On “observation minus reanalysis” method: A view from multidecadal variability

Wang, Jun; Zeng, Yan; Jones, Phil; Xia, Jiangjiang

doi:10.1002/jgrd.50574

Cited by 32 publications

(23 citation statements)

References 37 publications

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“…This is consistent with the results based on the global observations analyzed above (Table ), but the magnitude is weaker in the reanalysis. This smaller local warming relative to the global mean in the reanalysis might be associated with the models' characteristics (or biases) in physics such as land surface and convection and SST and sea ice boundary conditions (Hirahara et al, ), as well as the underestimated multidecadal variability as mentioned above (Gao et al, ; Wang et al, ). Additional analyses using other model experiments are required to explore the model‐dependence issue.…”

Section: Resultsmentioning

confidence: 99%

Long‐Term Warming Trends in Korea and Contribution of Urbanization: An Updated Assessment

et al. 2017

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This study conducted an updated analysis of the long‐term temperature trends over South Korea and reassessed the contribution of the urbanization effect to the local warming trends. Linear trends were analyzed for three different periods over South Korea in order to consider possible inhomogeneity due to changes in the number of available stations: recent 103 years (1912–2014), 61 years (1954–2014), and 42 years (1973–2014). The local temperature has increased by 1.90°C, 1.35°C, and 0.99°C during the three periods, respectively, which are found 1.4–2.6 times larger than the global land mean trends. The countries located in the northern middle and high latitudes exhibit similar warming trends (about 1.5 times stronger than the global mean), suggesting a weak influence of urbanization on the local warming over South Korea. Urbanization contribution is assessed using two methods. First, results from “city minus rural” methods showed that 30–45% of the local warming trends during recent four decades are likely due to the urbanization effect, depending on station classification methods and analysis periods. Results from an “observation minus reanalysis” method using the Twentieth Century Reanalysis (20CR) data sets (v2 and v2c) indicated about 25–30% contribution of the urbanization effect to the local warming trend during the recent six decades. However, the urbanization contribution was estimated as low as 3–11% when considering the century‐long period. Our results confirm large uncertainties in the estimation of urbanization contribution when using shorter‐term periods and suggest that the urbanization contribution to the century‐long warming trends could be much lower.

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Section: Resultsmentioning

confidence: 99%

Long‐Term Warming Trends in Korea and Contribution of Urbanization: An Updated Assessment

et al. 2017

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“…Many of the studies that have analyzed this subject have used the difference in the reanalysis and the observed series under what has been widely termed an “observation‐minus‐reanalysis” (OMR) approach [ Kalnay and Cai , ; Zhou et al ., ; Kalnay et al ., ; Yang et al ., ], although Wang et al . [] have recently shown that this approach, when applied to relatively short data series, may identify significant differences between observations and reanalysis data that are attributable to a differential in multidecadal variability between the data sets rather than land use.…”

Section: Introductionmentioning

confidence: 99%

How well does the ERA‐Interim reanalysis replicate trends in extremes of surface temperature across Europe?

Cornes

Jones

2013

JGR Atmospheres

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[1] Trends in extremes of daily maximum and minimum temperature across Europe derived from the European Centre for Medium-Range Weather Forecasts ERA-Interim reanalysis are compared against observed data. The period 1980-2011 is considered and both station series and the gridded E-OBS data are used to determine the success of the reanalysis, with indices of the numbers of days above or respectively below the 90th and 10th percentiles of daily maximum and minimum temperature used as metrics. It is shown in this paper that the ERA-Interim reanalysis data are generally very good at replicating both the seasonally and spatially varying trends in the indices across Europe. At the station level, the reanalysis data are also able to depict the observed trends remarkably well. However, the success of the reanalysis data depends on the season and the particular index considered. The reanalysis is least successful in replicating trends in the number of days exceeding the 90th percentile of maximum temperature, particularly during the summer season. The success of the reanalysis is also somewhat dependent on the time step of the reanalysis data used. Daily maximum and minimum temperatures calculated from the 3-hourly time step reanalysis data tend to be more reliable than those derived from the 12-hourly data.Citation: Cornes, R. C., and P. D. Jones (2013), How well does the ERA-Interim reanalysis replicate trends in extremes of surface temperature across Europe?,

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“…In addition to a comparison of urban and rural stations, some studies also used the OMR method to assess the urbanization impact on regional NSWS changes in China (Li et al , 2019. Given that reanalysis products poorly represent many characteristics of historical NSWS changes in many regions (McVicar et al 2008, Pryor et al 2009, Chen et al 2013 as well as existing problems in the rationale of the OMR method (Trenberth 2004, Wang et al 2013, it is advisable to view the OMR-estimated urbanization contribution to the observed regional NSWS trend in urban areas with caution. To quantify uncertainties associated with reanalysis and assess the reliability of the OMR method in the estimation of the urbanization influence on urban NSWS change, we carried out a detailed comparison of observed NSWS trends with those derived from multiple reanalysis products.…”

Section: Comparison Of the Observed And Reanalysis Wind Trendsmentioning

confidence: 99%

An analysis of the urbanization contribution to observed terrestrial stilling in the Beijing–Tianjin–Hebei region of China

Wang

Feng

Zeng

et al. 2020

Environ. Res. Lett.

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Decreases in terrestrial near-surface wind speed (NSWS) were documented in many regions over the past decades. Various drivers have been proposed for this terrestrial stilling, such as weakening of ocean-land pressure gradients related to climate change and increased surface roughness linked to vegetation growth; but none have been robustly established as the cause. A plausible reason for this quandary is that the local impact of urbanization on NSWS has been overlooked. Here, we used homogenized NSWS records from in situ weather stations and a satellite-based dynamic urban-rural classification scheme to quantitatively assess the contribution of urbanization to observed terrestrial stilling during 1980-2016 over the Beijing-Tianjin-Hebei region of China. Results suggested that urbanization contributed approximately 8% to the observed decrease in the regional NSWS in urban areas, implying that urbanization played a minor role in terrestrial stilling, even in this rapidly developing region. The largest NSWS changes related to urbanization occurred in winter, followed by spring, autumn, and summer. Urbanization reduced the days with relatively strong winds but increased the days with light and gentle winds. We found that except for the Japanese 55 year reanalysis (JRA-55) dataset, none of the common reanalysis products reproduced the observed NSWS trends in urban or rural areas. However, this could be because of JRA-55's intrinsic negative bias in NSWS trends over land. Thus, regional terrestrial NSWS trends derived from reanalysis products deserve careful examination.

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On “observation minus reanalysis” method: A view from multidecadal variability

Cited by 32 publications

References 37 publications

Long‐Term Warming Trends in Korea and Contribution of Urbanization: An Updated Assessment

Long‐Term Warming Trends in Korea and Contribution of Urbanization: An Updated Assessment

How well does the ERA‐Interim reanalysis replicate trends in extremes of surface temperature across Europe?

An analysis of the urbanization contribution to observed terrestrial stilling in the Beijing–Tianjin–Hebei region of China

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