scholarly journals BMA probabilistic forecasting of the 500hPa geopotential height over Northern Hemisphere using TIGGE multimodel ensemble forecasts

2018 ◽  
Author(s):  
Xiefei Zhi ◽  
Luying Ji
Keyword(s):  
Northern Hemisphere ◽  
Geopotential Height ◽  
Probabilistic Forecasting ◽  
Multimodel Ensemble ◽  
Ensemble Forecasts

scholarly journals Probabilistic Forecasting of the 500 hPa Geopotential Height over the Northern Hemisphere Using TIGGE Multi-model Ensemble Forecasts

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 253
Author(s):  
Luying Ji ◽  
Qixiang Luo ◽  
Yan Ji ◽  
Xiefei Zhi
Keyword(s):  
Northern Hemisphere ◽  
Geopotential Height ◽  
Prediction Skill ◽  
Ensemble Prediction ◽  
Lead Times ◽  
Height Distribution ◽  
Height Field ◽  
Probabilistic Forecasting ◽  
Ensemble Forecasts ◽  
Geopotential Height Field

Bayesian model averaging (BMA) and ensemble model output statistics (EMOS) were used to improve the prediction skill of the 500 hPa geopotential height field over the northern hemisphere with lead times of 1–7 days based on ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), and UK Met Office (UKMO) ensemble prediction systems. The performance of BMA and EMOS were compared with each other and with the raw ensembles and climatological forecasts from the perspective of both deterministic and probabilistic forecasting. The results show that the deterministic forecasts of the 500 hPa geopotential height distribution obtained from BMA and EMOS are more similar to the observed distribution than the raw ensembles, especially for the prediction of the western Pacific subtropical high. BMA and EMOS provide a better calibrated and sharper probability density function than the raw ensembles. They are also superior to the raw ensembles and climatological forecasts according to the Brier score and the Brier skill score. Comparisons between BMA and EMOS show that EMOS performs slightly better for lead times of 1–4 days, whereas BMA performs better for longer lead times. In general, BMA and EMOS both improve the prediction skill of the 500 hPa geopotential height field.

Skill and predictability in multimodel ensemble forecasts for Northern Hemisphere regions with dominant winter precipitation

2016 ◽  
Vol 48 (9-10) ◽  
pp. 3309-3324 ◽  
Author(s):  
Muhammad Azhar Ehsan ◽  
Michael K. Tippett ◽  
Mansour Almazroui ◽  
Muhammad Ismail ◽  
Ahmed Yousef ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Winter Precipitation ◽  
Multimodel Ensemble ◽  
Ensemble Forecasts

scholarly journals A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size

2007 ◽  
Vol 135 (4) ◽  
pp. 1424-1438 ◽  
Author(s):  
Andrew R. Lawrence ◽  
James A. Hansen
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Ensemble Forecast ◽  
Ensemble Forecasting ◽  
Limited Area ◽  
Ensemble Size ◽  
Probabilistic Forecasting ◽  
Ensemble Forecasts ◽  
Chaotic Model ◽  
The Impact

Abstract An ensemble-based data assimilation approach is used to transform old ensemble forecast perturbations with more recent observations for the purpose of inexpensively increasing ensemble size. The impact of the transformations are propagated forward in time over the ensemble’s forecast period without rerunning any models, and these transformed ensemble forecast perturbations can be combined with the most recent ensemble forecast to sensibly increase forecast ensemble sizes. Because the transform takes place in perturbation space, the transformed perturbations must be centered on the ensemble mean from the most recent forecasts. Thus, the benefit of the approach is in terms of improved ensemble statistics rather than improvements in the mean. Larger ensemble forecasts can be used for numerous purposes, including probabilistic forecasting, targeted observations, and to provide boundary conditions to limited-area models. This transformed lagged ensemble forecasting approach is explored and is shown to give positive results in the context of a simple chaotic model. By incorporating a suitable perturbation inflation factor, the technique was found to generate forecast ensembles whose skill were statistically comparable to those produced by adding nonlinear model integrations. Implications for ensemble forecasts generated by numerical weather prediction models are briefly discussed, including multimodel ensemble forecasting.

A complex network analysis of extreme cyclones in the Arctic

2021 ◽  
Author(s):  
Dörthe Handorf ◽  
Ozan Sahin ◽  
Annette Rinke ◽  
Jürgen Kurths
Keyword(s):  
Complex Network ◽  
Northern Hemisphere ◽  
Extreme Events ◽  
Geopotential Height ◽  
Winter Season ◽  
Climate Extremes ◽  
The Arctic ◽  
Weather And Climate ◽  
Class 1 ◽  
Height Fields

<p>Under the rapid and amplified warming of the Arctic, changes in the occurrence of Arctic weather and climate extremes are evident which have substantial cryospheric and biophysical impacts like floods, droughts, coastal erosion or wildfires. Furthermore, these changes in weather and climate extremes have the potential to further amplify Arctic warming. <br>Here we study extreme cyclone events in the Arctic, which often occur during winter and are associated with extreme warming events that are caused by cyclone-related heat and moisture transport into the Arctic. In that way Arctic extreme cyclones have the potential to retard sea-ice growth in autumn and winter or to initiate an earlier melt-season onset. <br>To get a better understanding of these extreme cyclones and their occurrences in the Arctic, it is important to reveal the related atmospheric teleconnection patterns and understand their underlying mechanisms. In this study, the methodology of complex networks is used to identify teleconnections associated with extreme cyclones events (ECE) over Spitzbergen. We have chosen Spitzbergen, representative for the Arctic North Atlantic region which is a hot spot of Arctic climate change showing also significant recent changes in the occurrence of extreme cyclone events. <br>Complex climate networks have been successfully applied in the analysis of climate teleconnections during the last decade. To analyze time series of unevenly distributed extreme events, event synchronization (ES) networks are appropriate. Using this framework, we analyze the spatial patterns of significant synchronization between extreme cyclone events over the Spitzbergen area and extreme events in sea-level pressure (SLP) in the rest of the Northern hemisphere for the extended winter season from November to March. Based on the SLP fields from the newest atmospheric reanalysis ERA5, we constructed the ES networks over the time period 1979-2019.<br>The spatial features of the complex network topology like Eigenvector centrality, betweenness centrality and network divergence are determined and their general relation to storm tracks, jet streams and waveguides position is discussed. Link bundles in the maps of statistically significant links of ECEs over Spitzbergen with the rest of the Northern Hemisphere have revealed two classes of teleconnections: Class 1 comprises links from various regions of the Northern hemisphere to Spitzbergen, class 2 comprises links from Spitzbergen to various regions of the Northern hemisphere. For each class three specific teleconnections have been determined. By means of composite analysis, the corresponding atmospheric conditions are characterized.<br>As representative of class 1, the teleconnection between extreme events in SLP over the subtropical West Pacific and delayed ECEs at Spitzbergen is investigated. The corresponding lead-lag analysis of atmospheric fields of SLP, geopotential height fields and meridional wind fields suggests that the class 1 teleconnections are caused by tropical forcing of poleward emanating Rossby wave trains. As representative of class 2, the teleconnection between ECEs at Spitzbergen and delayed extreme events in SLP over Northwest Russia is analyzed. The corresponding lead-lag analysis of atmospheric fields of SLP and geopotential height fields from the troposphere to the stratosphere suggests that the class 2 teleconnections are caused by troposphere-stratosphere coupling processes.</p>

scholarly journals Statistical post-processing of ensemble forecasts of the height of new snow

2019 ◽  
Vol 26 (3) ◽  
pp. 339-357 ◽  
Author(s):  
Jari-Pekka Nousu ◽  
Matthieu Lafaysse ◽  
Matthieu Vernay ◽  
Joseph Bellier ◽  
Guillaume Evin ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Evaluation Criteria ◽  
Training Dataset ◽  
Post Processing ◽  
Probabilistic Forecasting ◽  
Ensemble Forecasts ◽  
Heterogeneous Model ◽  
The Impact

Abstract. Forecasting the height of new snow (HN) is crucial for avalanche hazard forecasting, road viability, ski resort management and tourism attractiveness. Météo-France operates the PEARP-S2M probabilistic forecasting system, including 35 members of the PEARP Numerical Weather Prediction system, where the SAFRAN downscaling tool refines the elevation resolution and the Crocus snowpack model represents the main physical processes in the snowpack. It provides better HN forecasts than direct NWP diagnostics but exhibits significant biases and underdispersion. We applied a statistical post-processing to these ensemble forecasts, based on non-homogeneous regression with a censored shifted Gamma distribution. Observations come from manual measurements of 24 h HN in the French Alps and Pyrenees. The calibration is tested at the station scale and the massif scale (i.e. aggregating different stations over areas of 1000 km2). Compared to the raw forecasts, similar improvements are obtained for both spatial scales. Therefore, the post-processing can be applied at any point of the massifs. Two training datasets are tested: (1) a 22-year homogeneous reforecast for which the NWP model resolution and physical options are identical to the operational system but without the same initial perturbations; (2) 3-year real-time forecasts with a heterogeneous model configuration but the same perturbation methods. The impact of the training dataset depends on lead time and on the evaluation criteria. The long-term reforecast improves the reliability of severe snowfall but leads to overdispersion due to the discrepancy in real-time perturbations. Thus, the development of reliable automatic forecasting products of HN needs long reforecasts as homogeneous as possible with the operational systems.

Observed Patterns of Month-to-Month Storm-Track Variability and Their Relationship to the Background Flow*

2010 ◽  
Vol 67 (5) ◽  
pp. 1420-1437 ◽  
Author(s):  
Justin J. Wettstein ◽  
John M. Wallace
Keyword(s):  
Northern Hemisphere ◽  
Geopotential Height ◽  
Storm Track ◽  
Meridional Wind ◽  
Storm Tracks ◽  
Mean Flow ◽  
Annular Mode ◽  
The North ◽  
Jet Variability ◽  
The North Atlantic Oscillation

Abstract Month-to-month storm-track variability is investigated via EOF analyses performed on ERA-40 monthly-averaged high-pass filtered daily 850-hPa meridional heat flux and the variances of 300-hPa meridional wind and 500-hPa height. The analysis is performed both in hemispheric and sectoral domains of the Northern and Southern Hemispheres. Patterns characterized as “pulsing” and “latitudinal shifting” of the climatological-mean storm tracks emerge as the leading sectoral patterns of variability. Based on the analysis presented, storm-track variability on the spatial scale of the two Northern Hemisphere sectors appears to be largely, but perhaps not completely, independent. Pulsing and latitudinally shifting storm tracks are accompanied by zonal wind anomalies consistent with eddy-forced accelerations and geopotential height anomalies that project strongly on the dominant patterns of geopotential height variability. The North Atlantic Oscillation (NAO)–Northern Hemisphere annular mode (NAM) is associated with a pulsing of the Atlantic storm track and a meridional displacement of the upper-tropospheric jet exit region, whereas the eastern Atlantic (EA) pattern is associated with a latitudinally shifting storm track and an extension or retraction of the upper-tropospheric jet. Analogous patterns of storm-track and upper-tropospheric jet variability are associated with the western Pacific (WP) and Pacific–North America (PNA) patterns. Wave–mean flow relationships shown here are more clearly defined than in previous studies and are shown to extend through the depth of the troposphere. The Southern Hemisphere annular mode (SAM) is associated with a latitudinally shifting storm track over the South Atlantic and Indian Oceans and a pulsing South Pacific storm track. The patterns of storm-track variability are shown to be related to simple distortions of the climatological-mean upper-tropospheric jet.

Sign in / Sign up

Export Citation Format

Share Document