Engineering topics

Yan, Zhongwei

Publications and source records attributed to Yan, Zhongwei.

6 records

DOE OSTI2017

Climatic warming in China during 1901–2015 based on an extended dataset of instrumental temperature records

Monthly mean instrumental surface air temperature (SAT) observations back to the nineteenth century in China are synthesized from different sources via specific quality-control, interpolation, and homogenization. Compared with the first homogenized long-term SAT dataset for China which contained 18 stations mainly located in the middle and eastern part of China, the present dataset includes homogenized monthly SAT series at 32 stations, with an extended coverage especially towards western China. Missing values are interpolated by using observations at nearby stations, including those from neighboring countries. Cross validation shows that the mean bias error (MBE) is generally small and falls between 0.45 °C and –0.35 °C. Multiple homogenization methods and available metadata are applied to assess the consistency of the time series and to adjust inhomogeneity biases. The homogenized annual mean SAT series shows a range of trends between 1.1 °C and 4.0 °C/century in northeastern China, between 0.4 °C and 1.9 °C/century in southeastern China, and between 1.4 °C and 3.7 °C/century in western China to the west of 105 E (from the initial years of the stations to 2015). The unadjusted data include unusually warm records during the 1940s and hence tend to underestimate the warming trends at a number of stations. As a result, the mean SAT series for China based on the climate anomaly method shows a warming trend of 1.56 °C/century during 1901–2015, larger than those based on other currently available datasets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

A new estimate of the China temperature anomaly series and uncertainty assessment in 1900–2006

While global warming during the last century has been well recognized, the magnitude of the climate warming in regions such as China over the past 100 years still has some uncertainty due to limited observations during the early years. Several series of temperature anomalies for the 20th century in China have been independently developed by different groups. The uncertainty arises mainly from the sparse observations before 1950, where statistics are sensitive to the small and potentially biased sample. In this study, BSHADE–MSN (Biased Sentinel Hospitals Areal Disease Estimation and Means of Stratified Nonhomogeneous Surface), a combination of two novel distinct statistical methods that are applicable with different sample situations to a spatial heterogeneous surface, is applied to estimate annual mean temperature anomalies for China. This method takes into account prior knowledge of geographical spatial autocorrelation and nonhomogeneity of target domains, remedies the biased sample, and maximizes an objective function for the best linear unbiased estimation (BLUE) of the regional mean quantity. For the period 1900–1999, the overall trend estimated by BSHADE–MSN is 0.80°C with a 95% confidential interval between 0.41°C and 1.18°C. This is significantly lower than that calculated by Climate Anomaly Method (CAM) and Block Kriging. The new temperature anomaly series for China exhibits slightly warmer conditions for the period before 1950 than existing studies. All the methods applied so far agree well with each other for the period after 1950, when there are sufficient stations across the country for the estimation of temperature anomaly series. Cross validation shows that the new regional mean temperature anomaly series has smaller estimation error variance and higher accuracy than those based on the other methods assessed in this study.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Trend of Surface Air Temperature in Eastern China and Associated Large-Scale Climate Variability over the Last 100 Years

Using the reconstructed continuous and homogenized surface air temperature (SAT) series for 16 cities across eastern China (where the greatest industrial developments in China have taken place) back to the nineteenth century, the authors examine linear trends of SAT. The regional-mean SAT over eastern China shows a warming trend of 1.52°C (100 yr) –1 during 1909–2010. It mainly occurred in the past 4 decades and this agrees well with the variability in another SAT series developed from a much denser station network (over 400 sites) across this part of China since 1951. This study collects population data for 245 sites (from these 400+ locations) and split these into five equally sized groups based on population size. Comparison of these five groups across different durations from 30 to 60 yr in length indicates that differences in population only account for between 9% and 24% of the warming since 1951. To show that a larger urbanization impact is very unlikely, the study additionally determines how much can be explained by some large-scale climate indices. Anomalies of large-scale climate indices such as the tropical Indian Ocean SST and the Siberian atmospheric circulation systems account for at least 80% of the total warming trends.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Instrumental temperature series in eastern and central China back to the nineteenth century

In this study, we bring together different source data sets and use quality control, interpolation, and homogeneity methods to construct a set of homogenized monthly mean surface air temperature (SAT) series for 18 stations in eastern and central China from the late nineteenth century. Missing values are statistically interpolated, and cross validation is used to assess the accuracy of the interpolation approaches. Results show that the errors of interpolation are small, and the interpolated values are statistically acceptable. Multiple homogeneity methods and all available metadata are used to assess the consistency of the time series and then to develop adjustments when necessary. Thirty-three homogeneity breakpoints are detected in the 18 stations, and the time series is adjusted to the latest segment of the data series. The adjusted annual mean SAT generally shows a range of trends of 1.0° to 4.2°C/100 years in northeastern and southeastern China and a range of trends of -0.3° to 1.0°C/100 years in central China near 30°N. Compared to the adjusted time series, the unadjusted time series underestimates the warming trend during the past 100 years. The regional and annual mean SAT over eastern and central China agrees well with estimates from a much denser station network over this region of China since 1951 and shows a warming trend of 1.52°C/100 years during 1909–2010.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

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

The observation minus reanalysis (OMR) method is widely used to investigate the impact of urbanization and land use change on climate. Here we present the OMR trends for the periods of 1979–1998 and 1989–2008 in eastern China, which appear inconsistent for the regions experiencing rapid urbanization during recent decades. Using Ensemble Empirical Mode Decomposition, we extract the secular trend and multidecadal variability (MDV) from the temperature observations at stations and the corresponding reanalysis data for the last century and find that, in general, MDV in the reanalysis data is weaker than that in the station observations. This systematic difference considerably modulates the magnitude of the OMR trends during different periods, leading to inconsistent estimates of the impact of urbanization. After MDV adjustment, the OMR trends for Beijing and Shanghai are consistent for the different periods, about 0.04°C–0.1°C/decade, much smaller than some previous estimates. We caution those using OMR methods to estimate the effect of urbanization and also for those using reanalysis data for a limited period in studies of this kind.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Adjusting inhomogeneous daily temperature variability using wavelet analysis

A wavelet-analysis-based homogenization method (WHM) is developed for detecting and adjusting biases of variability in a daily climate observation series, which are influential in the estimation of climate extremes and relevant trends in the time series. WHM is applied to the Central England daily mean temperature series (CET, 1772–2010) and the daily mean temperature series at Henan station in mountainous western China (HNT, 1960–2008) in order to demonstrate the usefulness of the new technique. The changes of methods for calculating daily mean temperature for CET in 1878 caused significantly reduced daily variability (DV) in the subsequent sub-series of CET. The relocation of the Chinese station in 1981 to a higher mountainous site resulted in not only enhanced DV but also in weather (weekly) time-scale variability (WV) in the subsequent sub-series of HNT. The adjustments based on WHM in the present cases improve the estimates of the long-term trends of climate extremes such as hot days, cold days, heat waves, and cold surges. A few widely applied methods of homogenization such as multiple analysis of series for homogenization (MASH), higher-order moment (HOM), RHtestsV3 with quantile-matching (QM) adjustments and two-phase regression (TPR) are also applied to HNT for comparison. TPR is not aimed at improving the homogeneity of variability in the time series; MASH does not improve daily variability either; HOM improves it in a small way; and with RHtestsV3 with QM adjustments it is considerably improved, but biases remain. In contrast, WHM improves the homogeneity of the short-term variability in the time series, resulting in reasonable assessments of climate extremes and trends in the daily observations.

54 ENVIRONMENTAL SCIENCES↗