAEF as a result of the large spread of some parameters, where forcing ALADIN-LAEF with ECMWF-EPS provides statistically more reliable forecasts. The results indicate that the best global EPS might not always provide the best ICs and LBCs for a regional ensemble.

scholarly journals Observations of Seven African Easterly Waves in the East Atlantic during 2006

2010 ◽  
Vol 67 (1) ◽  
pp. 26-43 ◽  
Author(s):  
Jonathan Zawislak ◽  
Edward J. Zipser
Keyword(s):  
Large Scale ◽  
High Amplitude ◽  
African Easterly Waves ◽  
Easterly Waves ◽  
Wave Trough ◽  
Wind Structure ◽  
Easterly Wave ◽  
Global Data Assimilation System ◽  
Low Amplitude ◽  
The Relationship

Abstract The African Monsoon Multidisciplinary Analyses (AMMA) experiment and its downstream NASA extension, NAMMA, provide an unprecedented detailed look at the vertical structure of consecutive African easterly waves. During August and September 2006, seven easterly waves passed through the NAMMA domain: two waves developed into Tropical Cyclones Debby and Helene, two waves did not develop, and three waves were questionable in their role in the development of Ernesto, Florence, and Gordon. NCEP Global Data Assimilation System (GDAS) analyses are used to describe the track of both the vorticity maxima and midlevel wave trough associated with each of the seven easterly waves. Dropsonde data from NAMMA research flights are used to describe the observed wind structure and as a tool to evaluate the accuracy of the GDAS to resolve the structure of the wave. Finally, satellite data are used to identify the relationship between convection and the organization of the wind structure. Results support a necessary distinction between the large-scale easterly wave trough and smaller-scale vorticity centers within the wave. An important wave-to-wave variability is observed: for NAMMA waves, those waves that have a characteristically high-amplitude wave trough and well-defined low-level circulations (well organized) may contain less rainfall, do not necessarily develop, and are well resolved in the analysis, whereas low-amplitude (weakly organized) NAMMA waves may have stronger vorticity centers and large persistent raining areas and may be more likely to develop, but are not well resolved in the analysis.

scholarly journals The Madden–Julian Oscillation’s Influence on African Easterly Waves and Downstream Tropical Cyclogenesis

2011 ◽  
Vol 139 (9) ◽  
pp. 2704-2722 ◽  
Author(s):  
Michael J. Ventrice ◽  
Chris D. Thorncroft ◽  
Paul E. Roundy
Keyword(s):  
Large Scale ◽  
Tropical Cyclogenesis ◽  
Tropical Atlantic ◽  
Madden Julian Oscillation ◽  
African Easterly Waves ◽  
Tropical Africa ◽  
Easterly Waves ◽  
African Easterly Wave ◽  
Easterly Wave ◽  
Equatorial Rossby Waves

The influence of the Madden–Julian oscillation (MJO) over tropical Africa and Atlantic is explored during the Northern Hemisphere summer months. The MJO is assessed by using real-time multivariate MJO (RMM) indices. These indices divide the active convective signal of the MJO into 8 phases. Convection associated with the MJO is enhanced over tropical Africa during RMM phases 8, 1, and 2. Convection becomes suppressed over tropical Africa during the subsequent RMM phases (phases 3–7). African convective signals are associated with westward-propagating equatorial Rossby waves. The MJO modulates African easterly wave (AEW) activity. AEW activity is locally enhanced during RMM phases 1–3 and suppressed during RMM phases 6–8. Enhanced AEW activity occurs during periods of enhanced convection over tropical Africa, consistent with stronger or more frequent triggering of AEWs as well as more growth associated with latent heat release. Enhanced AEW activity occurs during the low-level westerly wind phase of the MJO, which increases the cyclonic shear on the equatorward side of the AEJ, increasing its instability. Atlantic tropical cyclogenesis frequency varies coherently with the MJO. RMM phases 1–3 show the greatest frequency of tropical cyclogenesis events whereas phases 7 and 8 show the least. RMM phase 2 is also the most likely phase to be associated with a train of three or more tropical cyclones over the tropical Atlantic. This observed evolution of tropical cyclogenesis frequency varies coherently with variations in AEW activity and the large-scale environment.

A New Method for Generating Initial Condition Perturbations in a Regional Ensemble Prediction System: Blending

2014 ◽  
Vol 142 (5) ◽  
pp. 2043-2059 ◽  
Author(s):  
Yong Wang ◽  
Martin Bellus ◽  
Jean-Francois Geleyn ◽  
Xulin Ma ◽  
Weihong Tian ◽  
...  
Keyword(s):  
Large Scale ◽  
Dynamical Downscaling ◽  
Ensemble Prediction ◽  
Small Scale ◽  
Lateral Boundary Condition ◽  
Limited Area ◽  
Initial Condition ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
Blending Method

Abstract A blending method for generating initial condition (IC) perturbations in a regional ensemble prediction system is proposed. The blending is to combine the large-scale IC perturbations from a global ensemble prediction system (EPS) with the small-scale IC perturbations from a regional EPS by using a digital filter and the spectral analysis technique. The IC perturbations generated by blending can well represent both large-scale and small-scale uncertainties in the analysis, and are more consistent with the lateral boundary condition (LBC) perturbations provided by global EPS. The blending method is implemented in the regional ensemble system Aire Limitée Adaptation Dynamique Développement International-Limited Area Ensemble Forecasting (ALADIN-LAEF), in which the large-scale IC perturbations are provided by the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS), and the small-scale IC perturbations are generated by breeding in ALADIN-LAEF. Blending is compared with dynamical downscaling and breeding over a 2-month period in summer 2007. The comparison clearly shows impact on the growth of forecast spread if the regional IC perturbations are not consistent with the perturbations coming through LBC provided by the global EPS. Blending can cure the problem largely, and it performs better than dynamical downscaling and breeding.

scholarly journals Dynamical Seasonal Prediction of Tropical Cyclone Activity Using the FGOALS-f2 Ensemble Prediction System

2021 ◽  
Vol 36 (5) ◽  
pp. 1759-1778
Author(s):  
Jinxiao Li ◽  
Qing Bao ◽  
Yimin Liu ◽  
Guoxiong Wu ◽  
Lei Wang ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Real Time ◽  
Large Scale ◽  
Southern Oscillation ◽  
Correlation Coefficients ◽  
Seasonal Prediction ◽  
Prediction Skill ◽  
Ensemble Prediction ◽  
Prediction System ◽  
Ensemble Prediction System

AbstractThere is a distinct gap between tropical cyclone (TC) prediction skill and the societal demand for accurate predictions, especially in the western Pacific (WP) and North Atlantic (NA) basins, where densely populated areas are frequently affected by intense TC events. In this study, seasonal prediction skill for TC activity in the WP and NA of the fully coupled FGOALS-f2 V1.0 dynamical prediction system is evaluated. In total, 36 years of monthly hindcasts from 1981 to 2016 were completed with 24 ensemble members. The FGOALS-f2 V1.0 system has been used for real-time predictions since June 2017 with 35 ensemble members, and has been operationally used in the two operational prediction centers of China. Our evaluation indicates that FGOALS-f2 V1.0 can reasonably reproduce the density of TC genesis locations and tracks in the WP and NA. The model shows significant skill in terms of the TC number correlation in the WP (0.60) and the NA (0.61) from 1981 to 2015; however, the model underestimates accumulated cyclone energy. When the number of ensemble members was increased from 2 to 24, the correlation coefficients clearly increased (from 0.21 to 0.60 in the WP, and from 0.18 to 0.61 in the NA). FGOALS-f2 V1.0 also successfully reproduces the genesis potential index pattern and the relationship between El Niño–Southern Oscillation and TC activity, which is one of the dominant contributors to TC seasonal prediction skill. However, the biases in large-scale factors are barriers to the improvement of the seasonal prediction skill, e.g., larger wind shear, higher relative humidity, and weaker potential intensity of TCs. For real-time predictions in the WP, FGOALS-f2 V1.0 demonstrates a skillful prediction for track density in terms of landfalling TCs, and the model successfully forecasts the correct sign of seasonal anomalies of landfalling TCs for various regions in China.

Study of perturbing method in regional BGM ensemble prediction system

2012 ◽  
Vol 4 (1) ◽  
pp. 65
Author(s):  
Xiao Yu-Hua ◽  
He Guang-Bi ◽  
Chen Jing ◽  
Deng Guo
Keyword(s):  
Ensemble Prediction ◽  
Prediction System ◽  
Ensemble Prediction System

Extended Prediction of North Indian Ocean Tropical Cyclones

2012 ◽  
Vol 27 (3) ◽  
pp. 757-769 ◽  
Author(s):  
James I. Belanger ◽  
Peter J. Webster ◽  
Judith A. Curry ◽  
Mark T. Jelinek
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Tropical Cyclones ◽  
North Indian Ocean ◽  
Ensemble Prediction ◽  
Tropical Cyclone Genesis ◽  
Lead Times ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
The North

Abstract This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.

scholarly journals A Probabilistic Multimodel Ensemble Approach to Seasonal Prediction

2009 ◽  
Vol 24 (3) ◽  
pp. 812-828 ◽  
Author(s):  
Young-Mi Min ◽  
Vladimir N. Kryjov ◽  
Chung-Kyu Park
Keyword(s):  
Real Time ◽  
Gaussian Approximation ◽  
Seasonal Prediction ◽  
Asia Pacific ◽  
Ensemble Prediction ◽  
Prediction System ◽  
Sampling Errors ◽  
Seasonal Forecasts ◽  
Multimodel Ensemble ◽  
Ensemble Prediction System

Abstract A probabilistic multimodel ensemble prediction system (PMME) has been developed to provide operational seasonal forecasts at the Asia–Pacific Economic Cooperation (APEC) Climate Center (APCC). This system is based on an uncalibrated multimodel ensemble, with model weights inversely proportional to the errors in forecast probability associated with the model sampling errors, and a parametric Gaussian fitting method for the estimate of tercile-based categorical probabilities. It is shown that the suggested method is the most appropriate for use in an operational global prediction system that combines a large number of models, with individual model ensembles essentially differing in size and model weights in the forecast and hindcast datasets being inconsistent. Justification for the use of a Gaussian approximation of the precipitation probability distribution function for global forecasts is also provided. PMME retrospective and real-time forecasts are assessed. For above normal and below normal categories, temperature forecasts outperform climatology for a large part of the globe. Precipitation forecasts are definitely more skillful than random guessing for the extratropics and climatological forecasts for the tropics. The skill of real-time forecasts lies within the range of the interannual variability of the historical forecasts.

Sign in / Sign up

Export Citation Format

Share Document