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Cao, Lijuan

Publications and source records attributed to Cao, Lijuan.

6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

New Record Ocean Temperatures and Related Climate Indicators in 2023

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities. In 2023, the sea surface temperature (SST) and upper 2000 m ocean heat content (OHC) reached record highs. The 0–2000 m OHC in 2023 exceeded that of 2022 by 15 ± 10 ZJ (1 Zetta Joules = 10 21 Joules) (updated IAP/CAS data); 9 ± 5 ZJ (NCEI/NOAA data). The Tropical Atlantic Ocean, the Mediterranean Sea, and southern oceans recorded their highest OHC observed since the 1950s. Associated with the onset of a strong El Niño, the global SST reached its record high in 2023 with an annual mean of ~0.23°C higher than 2022 and an astounding > 0.3°C above 2022 values for the second half of 2023. The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

54 ENVIRONMENTAL SCIENCES↗
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

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

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↗