Quality of the ERA5 and CFSR winds and their contribution to wave modelling performance in a semi-closed sea

Çalışır, Emre; Soran, Mehmet Burak; Akpınar, Adem

doi:10.1080/1755876x.2021.1911126

Cited by 15 publications

(6 citation statements)

References 59 publications

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“…Our findings regarding ERA5's good performance in the spatially‐averaged 10‐m wind speeds but a systematic underestimation at moderate and strong intensities are in general agreement with previous studies evaluating ERA5 against the buoy and satellite data over the ocean (e.g., Çalışır et al, 2023; Campos et al, 2022). Campos et al (2022) reported an underestimation of the long‐term mean wind speed by 10%–15% conditioned on the presence of cyclones over the central and western North Atlantic.…”

Section: Discussionsupporting

confidence: 92%

Evaluation of ERA5 precipitation and 10‐m wind speed associated with extratropical cyclones using station data over North America

Chen,

Collet,

Di Luca

2024

Intl Journal of Climatology

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While the ERA5 reanalysis is commonly utilized in climate studies on extratropical cyclones (ETCs), only a few studies have quantified its ability in the representation of ETCs over land. To address this gap, this study evaluates ERA5's skill in representing the ETC‐associated 10‐m wind speed and the precipitation in central and eastern North America during 2005–2019. Hourly data collected from ~3000 stations, amounting to around 420 million reports stored in the Integrated Surface Database, is used as reference. For the spatial‐averaged ETC properties, ERA5 shows a good skill for wind speed with normalized mean bias (NMB) of −0.7% and normalized root‐mean‐square error (NRMSE) of 14.3%, despite a tendency to overestimate low winds and underestimate high winds. The ERA5 skill is worse for precipitation than for wind speed with NMB of −10.4% and NRMSE of 56.5% and a strong tendency to underestimate high values. For both variables, the best and worst performance is found in DJF and JJA, respectively. Negative biases are often identified over regions with stronger precipitation/wind speeds, and a systematic underestimation of wind speed is found over the Rockies with complex topography. Compared to the averaged ETCs, ERA5's performance deteriorates for the top 5% extreme ETCs with a stronger tendency to underestimate both wind speed and precipitation (NMB of −10.2% and −22.6%, respectively). Furthermore, ERA5's skill is worse for local extreme values within ETCs than for spatial averages. Our results highlight some important limitations of the ERA5 reanalysis products for studies looking at the possible impacts of ETCs.

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Section: Discussionsupporting

confidence: 92%

Evaluation of ERA5 precipitation and 10‐m wind speed associated with extratropical cyclones using station data over North America

Chen,

Collet,

Di Luca

2024

Intl Journal of Climatology

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“…ERA5 winds were deeply investigated [33][34][35], including validations using scatterometer data [36]. The aforementioned studies highlight the better quality of ERA5 compared to its predecessors.…”

Section: Introductionmentioning

confidence: 99%

Assessment and Calibration of ERA5 Severe Winds in the Atlantic Ocean Using Satellite Data

et al. 2022

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In this paper, we analyze the surface winds of ECMWF ERA5 reanalysis in the Atlantic Ocean. The first part addresses a reanalysis validation, studying the spatial distribution of the errors and the performance as a function of the percentiles, with a further investigation under cyclonic conditions. The second part proposes and compares two calibration models, a simple least-squares linear regression (LR) and the quantile mapping method (QM). Our results indicate that ERA5 provides high-quality winds for non-extreme conditions, especially at the eastern boundaries, with bias between −0.5 and 0.3 m/s and RMSE below 1.5 m/s. The reanalysis errors are site-dependent, where large RMSE and severe underestimation are found in tropical latitudes and locations following the warm currents. The most extreme winds in tropical cyclones show the worst results, with RMSE above 5 m/s. Apart from these areas, the strong winds at extratropical locations are well represented. The bias-correction models have proven to be very efficient in removing systematic bias. The LR works well for low-to-mild wind intensities while the QM is better for the upper percentiles and winds above 15 m/s—an improvement of 10% in RMSE and 50% for the bias compared to the original reanalysis is reported.

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“…The difference in the median and extreme wind speeds in reanalyses in South Atlantic basin was already discussed by Cardoso (2019) and Crespo et al (2022), who showed that compared with coastal buoys ERA5 has smaller biases in representation of the mean wind speed, while CFSR is better for the extreme winds. Moreover, other studies for different regions of the globe also reported this aspect (e.g., Çalışır et al, 2021;Thomas et al, 2021). Many aspects distinguish CFSR from ERA5, such as horizontal resolution (∼38 vs. 25 km), assimilation techniques and data, dynamic cores and physical parameterizations of the models.…”

Section: Climatology Of the Extreme Wind Speed At 10-m Heightmentioning

confidence: 83%

Synoptic Climatology of Subtropical Cyclone Impacts on Near‐Surface Winds Over the South Atlantic Basin

Cardoso

Rocha

Crespo

2022

Earth and Space Science

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Winds and precipitation are two meteorological variables of great impact on the economy and society, especially when extreme events occur. The objective of this study is to investigate the subtropical cyclone (SC) impacts on near‐surface wind extremes (defined by 95th percentile) and precipitation in the South Atlantic basin. For the period 1979–2015, the analysis used two reanalysis data (ERA5 and Climate Forecast System Reanalysis [CFSR]) and estimated precipitation from the Tropical Rainfall Measuring Mission (TRMM) considering the extended warm (from September to February) and cold (from March to August) seasons. A total of 169 SCs occurred in the warm season against 87 in the cold one. Two approaches are used to quantify SC impacts: Lagrangian, where the composites follow the cyclone center, and Eulerian, which considers the averaged environment during the cyclone lifecycle. In general, both approaches indicate SC contribution to the positive anomalies of mean and extreme near‐surface wind speeds to the east and northeast of a cyclogenetic region in southeastern Brazil (RG1). For all analyses conducted, wind speeds from CFSR are higher than in ERA5. The SC activity contributes to the enhancement of precipitation to the east and inside RG1 in an organized northwest‐southeast positive anomaly band from the continent to the ocean, while favoring drier conditions to the south. These positive precipitation anomalies are associated with an anomalous low pressure, low‐level moisture flux convergence and warm advection occurring at the same time with an upper‐level divergent flow near RG1. All these features are intensified in the cold season.

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Quality of the ERA5 and CFSR winds and their contribution to wave modelling performance in a semi-closed sea

Cited by 15 publications

References 59 publications

Evaluation of ERA5 precipitation and 10‐m wind speed associated with extratropical cyclones using station data over North America

Evaluation of ERA5 precipitation and 10‐m wind speed associated with extratropical cyclones using station data over North America

Assessment and Calibration of ERA5 Severe Winds in the Atlantic Ocean Using Satellite Data

Synoptic Climatology of Subtropical Cyclone Impacts on Near‐Surface Winds Over the South Atlantic Basin

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