Evaluation of HRCLDAS and ERA5 Datasets for Near-Surface Wind over Hainan Island and South China Sea

Jiang, Yi; Han, Shuai; Shi, Chunxiang; Gao, Tao; Zhen, Honghui; Liu, Xiaoyan

doi:10.3390/atmos12060766

Cited by 27 publications

(14 citation statements)

References 28 publications

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“…ERA5 is, as well, less reliable in areas of heterogeneous topography 28 , which could affect our results in Novoye Chaplino, Sireniki, and Pakhachi, as they are located near mountain ranges. Despite this, ERA5 has been found to usable in Europe 29 and the South China Sea 30 , so we therefore believe ERA5 reasonably represents meteorological conditions in Beringia, within a degree of uncertainty.…”

Section: Historical Recordmentioning

confidence: 77%

Coastal Sea-Ice Break-Up Events in Beringia

Aucoin

Tremblay

Newton

2022

MSURJ

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We quantify changes in break‐up events of landfast ice in the transition from a perennial to a seasonal sea ice cover in the Arctic. A break‐up event is defined as a time when coastal sea ice concentration drops below 95% after a minimum period of 10 days of stable ice conditions. To this end we analyze output diagnostics from the Community Earth System Model (Version 1) – Large Ensemble from 1920 to 2080, focusing on six coastal communities of Alaska, Chukotka, and the Kamtchatka Peninsula: Utqiaġvik, Point Hope, Gambell, Novoye Chaplino, Sireniki, and Pakhachi. Model results generally agree with the satellite record with open water formation along the coastline associated with sustained offshore winds, although the sensitivity of CESM1‐LE is higher than that of observations due to the absence of a landfast ice parameterization in CESM1‐ LE. Specifically, we see a linear relationship between the magnitude of the opening and offshore surface wind stresses integrated over the 10 days prior to the opening event, (p‐value < 0.01). While the break‐up event frequency increases (5.53 × 10−5 events/day/year for Utqiagvik) in the 21st century due to the thin- ning, or weakening, of the landfast ice cover, the total number of winter break‐up events decreases due to a shortening of the winter season (mean of ‐5.3 days/decade).

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Section: Historical Recordmentioning

confidence: 77%

Coastal Sea-Ice Break-Up Events in Beringia

Aucoin

Tremblay

Newton

2022

MSURJ

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“…Climate reanalysis has been widely used to overcome the absence of high-quality and long-term observational records for wind energy users. e new ERA5 dataset has been proven superior to the traditional MERRA2 product in predicting the regional distributions of wind resources in the South China Sea [24], Europe [25], America [26], and other areas worldwide [9]. Here, we analyzed the applicability of these two reanalyses in estimating tall tower wind characteristics using different statistical downscaling methods in South China.…”

Section: Discussionmentioning

confidence: 99%

Comparison of the Applicability of Two Reanalysis Products in Estimating Tall Tower Wind Based on Multiple Linear Regression and Artificial Neural Network in South China

Li¹,

Qin²,

Yang³

et al. 2022

Advances in Meteorology

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Climate reanalysis products have been widely used to overcome the absence of high-quality and long-term observational records for wind energy users. In this study, the applicability of two popular reanalysis datasets (ERA5 and MERRA2) in estimating wind characteristics for four tall tower observatories (TTOs) in South China was assessed. For each TTO, linear and nonlinear downscaling techniques, namely, multiple linear regression (MLR) and an artificial neural network (ANN), respectively, were adopted for the downscaling of the scalar wind speed and the corresponding U/V components. The downscaled wind speed and U/V components were subsequently compared with the TTO observations by correlation coefficient (Pearson’s r), the root mean square error (RMSE), the uncertainty analysis (U95), and the reliability analysis (RE). According to the results, ERA5 had a better applicability (higher Pearson’s r and RE, but lower RMSE and U95) in estimating TTO wind speed than MERRA2 when using both the MLR and ANN downscaling method. The average Pearson’s r, RE, RMSE, and U95 of the downscaled wind from ERA5 by the MLR (ANN) method were 0.66 (0.69), 40.8% (41.8%), 2.20 m/s (2.11 m/s), 0.181 m/s (0.179 m/s), respectively, and 0.60 (0.63), 38.0% (39.7%), 2.32 m/s (2.25 m/s), 0.189 m/s (0.187 m/s), respectively, for MERRA2. The wind components analysis showed that the better performance of ERA5 was attributed to its smaller error in estimating V component than MERRA2. For the wind direction, the two reanalysis datasets did not display distinct differences. Additionally, the misalignment of the wind direction between the reanalysis products and the TTOs was higher for the secondary predominant wind direction (SPWD) than for the predominant wind direction (PWD). Furthermore, we found that the reanalysis U wind had a higher RMSE but a lower RE and Pearson’s r than the V wind, which indicates that the misalignment in the wind direction was mainly associated with the deviation in the U component.

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“…In order to evaluate the results, CAMS O 3 reanalysis data were also obtained (https://ads.atmosphere.copernicus.eu). Some meteorological factors including geopotential heights (Z ), temperature at 2 m (T ), relative humidity (RH) at 1,000 hPa and total cloud covers (TCC), planetary boundary layer height (PBLH), vertical velocity (W ), and wind (U,V ) were obtained from the European Center for Medium-Range Weather Forecasts (ECMWF, ERA5, https://cds.climate.copernicus.eu/) and had a resolution of 0.75° × 0.75° (Jiang et al, 2021;Zhu et al, 2021), and the meteorological fields of ERA5 reanalysis data compare well with MERRA reanalysis data in China (Huang et al, 2022).…”

Section: Data Descriptionmentioning

confidence: 99%

Composite Effects of ENSO and EASM on Summer Ozone Pollution in Two Regions of China

Gong

Chen

et al. 2022

JGR Atmospheres

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With the efforts to reduce anthropogenic emissions, the air quality in China has been gradually improving. In spite of the declining of PM 2.5 in recent years (Gong et al., 2021), O 3 pollution has become more prominent in air pollution, which has attracted widespread attention in China. Surface O 3 has not only impacts on human health (WHO, 2006), but also is harmful to crops due to its impact on the plant photosynthesis rate (Fuhrer & Booker, 2003;Tai et al., 2014). In the past, observational data indicated that summer O 3 concentration in China had increased from 2013 to 2017, especially in eastern China where O 3 was usually higher than that in other regions . As for the sub-regions in eastern China, the data observed by Mount Tai station in Shandong showed that the summer O 3 concentration in this region had been increasing from 2003 to 2015 (Sun et al., 2016). O 3 concentration in Beijing has also been increased significantly since 2006 (Cheng et al., 2019). It

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Evaluation of HRCLDAS and ERA5 Datasets for Near-Surface Wind over Hainan Island and South China Sea

Cited by 27 publications

References 28 publications

Coastal Sea-Ice Break-Up Events in Beringia

Coastal Sea-Ice Break-Up Events in Beringia

Comparison of the Applicability of Two Reanalysis Products in Estimating Tall Tower Wind Based on Multiple Linear Regression and Artificial Neural Network in South China

Composite Effects of ENSO and EASM on Summer Ozone Pollution in Two Regions of China

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