Land surface temperature(LST) is one of the most important factors in the land-atmosphere interaction process. Raw measured LSTs may contain biases due to instrument replacement, changes in recording procedures, and other non-climatic factors. This study attempts to reduce the above biases in raw daily measurements and achieves a homogenized daily LST dataset over China using 2360 stations from 1960 through 2017. The high-quality land surface air temperature(LSAT)dataset is used to correct the LST warming biases especially evident during cold months in regions north of 40°N due to the replacement of observation instruments around 2004. Subsequently, the Multiple Analysis of Series for Homogenization(MASH) method is adopted to detect and then adjust the daily observed LST records. In total, 3.68 × 103 effective breakpoints in 1.65 × 106 monthly records(about 20%) are detected. A large number of these effective breakpoints are located over large parts of the Sichuan Basin and southern China. After the MASH procedure, LSTs at more than 80% of the breakpoints are adjusted within +/– 0.5°C, and of the remaining breakpoints, only 10% are adjusted over 1.5°C.Compared to the raw LST dataset over the whole domain, the homogenization significantly reduces the mean LST magnitude and its interannual variability as well as its linear trend at most stations. Finally, we perform preliminary analysis upon the homogenized LST and find that the annual mean LST averaged across China shows a significant warming trend [0.22°C(10 yr)–1]. The homogenized LST dataset can be further adapted for a variety of applications(e.g.,model evaluation and extreme event characterization). 相似文献
To achieve accurate evaluation of evapotranspiration of reference crops (ET0) in Jiangxi, China, in the absence of systematic climatological data, with reference to the FAO-56 Penman–Monteith (P-M) equation, the Priestley-Taylor (P–T) method, the Makkink method, the Hargreaves-Samani (H–S) method, the Irmak-Allen (I-A) method, the Penman1948 (48PM) method, the Penman-Van Bavel (PVB) method, the Baier-Robertson (B-R) method, the improved Baier-Robertson (M-B-R) method, the Schendel (Sch) method, the Turc method, the Jensen-Haise (J-H) method, and the Brutsaert-Stricker (B-S) method were used to evaluate the daily climatological data collected by 26 weather stations in Jiangxi, China, and 17 weather stations in adjacent provinces. The results were compared with each other and parameter rate determination was conducted. The results indicated that the Turc method exhibited optimized applicability before parameter rate determination and the average root mean square error (RMSE) and the average normalized root mean square error (NRMSE) by this method were 0.39 mm/d and 0.157 mm, respectively. However, parameter rate determination led to negligible improvement in accuracy for this method. The Turc method could be directly applied in Jiangxi (except Nanchang). For special distribution of error after parameter rate determination, all methods exhibited significant errors in Northern Jiangxi. Herein, the 48PM method and the B-S method showed good applicability after parameter rate determination and RMSE and NRMSE of data by these methods ranged in 0.06 ~ 0.34 mm/d and 0.08 ~ 0.27, 8 ~ 27%, respectively, and their d-indices were close to 1. The annual over-estimations in weather stations in Jiangxi were below 30 mm. In the absence of data about relative humidity and wind speed, the P–T method was an appropriate simplified method for Jiangxi. In this case, α was slightly lower than the default value (1.05 ~ 1.18), RMSE was within 0.21 ~ 0.66 mm/d, and NRMSE was within 0.08 ~ 0.308 ~ 30%. Accuracy of RMSE, d-index, and NRMSE of data by the P–T method, the I-A method, and the PVB method was consistent with all stations, while that by the Mak method was slightly lower, which could be attributed to severe over-estimation in July and August. RMSE of the H–S method, the B-R method, the M-B-R method, the J-H method, and the Sch method were above 0.75 mm/d and these methods were not suitable for accurate evaluation of ET0 in Jiangxi, China. The annual ET0 was calculated by various methods (except the 48PM method and the B-S method) exhibited significant variation around 2003. This may be attributed to significant changes in certain meteorological factors over recent years.
In the first half of winter 2020/21,China has experienced an extremely cold period across both northern and southern regions,with record-breaking low temperatures set in many stations of China.Meanwhile,a moderate La Ni?a event which exceeded both oceanic and atmospheric thresholds began in August 2020 and in a few months developed into its mature phase,just prior to the 2020/21 winter.In this report,the mid?high-latitude large-scale atmospheric circulation anomalies in the Northern Hemisphere,which were forced by the negative phase of Arctic Oscillation,a strengthened Siberian High,an intensified Ural High and a deepened East Asian Trough,are considered to be the direct reason for the frequent cold surges in winter 2020/21.At the same time,the synergistic effect of the warm Arctic and the cold tropical Pacific(La Ni?a)provided an indispensable background,at a hemispheric scale,to intensify the atmospheric circulation anomalies in middle-to-high latitudes.In the end,a most recent La Ni?a prediction is provided and the on-coming evolution of climate is discussed for the remaining part of the 2020/21 winter for the purpose of future decision-making and early warning. 相似文献
