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Preserving Continuity of Long-Term Daily Maximum and Minimum Temperature Observations with Automation of Reference Climate Stations using Overlapping Data and Meteorological Conditions

机译：使用重叠数据和气象条件，保持与辅助气候站的自动化的长期日最大和最小温度观测的连续性

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Ewa J. Milewska; Lucie A. Vincent;
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年度 2016
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1. Preserving Continuity of Long-Term Daily Maximum and Minimum Temperature Observations with Automation of Reference Climate Stations using Overlapping Data and Meteorological Conditions [J] . Milewska Ewa J., Vincent Lucie A. Atmosphere-ocean . 2016,第1期

机译：使用重叠数据和气象条件通过参考气候站的自动化来保持长期每日最高和最低温度观测的连续性
2. Regional climate model simulations of daily maximum and minimum near-surface temperatures across Europe compared with observed station data 1961-1990 [J] . Anders Moberg, Philip D. Jones Climate dynamics . 2004,第7a8期

机译：与1961-1990年观测站的数据相比，全欧洲每日最高和最低近地表温度的区域气候模型模拟
3. Spatial Interpolation of Daily Maximum and Minimum Air Temperature Based on Meteorological Model Analyses and Independent Observations [J] . ARTHUR T. DEGAETANO, BRIAN N. BELCHER Journal of Applied Meteorology and Climatology . 2007,第11期

机译：基于气象模型分析和独立观测的每日最高和最低气温的空间插值
4. Using daily minimum and dew point temperatures to assess weather station sites for reference conditions [C] . Xinhua Jia, Edward C. Martin Annual International Meeting of the American Society of Agricultural Engineers . 2001

机译：使用日最小和露点温度来评估气象站网站参考条件
5. Temperature and humidity data correction for calculating reference evapotranspiration at nonreference weather stations [D] . Temesgen, Bekele 1996

机译：温度和湿度数据校正，以计算非参考气象站的参考蒸散量
6. Determination of optimum daily maximum temperature using climate data [O] . Yasushi Honda, Michinori Kabuto, Masaji Ono, 2007

机译：使用气候数据确定最佳每日最高温度
7. Simulating air temperature in an urban street canyon in all weather conditions using measured data at a reference meteorological station [O] . Erell, E., Williamson, T. 2006

机译：使用参考气象站的测量数据，在所有天气条件下模拟城市街道峡谷的空气温度

Preserving Continuity of Long-Term Daily Maximum and Minimum Temperature Observations with Automation of Reference Climate Stations using Overlapping Data and Meteorological Conditions

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