scholarly journals Use of Multiensemble Track Clustering to Inform Medium-Range Tropical Cyclone Forecasts

2020 ◽  
Vol 35 (4) ◽  
pp. 1407-1426
Author(s):  
Alex M. Kowaleski ◽  
Jenni L. Evans
Keyword(s):  
Tropical Cyclone ◽  
Forecast Errors ◽  
Mean Error ◽  
Ensemble Mean ◽  
Cluster Properties ◽  
The Mean ◽  
Regression Mixture ◽  
Small Clusters ◽  
The Relationship ◽  
Average Cluster

AbstractTropical cyclone ensemble track forecasts from 153 initialization times during 2017–18 are clustered using regression mixture models. Clustering is performed on a four-ensemble dataset [ECMWF + GEFS + UKMET + CMC (EGUC)], and a three-ensemble dataset that excludes the CMC (EGU). For both datasets, five-cluster partitions are selected to analyze, and the relationship between cluster properties (size, ensemble composition) and 96–144-h cluster-mean error is evaluated. For both datasets, small clusters produce very large errors, with the least populous cluster producing the largest error in more than 50% of forecasts. The mean of the most populous EGUC cluster outperforms the most accurate (EGU) ensemble mean in only 43% of forecasts; however, when the most populous EGUC cluster from each forecast contains ≥30% of the ensemble population, its average cluster-mean error is significantly reduced compared to when the most populous cluster is smaller. Forecasts with a highly populous EGUC cluster also appear to have smaller EGUC-, EGU-, and ECMWF-mean errors. Cluster-mean errors also vary substantially by the ensembles composing the cluster. The most accurate clusters are EGUC clusters that contain threshold memberships of ECMWF, GEFS, and UKMET, but not CMC. The elevated accuracy of EGUC CMC-excluding clusters indicates the potential utility of including the CMC in clustering, despite its large ensemble-mean errors. Pruning ensembles by removing members that belong to small clusters reduces 96–144-h forecast errors for both EGUC and EGU clustering. For five-cluster partitions, a pruning threshold of 10% affects 49% and 35% of EGUC and EGU ensembles, respectively, improving 69%–74% of the forecasts affected by pruning.

scholarly journals Is Autonomy Always Beneficial for Work Engagement? A Six-year Four-Wave Follow-Up Study

2020 ◽  
Vol 6 (1) ◽  
pp. 16-27
Author(s):  
Piia Seppälä ◽  
Anne Mäkikangas ◽  
Jari J. Hakanen ◽  
Asko Tolvanen ◽  
Taru Feldt
Keyword(s):  
Work Engagement ◽  
Initial Level ◽  
Multilevel Regression ◽  
Specific Point ◽  
Relationship Patterns ◽  
The Mean ◽  
Regression Mixture ◽  
The Relationship ◽  
Predictive Relationship

Work engagement is expected to result from job resources such as autonomy. However, previous results have yielded that the autonomy–work engagement relationship is not always particularly strong. Whereas previous longitudinal studies have examined this relationship as an average at a specific point in time, this study examined whether this relationship is different within individuals from one time to another over the years. Furthermore, experiences of work engagement are expected to affect how employees benefit from autonomy, but no studies have so far investigated whether the initial level of work engagement affects the autonomy–work engagement relationship. This study aimed to first identify the different kinds of longitudinal relationship patterns between autonomy and work engagement, and then to investigate whether the identified relationship patterns differ in terms of the initial mean level of work engagement. The four-wave study was conducted among Finnish managers (n = 329) over a period of six years. Multilevel regression mixture analysis identified five relationship patterns. Four of the patterns showed a positive predictive relationship between autonomy and work engagement. However, the relationship was statistically significant in only one of these patterns. Furthermore, when the initial mean level of work engagement was high, autonomy related more strongly to work engagement. However, an atypical pattern was identified that showed a negative association between autonomy and work engagement. In this pattern, the mean level of work engagement was low. Consequently, autonomy may not always enhance work engagement; sometimes this relationship may even be negative.

The Relationship between Deterministic and Ensemble Mean Forecast Errors Revealed by Global and Local Attractor Radii

2019 ◽  
Vol 36 (3) ◽  
pp. 271-278 ◽  
Author(s):  
Jie Feng ◽  
Jianping Li ◽  
Jing Zhang ◽  
Deqiang Liu ◽  
Ruiqiang Ding
Keyword(s):  
Forecast Errors ◽  
Ensemble Mean ◽  
Local Attractor ◽  
Global And Local ◽  
The Relationship

Initial Condition Sensitivity of Western Pacific Extratropical Transitions Determined Using Ensemble-Based Sensitivity Analysis

2009 ◽  
Vol 137 (10) ◽  
pp. 3388-3406 ◽  
Author(s):  
Ryan D. Torn ◽  
Gregory J. Hakim
Keyword(s):  
Sensitivity Analysis ◽  
Tropical Cyclone ◽  
Initial Conditions ◽  
Forecast Error ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Forecast Errors ◽  
Initial Condition ◽  
Ensemble Forecasts ◽  
The Relationship

Abstract An ensemble Kalman filter based on the Weather Research and Forecasting (WRF) model is used to generate ensemble analyses and forecasts for the extratropical transition (ET) events associated with Typhoons Tokage (2004) and Nabi (2005). Ensemble sensitivity analysis is then used to evaluate the relationship between forecast errors and initial condition errors at the onset of transition, and to objectively determine the observations having the largest impact on forecasts of these storms. Observations from rawinsondes, surface stations, aircraft, cloud winds, and cyclone best-track position are assimilated every 6 h for a period before, during, and after transition. Ensemble forecasts initialized at the onset of transition exhibit skill similar to the operational Global Forecast System (GFS) forecast and to a WRF forecast initialized from the GFS analysis. WRF ensemble forecasts of Tokage (Nabi) are characterized by relatively large (small) ensemble variance and greater (smaller) sensitivity to the initial conditions. In both cases, the 48-h forecast of cyclone minimum SLP and the RMS forecast error in SLP are most sensitive to the tropical cyclone position and to midlatitude troughs that interact with the tropical cyclone during ET. Diagnostic perturbations added to the initial conditions based on ensemble sensitivity reduce the error in the storm minimum SLP forecast by 50%. Observation impact calculations indicate that assimilating approximately 40 observations in regions of greatest initial condition sensitivity produces a large, statistically significant impact on the 48-h cyclone minimum SLP forecast. For the Tokage forecast, assimilating the single highest impact observation, an upper-tropospheric zonal wind observation from a Mongolian rawinsonde, yields 48-h forecast perturbations in excess of 10 hPa and 60 m in SLP and 500-hPa height, respectively.

Wavelet spectra and filtering of tropical cyclone forecast errors

2018 ◽  
Vol 16 (03) ◽  
pp. 1850011
Author(s):  
D. H. Smith
Keyword(s):  
Tropical Cyclone ◽  
Feature Detection ◽  
Local Error ◽  
Forecast Errors ◽  
Cyclone Track ◽  
Sea Level Pressure ◽  
Compression Performance ◽  
Wavelet Expansions ◽  
Ensemble Mean ◽  
Structural Differences

Ensemble mean forecast errors during a tropical cyclone event are probed with a spherical wavelet transform constructed by the lifting scheme. Coefficient spectra and associated filtered error components are examined during the forecast, with an emphasis on feature detection, for mean sea level pressure and wind components. Leading wavelet coefficients within a reference circle centered on the estimated cyclone track demonstrate a clear affinity for local error extrema, reflecting the transform’s feature detection capacity. Compression performance of the transform is also demonstrated by truncated wavelet expansions, which exhibit contrasting behavior reflecting fundamental structural differences between the wind and pressure error fields.

scholarly journals On the Decay of Tropical Cyclone Winds Crossing Narrow Landmasses

2006 ◽  
Vol 45 (3) ◽  
pp. 491-499 ◽  
Author(s):  
Mark DeMaria ◽  
John A. Knaff ◽  
John Kaplan
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Absolute Error ◽  
Total Sample ◽  
Forecast Errors ◽  
Modified Model ◽  
Decay Model ◽  
Prediction Scheme ◽  
Fixed Radius ◽  
The Mean

Abstract A method is developed to adjust the Kaplan and DeMaria tropical cyclone inland wind decay model for storms that move over narrow landmasses. The basic assumption that the wind speed decay rate after landfall is proportional to the wind speed is modified to include a factor equal to the fraction of the storm circulation that is over land. The storm circulation is defined as a circular area with a fixed radius. Application of the modified model to Atlantic Ocean cases from 1967 to 2003 showed that a circulation radius of 110 km minimizes the bias in the total sample of landfalling cases and reduces the mean absolute error of the predicted maximum winds by about 12%. This radius is about 2 times the radius of maximum wind of a typical Atlantic tropical cyclone. The modified decay model was applied to the Statistical Hurricane Intensity Prediction Scheme (SHIPS), which uses the Kaplan and DeMaria decay model to adjust the intensity for the portion of the predicted track that is over land. The modified decay model reduced the intensity forecast errors by up to 8% relative to the original decay model for cases from 2001 to 2004 in which the storm was within 500 km from land.

scholarly journals Ensemble Mean Storm-Scale Performance in the Presence of Nonlinearity

2015 ◽  
Vol 143 (12) ◽  
pp. 5115-5133 ◽  
Author(s):  
Michael A. Hollan ◽  
Brian C. Ancell
Keyword(s):  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Wrf Model ◽  
Forecast Errors ◽  
Ensemble Mean ◽  
Deterministic Solution ◽  
Significant Divergence ◽  
The Mean ◽  
And Control

Abstract The use of ensembles in numerical weather prediction models is becoming an increasingly effective method of forecasting. Many studies have shown that using the mean of an ensemble as a deterministic solution produces the most accurate forecasts. However, the mean will eventually lose its usefulness as a deterministic forecast in the presence of nonlinearity. At synoptic scales, this appears to occur between 12- and 24-h forecast time, and on storm scales it may occur significantly faster due to stronger nonlinearity. When this does occur, the question then becomes the following: Should the mean still be adhered to, or would a different approach produce better results? This paper will investigate the usefulness of the mean within a WRF Model utilizing an ensemble Kalman filter for severe convective events. To determine when the mean becomes unrealistic, the divergence of the mean of the ensemble (“mean”) and a deterministic forecast initialized from a set of mean initial conditions (“control”) are examined. It is found that significant divergence between the mean and control emerges no later than 6 h into a convective event. The mean and control are each compared to observations, with the control being more accurate for nearly all forecasts studied. For the case where the mean provides a better forecast than the control, an approach is offered to identify the member or group of members that is closest to the mean. Such a forecast will contain similar forecast errors as the mean, but unlike the mean, will be on an actual forecast trajectory.

scholarly journals A Probabilistic Tropical Cyclone Track Forecast Scheme Based on the Selective Consensus of Ensemble Prediction Systems

2017 ◽  
Vol 32 (6) ◽  
pp. 2143-2157 ◽  
Author(s):  
Xiping Zhang ◽  
Hui Yu
Keyword(s):  
Tropical Cyclone ◽  
Ensemble Prediction ◽  
Lead Times ◽  
Track Forecast ◽  
Forecast Errors ◽  
Forecast Uncertainty ◽  
Ensemble Prediction System ◽  
The Mean ◽  
Environmental Prediction ◽  
Uncertainty Information

Abstract Selective consensus and a grand ensemble based on an ensemble prediction system (EPS) have been found to be effective in improving deterministic tropical cyclone (TC) track forecasts, while little attention has been paid to quantitative applications of the forecast uncertainty information provided by EPSs. In this paper the forecast uncertainty information is evaluated for two operational EPSs and their grand ensemble. Then, a probabilistic TC track forecast scheme is proposed based on the selective consensus of the two EPSs; this scheme is composed of member picking, mean track shifting, and probability ellipses. The operational EPSs are from the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS) and the National Centers for Environmental Prediction (NCEP-GEFS). Evaluation exhibits that the hit ratios of ECMWF-EPS are above 80% for the 70% probability ellipses at all lead times until 120 h and are used in the proposed scheme. The other components of the proposed scheme are about picking potentially good EPS members. A picking ratio of 1/2 is found to be the best choice, and the member-picking technique is used for the grand ensemble but only for lead times out to 48 h. For lead times longer than 48 h, all of the grand ensemble members are used in obtaining the mean track. The effectiveness of the proposed scheme shows a 10% improvement in the mean track forecast errors over the grand ensemble and a 4.5% improvement in the hit ratio of 70% probability ellipses over the ECMWF-EPS at 24 h, demonstrating its good potential to be applied in operations.

OBEST: An Observation-Based Ensemble Subsetting Technique for Tropical Cyclone Track Prediction

2016 ◽  
Vol 31 (1) ◽  
pp. 57-70 ◽  
Author(s):  
Lin Dong ◽  
Fuqing Zhang
Keyword(s):  
Tropical Cyclone ◽  
Lead Times ◽  
Track Forecast ◽  
Forecast Errors ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Weather Forecasts ◽  
Ensemble Mean ◽  
Medium Range ◽  
Environmental Prediction

Abstract An observation-based ensemble subsetting technique (OBEST) is developed for tropical cyclone track prediction in which a subset of members from either a single- or multimodel ensemble is selected based on the distance from the latest best-track position. The performance of OBEST is examined using both the 2-yr hindcasts for 2010–11 and the 2-yr operational predictions during 2012–13. It is found that OBEST outperforms both the simple ensemble mean (without subsetting) and the corresponding deterministic high-resolution control forecast for most forecast lead times up to 5 days. Applying OBEST to a superensemble of global ensembles from both the European Centre for Medium-Range Weather Forecasts and the National Centers for Environmental Prediction yielded a further reduction in track forecast errors by 5%–10% for lead times of 24–120 h.

The relationship of IGE receptor topography to signaling activity in RBL-2H3 mast cells

1991 ◽  
Vol 49 ◽  
pp. 236-237
Author(s):  
J.R. Pfeiffer ◽  
J.C. Seagrave ◽  
C. Wofsy ◽  
J.M. Oliver
Keyword(s):  
Mast Cells ◽  
Protein A ◽  
Scattered Electron ◽  
Ige Receptor ◽  
Receptor Complexes ◽  
Ige Binding ◽  
Electron Imaging ◽  
Small Clusters ◽  
Relationship Of ◽  
The Relationship

In RBL-2H3 rat leukemic mast cells, crosslinking IgE-receptor complexes with anti-IgE antibody leads to degranulation. Receptor crosslinking also stimulates the redistribution of receptors on the cell surface, a process that can be observed by labeling the anti-IgE with 15 nm protein A-gold particles as described in Stump et al. (1989), followed by back-scattered electron imaging (BEI) in the scanning electron microscope. We report that anti-IgE binding stimulates the redistribution of IgE-receptor complexes at 37“C from a dispersed topography (singlets and doublets; S/D) to distributions dominated sequentially by short chains, small clusters and large aggregates of crosslinked receptors. These patterns can be observed (Figure 1), quantified (Figure 2) and analyzed statistically. Cells incubated with 1 μg/ml anti-IgE, a concentration that stimulates maximum net secretion, redistribute receptors as far as chains and small clusters during a 15 min incubation period. At 3 and 10 μg/ml anti-IgE, net secretion is reduced and the majority of receptors redistribute rapidly into clusters and large aggregates.

Multi-Center Calibration of the Second Reference Material for Thromboplastin, Rabbit, Plain, Coded CRM 149R

1991 ◽  
Vol 65 (03) ◽  
pp. 263-267 ◽  
Author(s):  
A M H P van den Besselaar ◽  
R M Bertina
Keyword(s):  
Reference Material ◽  
Standard Error ◽  
Standard Errors ◽  
Sensitivity Index ◽  
Long Term Stability ◽  
Significant Bias ◽  
The Mean ◽  
The Relationship ◽  
International Sensitivity Index

SummaryIn a collaborative trial of eleven laboratories which was performed mainly within the framework of the European Community Bureau of Reference (BCR), a second reference material for thromboplastin, rabbit, plain, was calibrated against its predecessor RBT/79. This second reference material (coded CRM 149R) has a mean International Sensitivity Index (ISI) of 1.343 with a standard error of the mean of 0.035. The standard error of the ISI was determined by combination of the standard errors of the ISI of RBT/79 and the slope of the calibration line in this trial.The BCR reference material for thromboplastin, human, plain (coded BCT/099) was also included in this trial for assessment of the long-term stability of the relationship with RBT/79. The results indicated that this relationship has not changed over a period of 8 years. The interlaboratory variation of the slope of the relationship between CRM 149R and RBT/79 was significantly lower than the variation of the slope of the relationship between BCT/099 and RBT/79. In addition to the manual technique, a semi-automatic coagulometer according to Schnitger & Gross was used to determine prothrombin times with CRM 149R. The mean ISI of CRM 149R was not affected by replacement of the manual technique by this particular coagulometer.Two lyophilized plasmas were included in this trial. The mean slope of relationship between RBT/79 and CRM 149R based on the two lyophilized plasmas was the same as the corresponding slope based on fresh plasmas. Tlowever, the mean slope of relationship between RBT/79 and BCT/099 based on the two lyophilized plasmas was 4.9% higher than the mean slope based on fresh plasmas. Thus, the use of these lyophilized plasmas induced a small but significant bias in the slope of relationship between these thromboplastins of different species.

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