Improvement of Medium-Range Forecasts Using the Analog-Dynamical Method

2014 ◽  
Vol 142 (4) ◽  
pp. 1570-1587 ◽  
Author(s):  
Haipeng Yu ◽  
Jianping Huang ◽  
Jifan Chou
Keyword(s):  
Lead Time ◽  
Forecast Skill ◽  
Forecast Errors ◽  
Weather Forecasts ◽  
Planetary Scale ◽  
Anomaly Correlation Coefficient ◽  
Systematic Correction ◽  
Medium Range ◽  
Dynamical Method ◽  
Height Fields

Abstract This study further develops the analog-dynamical method and applies it to medium-range weather forecasts. By regarding the forecast field as a small disturbance superimposed on historical analog fields, historical analog errors can be used to estimate and correct forecast errors. This method is applied to 10-day forecasts from the Global and Regional Assimilation and Prediction System (GRAPES). Both the distribution of atmospheric circulation and the pattern of sea surface temperature (SST) are considered in choosing the analog samples from a historical dataset for 2001–10 based on NCEP Final (FNL) data. The results demonstrate that the analog-dynamical method greatly reduces forecast errors and extends the period of validity of the global 500-hPa height field by 0.8 days, which is superior to results obtained using systematic correction. The correction effect at 500 hPa is increasingly significant when the lead time increases. Although the analogs are selected using 500-hPa height fields, the forecast skill at all vertical levels is improved. The average increase of the anomaly correlation coefficient (ACC) is 0.07, and the root-mean-square error (RMSE) is decreased by 10 gpm on average at a lead time of 10 days. The magnitude of errors for most forecast fields, such as height, temperature, and kinetic energy is decreased considerably by inverse correction. The model improvement is primarily a result of improvement for planetary-scale waves, while the correction for synoptic-scale waves does not affect model forecast skill. As this method is easy to operate and transport to other sophisticated models, it could be appropriate for operational use.

scholarly journals The Impact of Analysis Error on Medium-Range Weather Forecasts

2008 ◽  
Vol 136 (9) ◽  
pp. 3425-3431 ◽  
Author(s):  
Kyle L. Swanson ◽  
Paul J. Roebber
Keyword(s):  
North Pacific Ocean ◽  
Forecast Skill ◽  
Ensemble Spread ◽  
Weather Forecasts ◽  
The North ◽  
Medium Range ◽  
Difference Fields ◽  
Height Fields ◽  
Analysis Error ◽  
The Impact

Abstract All meteorological analyzed fields contain errors, the magnitude of which ultimately determines the point at which a given forecast will fail. Here, the authors explore the extent to which analysis difference fields capture certain aspects of the actual but unknowable flow-dependent analysis error. The analysis difference fields considered here are obtained by subtracting the NCEP and ECMWF reanalysis 500-hPa height fields. It is shown that the magnitude of this 500-hPa analysis difference averaged over the North Pacific Ocean has a statistically significant impact on forecast skill over the continental United States well into the medium range (5 days). Further, it is shown that the impact of this analysis difference on forecast skill is similar to that of ensemble spread well into the medium range, a measure of forecast uncertainty currently used in the operational setting. Finally, the analysis difference and ensemble spread are shown to be independent; hence, the impact of these two quantities upon forecast skill is additive.

scholarly journals Origin and Impact of Initialization Shocks in Coupled Atmosphere–Ocean Forecasts*

2015 ◽  
Vol 143 (11) ◽  
pp. 4631-4644 ◽  
Author(s):  
David P. Mulholland ◽  
Patrick Laloyaux ◽  
Keith Haines ◽  
Magdalena Alonso Balmaseda
Keyword(s):  
Data Assimilation ◽  
Coupled System ◽  
Atmospheric Temperature ◽  
Ocean Model ◽  
Forecast Skill ◽  
Weather Forecasts ◽  
Model Component ◽  
Medium Range ◽  
Series Of Experiments ◽  
Coupled Data Assimilation

Abstract Current methods for initializing coupled atmosphere–ocean forecasts often rely on the use of separate atmosphere and ocean analyses, the combination of which can leave the coupled system imbalanced at the beginning of the forecast, potentially accelerating the development of errors. Using a series of experiments with the European Centre for Medium-Range Weather Forecasts coupled system, the magnitude and extent of these so-called initialization shocks is quantified, and their impact on forecast skill measured. It is found that forecasts initialized by separate oceanic and atmospheric analyses do exhibit initialization shocks in lower atmospheric temperature, when compared to forecasts initialized using a coupled data assimilation method. These shocks result in as much as a doubling of root-mean-square error on the first day of the forecast in some regions, and in increases that are sustained for the duration of the 10-day forecasts performed here. However, the impacts of this choice of initialization on forecast skill, assessed using independent datasets, were found to be negligible, at least over the limited period studied. Larger initialization shocks are found to follow a change in either the atmosphere or ocean model component between the analysis and forecast phases: changes in the ocean component can lead to sea surface temperature shocks of more than 0.5 K in some equatorial regions during the first day of the forecast. Implications for the development of coupled forecast systems, particularly with respect to coupled data assimilation methods, are discussed.

scholarly journals Predictability of a Mediterranean Tropical-Like Storm Downstream of the Extratropical Transition of Hurricane Helene (2006)

2013 ◽  
Vol 141 (6) ◽  
pp. 1943-1962 ◽  
Author(s):  
Florian P. Pantillon ◽  
Jean-Pierre Chaboureau ◽  
Patrick J. Mascart ◽  
Christine Lac
Keyword(s):  
Tropical Cyclone ◽  
Lead Time ◽  
Large Scale ◽  
Synoptic Situation ◽  
British Isles ◽  
Extratropical Transition ◽  
Ensemble Forecasts ◽  
Weather Forecasts ◽  
Warm Core ◽  
Medium Range

Abstract The extratropical transition (ET) of a tropical cyclone is known as a source of forecast uncertainty that can propagate far downstream. The present study focuses on the predictability of a Mediterranean tropical-like storm (Medicane) on 26 September 2006 downstream of the ET of Hurricane Helene from 22 to 25 September. While the development of the Medicane was missed in the deterministic forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) initialized before and during ET, it was contained in the ECMWF ensemble forecasts in more than 10% of the 50 members up to 108-h lead time. The 200 ensemble members initialized at 0000 UTC from 20 to 23 September were clustered into two nearly equiprobable scenarios after the synoptic situation over the Mediterranean. In the first and verifying scenario, Helene was steered northeastward by an upstream trough during ET and contributed to the building of a downstream ridge. A trough elongated farther downstream toward Italy and enabled the development of the Medicane in 9 of 102 members. In the second and nonverifying scenario, Helene turned southeastward during ET and the downstream ridge building was reduced. A large-scale low over the British Isles dominated the circulation in Europe and only 1 of 98 members forecasted the Medicane. The two scenarios resulted from a different phasing between Helene and the upstream trough. Sensitivity experiments performed with the Méso-NH model further revealed that initial perturbations targeted on Helene and the upstream trough were sufficient in forecasting the warm-core Medicane at 84- and 108-h lead time.

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>

Strong Trends in the Skill of the ERA-40 and NCEP–NCAR Reanalyses in the High and Midlatitudes of the Southern Hemisphere, 1958–2001*

2004 ◽  
Vol 17 (23) ◽  
pp. 4603-4619 ◽  
Author(s):  
David H. Bromwich ◽  
Ryan L. Fogt
Keyword(s):  
Satellite Data ◽  
Austral Winter ◽  
Weather Forecasts ◽  
Atmospheric Research ◽  
June July August ◽  
Medium Range ◽  
Height Fields ◽  
Environmental Prediction ◽  
June July ◽  
High Level

Abstract The European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis (NCEP1) data are compared with Antarctic and other mid- to high-latitude station observations for the complete years of overlap, 1958–2001. Overall, it appears that ERA-40 more closely follows the observations; however, a more detailed look at the presatellite era reveals many shortcomings in ERA-40, particularly in the austral winter. By calculating statistics in 5-yr moving windows for June–July–August (JJA), it is shown that ERA-40 correlations with observed MSLP and surface (2 m) temperatures are low and even negative during the mid-1960s. A significant trend in skill in ERA-40 is observed in conjunction with the assimilation of satellite data during winter, eventually reaching a high level of skill after 1978 that is superior to NCEP1. NCEP1 shows consistency in its correlation with observations throughout time in this season; however, the biases in the NCEP1 MSLP fields decrease significantly with time. Similar problems are also found in the 500-hPa geopotential height fields above the direct influences of the mountainous topography. The height differences between ERA-40 and NCEP1 over the South Pacific are substantial before the modern satellite era throughout the depth of the troposphere. The ability for ERA-40 to be more strongly constrained by the satellite data compared to NCEP1, which is largely constrained by the station observational network, suggests that the differing assimilation schemes between ERA-40 and NCEP1 lead to the large discrepancies seen here. Thus, both reanalyses must be used with caution over high southern latitudes during the nonsummer months prior to the assimilation of satellite sounding data.

scholarly journals Winter Subseasonal Wind Speed Forecasts for Finland from ECMWF

2021 ◽  
Vol 18 ◽  
pp. 127-134
Author(s):  
Otto Hyvärinen ◽  
Terhi K. Laurila ◽  
Olle Räty ◽  
Natalia Korhonen ◽  
Andrea Vajda ◽  
...  
Keyword(s):  
Wind Speed ◽  
Lead Time ◽  
Reference Data ◽  
Data Sets ◽  
Weather Forecasts ◽  
The Third ◽  
Probabilistic Forecasts ◽  
Medium Range ◽  
Mean Wind Speed ◽  
Gaussian Regression

Abstract. The subseasonal forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts) were used to construct weekly mean wind speed forecasts for the spatially aggregated area in Finland. Reforecasts for the winters (November, December and January) of 2016–2017 and 2017–2018 were analysed. The ERA-Interim reanalysis was used as observations and climatological forecasts. We evaluated two types of forecasts, the deterministic forecasts and the probabilistic forecasts. Non-homogeneous Gaussian regression was used to bias-adjust both types of forecasts. The forecasts proved to be skilful until the third week, but the longest skilful lead time depends on the reference data sets and the verification scores used.

The role of arctic forecast errors in the evolution of northern extra-tropical forecast skill

2020 ◽  
Author(s):  
Thomas Haiden
Keyword(s):  
Forecast Error ◽  
Weather Prediction ◽  
Polar Vortex ◽  
Forecast Skill ◽  
The Arctic ◽  
Forecast Errors ◽  
Ensemble Forecasts ◽  
Medium Range Forecast ◽  
Medium Range

<p><br>Increases in extra-tropical numerical weather prediction (NWP) skill over the last decades have been well documented. The role of the Arctic, defined here as the area north of 60N, in driving (or slowing) this improvement has however not been systematically assessed. To investigate this question, spatial patterns of changes in medium-range forecast error of ECMWF’s Integrated Forecast System (IFS) are analysed both for deterministic and ensemble forecasts. The robustness of these patterns is evaluated by comparing results for different parameters and levels, and by comparing them with the respective changes in ERA5 forecasts, which are based on a ‘frozen’ model version. In this way the effect of different atmospheric variability on the estimation of skill improvement can be minimized. It is shown to what extent the strength of the polar vortex as measured by the Arctic and North-Atlantic Oscillation (AO, NAO) influences the magnitude of forecast errors. Results may indicate whether recent and future changes in these indices, possibly driven in part by sea-ice decline, could systematically affect the longer-term evolution of medium-range forecast skill.</p>

scholarly journals Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

2012 ◽  
Vol 16 (8) ◽  
pp. 2825-2838 ◽  
Author(s):  
S. Shukla ◽  
N. Voisin ◽  
D. P. Lettenmaier
Keyword(s):  
Weather Forecast ◽  
Forecast Skill ◽  
Prediction Skill ◽  
Infiltration Capacity ◽  
Forecast Period ◽  
Medium Range Weather Forecast ◽  
Weather Forecasts ◽  
Medium Range ◽  
Hydrologic Prediction ◽  
Potential Improvement

Abstract. We investigated the contribution of medium range weather forecasts with lead times of up to 14 days to seasonal hydrologic prediction skill over the conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP) based experiments were performed for the period 1980–2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980–2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts for runoff [SM] forecasts generally varies from 0 to 0.8 [0 to 0.5] as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

scholarly journals Evaluating CFSv2 Subseasonal Forecast Skill with an Emphasis on Tropical Convection

2017 ◽  
Vol 145 (9) ◽  
pp. 3795-3815 ◽  
Author(s):  
Nicholas J. Weber ◽  
Clifford F. Mass
Keyword(s):  
Lead Time ◽  
Large Scale ◽  
Tropical Convection ◽  
Forecast Skill ◽  
Lead Times ◽  
Forecast Errors ◽  
Predictive Skill ◽  
Forecast Lead Time ◽  
Temporal Averaging ◽  
Total Variability

This study examines the subseasonal predictive skill of CFSv2, focusing on the spatial and temporal distributions of error for large-scale atmospheric variables and the realism of simulated tropical convection. Errors in a 4-member CFSv2 ensemble forecast saturate at lead times of approximately 3 weeks for 500-hPa geopotential height and 5 weeks for 200-hPa velocity potential. Forecast errors exceed those of climatology at lead times beyond 2 weeks. Sea surface temperature, which evolves more slowly than atmospheric fields, maintains skill over climatology through the first month. Spatial patterns of error are robust across lead times and temporal averaging periods, increasing in amplitude as lead time increases and temporal averaging period decreases. Several significant biases were found in the CFSv2 reforecasts, such as too little convection over tropical land and excessive convection over the ocean. The realism of simulated tropical convection and associated teleconnections degrades with forecast lead time. Large-scale tropical convection in CFSv2 is more stationary than observed. Forecast MJOs propagate eastward too slowly and those initiated over the Indian Ocean have trouble traversing beyond the Maritime Continent. The total variability of simulated propagating convection is concentrated at lower frequencies compared to observed convection, and is more fully described by a red spectrum, indicating weak representation of convectively coupled waves. These flaws in simulated tropical convection, which could be tied to problems with convective parameterization and associated mean state biases, affect atmospheric teleconnections and may degrade extended global forecast skill.

scholarly journals Wave Activity Events and the Variability of the Stratospheric Polar Vortex

2014 ◽  
Vol 27 (20) ◽  
pp. 7796-7806 ◽  
Author(s):  
Abraham Solomon
Keyword(s):  
Polar Vortex ◽  
Wave Activity ◽  
Stratospheric Polar Vortex ◽  
Weather Forecasts ◽  
Planetary Scale ◽  
Intraseasonal Variations ◽  
Medium Range ◽  
Polar Stratosphere ◽  
Hemisphere Winter ◽  
Wave Induced

Abstract During Northern Hemisphere winter, polar stratospheric winds and temperatures exhibit significant variability that is due to the vertical propagation of planetary-scale waves. The most dramatic intraseasonal variations in temperature are associated with sudden stratospheric warmings (SSWs), which are wave-breaking events that occur approximately every other year. This paper will introduce the concept of wave activity events (WAEs), which are periods of enhanced pseudomomentum density in the polar stratosphere that occur every year. It will be demonstrated that all SSWs are associated with WAEs; furthermore, minor warmings and many final warmings in the polar spring are also WAEs, and therefore a better understanding of these more frequent wave events can provide additional insights into stratospheric wave-induced variability. Employing the Interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) for 1979–2011, 119 WAEs are identified and their life cycle is compared with that of the 23 SSWs observed during this period.

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