Subseasonal Forecast Skill for Weekly Mean Atmospheric Variability Over the Northern Hemisphere in Winter and Its Relationship to Midlatitude Teleconnections

2020 ◽  
Vol 47 (17) ◽  
Author(s):  
Akio Yamagami ◽  
Mio Matsueda
Keyword(s):  
Northern Hemisphere ◽  
Forecast Skill ◽  
Atmospheric Variability

scholarly journals Hayashi spectra of the northern hemisphere mid-latitude atmospheric variability in the NCEP–NCAR and ECMWF reanalyses

2005 ◽  
Vol 25 (6) ◽  
pp. 639-652 ◽  
Author(s):  
Alessandro Dell’Aquila ◽  
Valerio Lucarini ◽  
Paolo M. Ruti ◽  
Sandro Calmanti
Keyword(s):  
Northern Hemisphere ◽  
Atmospheric Variability

scholarly journals Link Between Autumnal Arctic Sea Ice and Northern Hemisphere Winter Forecast Skill

2020 ◽  
Vol 47 (5) ◽  
Author(s):  
J. C. Acosta Navarro ◽  
P. Ortega ◽  
L. Batté ◽  
D. Smith ◽  
P. A. Bretonnière ◽  
...  
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Arctic Sea Ice ◽  
Forecast Skill ◽  
Arctic Sea ◽  
Hemisphere Winter ◽  
Northern Hemisphere Winter

scholarly journals A regime view of northern hemisphere atmospheric variability and change under global warming

2000 ◽  
Vol 27 (8) ◽  
pp. 1139-1142 ◽  
Author(s):  
A. H. Monahan ◽  
J. C. Fyfe ◽  
G. M. Flato
Keyword(s):  
Global Warming ◽  
Northern Hemisphere ◽  
Atmospheric Variability

Evaluation of systematic biases and skill of summer subseasonal forecasts in the ECMWF system

2020 ◽  
Author(s):  
Frederico Johannsen ◽  
Emanuel Dutra ◽  
Linus Magnusson
Keyword(s):  
Northern Hemisphere ◽  
Lead Time ◽  
Model Error ◽  
Forecast Skill ◽  
Daily Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Error Growth ◽  
Weather Forecasts ◽  
Systematic Biases

<p>Subseasonal forecasts (ranging between 2 weeks and 2 months) have been the subject of attention in many operational weather forecasts centers and by the research community in recent years. This growing attention stems from the value of these forecasts for society and from the scientific challenges involved. The scientific challenges of capturing and representing key processes and teleconnections which are relevant at these scales are significant. One example is temperature extremes associated with weather extremes like heatwaves and droughts that can have severe consequences in nature and human health, among others. Some of the limitations in forecast skill arise from the limits of predictability of the chaotic earth system. Model error is also likely to play a relevant role. In this study, we investigate systematic model biases, their evolution with lead time and potential links with forecast skill.</p><p>This study assessed the skill and biases of the European Centre for Medium-Range Weather Forecasts (ECMWF) subseasonal forecast in predicting the daily temperature extremes in the Northern Hemisphere. These forecasts are from an experimental setup of ECMWF extended-range forecast system. The forecasts compromise 11 ensemble members with weekly starting dates between 9 April to 30 July extending up to 6 weeks lead with a 20-years hindcast period (1998-2017). The forecasts were performed by the coupled ECMWF systems with TcO199 horizontal resolution (about 50km) in the atmosphere and 1x1 degree ocean. A particular focus is given to Europe and to two other regions that were identified with large systematic errors. The data used in this work consisted of the daily maximum and minimum two-meter temperature, precipitation and other surface fluxes that are aggregated into weekly means and verified against ERA5. </p><p>The evaluation of systematic biases in daily temperature extremes shows a clear increase with lead time, which is widespread on a hemispheric scale. The spatial patterns of model error growth with lead time are reasonably similar between daily maximum and minimum temperatures. However, the amplitude of the errors is remarkably different with general cold bias of daily maximum and warm bias of daily minimum that consistently grow with forecast lead time. Despite the consistent error growth with lead time, there are clear differences between the forecasts initialized in late Spring (April-May) and those in Summer (June-July). These biases are not fully collocated in two regions in the Northern Hemisphere showing the largest warm temperature biases: Central US and East of Caspian Sea. The warm biases are consistent with an underestimation of precipitation and dry soil moisture, compared to ERA5, but only over the East Caspian region.  Forecasts skill assessed via the anomaly correlation shows that the temperature forecasts are skillful up to week 2, with a drop in skill from week 3 onwards. This drop in skill is consistent over all the European domain. Similar results are found for precipitation, but with ACC at week 2 comparable with those of temperature at week 3. </p>

scholarly journals The Predictors and Forecast Skill of Northern Hemisphere Teleconnection Patterns for Lead Times of 3–4 Weeks

2017 ◽  
Vol 145 (7) ◽  
pp. 2855-2877 ◽  
Author(s):  
Jiaxin Black ◽  
Nathaniel C. Johnson ◽  
Stephen Baxter ◽  
Steven B. Feldstein ◽  
Daniel S. Harnos ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Geopotential Height ◽  
Longwave Radiation ◽  
Teleconnection Pattern ◽  
Forecast Skill ◽  
Lead Times ◽  
Least Squares Regression ◽  
Atmospheric Flow ◽  
Teleconnection Patterns ◽  
The Pacific

The Pacific–North American pattern (PNA), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO) are three dominant teleconnection patterns known to strongly affect December–February surface weather in the Northern Hemisphere. A partial least squares regression (PLSR) method is adopted in this study to generate wintertime two-week statistical forecasts of these three teleconnection pattern indices for lead times of up to five weeks over the 1980–2013 period. The PLSR approach generates forecasts for the teleconnection pattern indices by maximizing the variance explained by predictor indices determined as linear combinations of predictor fields, which include gridded outgoing longwave radiation (OLR), 300-hPa geopotential height (Z300), and 50-hPa geopotential height (Z50). Overall, the PLSR models yield statistically significant skill at all lead times up to five weeks. In particular, cross-validated correlations between the combined weeks 3–4 PLSR forecasts and verification for the PNA, NAO, and AO indices are 0.34, 0.28, and 0.41, respectively. The PLSR approach also allows the authors to isolate a small number of predictor patterns that help shed light on the sources of prediction skill for each teleconnection pattern. As expected, the results reveal the importance of tropical convection (OLR) for forecast skill in weeks 3–4, but the initial atmospheric flow (Z300) accounts for a substantial fraction of the skill as well. Overall, the results of this study provide promise for improving subseasonal-to-seasonal (S2S) forecasts and the physical understanding of predictability on these time scales.

scholarly journals The Impact of Increased Frequency of Rawinsonde Observations on Forecast Skill Investigated with an Observing System Simulation Experiment

2014 ◽  
Vol 142 (5) ◽  
pp. 1823-1834 ◽  
Author(s):  
N. C. Privé ◽  
R. M. Errico ◽  
K.-S. Tai
Keyword(s):  
Northern Hemisphere ◽  
Simulation Experiment ◽  
System Simulation ◽  
Forecast Skill ◽  
Cycle Times ◽  
Earth Observing System ◽  
Observing System Simulation Experiment ◽  
The Impact ◽  
Mean Square Errors ◽  
Analysis Quality

Abstract Most rawinsondes are launched once or twice daily, at 0000 and/or 1200 UTC; only a small number of the total rawinsonde observations are taken at 0600 and 1800 UTC (“off hour” cycle times). In this study, the variations of forecast and analysis quality between cycle times and the potential improvement of skill due to supplemental rawinsonde measurements at 0600 and 1800 UTC are tested in the framework of an observing system simulation experiment (OSSE). The National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA GMAO) Goddard Earth Observing System Model, version 5 (GEOS-5), is used with the GMAO OSSE setup for an experiment emulating the months of July and August with the 2011 observational network. The OSSE is run with and without supplemental rawinsonde observations at 0600 and 1800 UTC, and the differences in analysis error and forecast skill are quantified. The addition of supplemental rawinsonde observations results in significant improvement of analysis quality in the Northern Hemisphere for both the 0000/1200 and 0600/1800 UTC cycle times, with greater improvement for the off-hour times. Reduction of root-mean-square errors on the order of 1%–3% for wind and temperature is found at the 24- and 48-h forecast times. There is a slight improvement in Northern Hemisphere anomaly correlations at the 120-h forecast time.

scholarly journals High-Resolution Global Climate Simulations with the ECMWF Model in Project Athena: Experimental Design, Model Climate, and Seasonal Forecast Skill

2012 ◽  
Vol 25 (9) ◽  
pp. 3155-3172 ◽  
Author(s):  
T. Jung ◽  
M. J. Miller ◽  
T. N. Palmer ◽  
P. Towers ◽  
N. Wedi ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Seasonal Forecast ◽  
Horizontal Resolution ◽  
Forecast Skill ◽  
Boreal Winter ◽  
Project Athena ◽  
The Tropics ◽  
Ecmwf Model

The sensitivity to the horizontal resolution of the climate, anthropogenic climate change, and seasonal predictive skill of the ECMWF model has been studied as part of Project Athena—an international collaboration formed to test the hypothesis that substantial progress in simulating and predicting climate can be achieved if mesoscale and subsynoptic atmospheric phenomena are more realistically represented in climate models. In this study the experiments carried out with the ECMWF model (atmosphere only) are described in detail. Here, the focus is on the tropics and the Northern Hemisphere extratropics during boreal winter. The resolutions considered in Project Athena for the ECMWF model are T159 (126 km), T511 (39 km), T1279 (16 km), and T2047 (10 km). It was found that increasing horizontal resolution improves the tropical precipitation, the tropical atmospheric circulation, the frequency of occurrence of Euro-Atlantic blocking, and the representation of extratropical cyclones in large parts of the Northern Hemisphere extratropics. All of these improvements come from the increase in resolution from T159 to T511 with relatively small changes for further resolution increases to T1279 and T2047, although it should be noted that results from this very highest resolution are from a previously untested model version. Problems in simulating the Madden–Julian oscillation remain unchanged for all resolutions tested. There is some evidence that increasing horizontal resolution to T1279 leads to moderate increases in seasonal forecast skill during boreal winter in the tropics and Northern Hemisphere extratropics. Sensitivity experiments are discussed, which helps to foster a better understanding of some of the resolution dependence found for the ECMWF model in Project Athena.

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