机构地区:[1]中国水利水电科学研究院,北京100038 [2]新疆大学干旱生态环境研究所,乌鲁木齐830046 [3]中国气象局国家气象信息中心,北京100081 [4]中国科学院寒区旱区环境与工程研究所冰冻圈科学国家重点实验室,兰州730000 [5]中国科学院新疆生态与地理研究所,乌鲁木齐830011 [6]中国气象局华云信息技术工程有限公司,北京100081
出 处:《生态学报》2017年第3期979-995,共17页Acta Ecologica Sinica
基 金:水利部公益性行业科研专项经费(201301103);国家自然科学基金重点项目(41130531)
摘 要:利用中国气象局国家气象信息中心研发的中国气象局陆面数据同化系统(China Meteorological Administration Land Data Assimilation System,CLDAS)大气近地面强迫资料,驱动美国国家大气研究中心公用陆面模式(Community Land Model,CLM3.5),对中国新疆地区土壤温度时空分布进行逐小时Off-line模拟(模拟时段为2009—2012年);利用国家土壤温度自动站(新疆区域105站点)数据验证CLDAS驱动场强迫下的CLM3.5模式在中国新疆地区3个土壤层(5cm、20cm和80cm)的土壤温度模拟能力。研究发现:在月变化方面,第1层(5cm)土壤温度模拟与实测值差异最大,在每年7月最大差异达5k左右;第2层(20cm)在每年7月达最大差异(3k左右),而第3层(80cm)在每年7月均模拟的很好。造成这种现象的原因可能因为新疆地区7月前后浅层土壤温度变化剧烈,温度白天最高可达300K以上,昼夜温差大,导致模式不能很好抓住浅层土壤温度的变化趋势。研究还发现,在80cm土壤深度,模式在1月、12月的模拟结果均较前两层差。在日变化方面,研究发现:较浅的两层(5cm和20cm)土壤温度模拟值在夏季和秋季均较差。与月变化模拟结果类似的是,80cm土壤层日变化在1、12月模拟较差,然而在其他时段却模拟的很好。在小时变化方面,分析发现:第1层土壤(5cm)模拟结果在每年的1—4月及9—11月的全天(即24 h),模式也会有不同的偏差:其中,在03UTC—21UTC之间主要表现为模式结果比观测结果偏高,而在日内21UTC—00UTC主要表现为模拟结果偏小。在每年的5—8月,全天模拟值都偏小,其中在09UTC达当日最大值。而距离第2层(20cm)处的土壤温度模拟值在大部分月份都偏差较小(-1K至1k之间),并在日内12UTC偏差达到当日最大值。研究发现,在土壤20cm处,模式模拟的最大值较观测值提前,而第3层(80cm)的土壤温度基本不受日内变化影响,表现较为平稳。造成这种影响的原因可能是因为This study modeled the spatial and temporal distribution of soil temperatures in the Xinjiang region of China, using atmospheric surface forcing data in the China Meteorological Administration Land Data Assimilation System ( CLDAS, NMIC of China Meteorological Administration ) to drive the Community Land Model ( CLM3.5, National Center of Atmospheric Research USA) for hourly off-line simulations (from 2009 to 2012 ). To verify the CLM3.5 simulated soil temperatures, data from national automatic soil-temperature stations (105 in the Xinjiang region) were used at three soil layers (5 cm, 20 cm, and 80 cm ). For monthly variation, simulated top layer (5cm) soil temperatures differed substantially from measured values, with the largest difference (±5℃ ) reaching the maximum in July each year. The difference (±3℃ ) between modeled and observed soil temperatures at the second layer (20 cm) reached the maximum in July for all years, whereas for the third layer ( 80 cm) , simulated annual July soil temperatures were in accordance with the observed values. The large discrepancies in July soil temperatures in the top surface layers can be explained by the drastic surface temperature changes in the Xinjiang region during that month. With day-time temperatures that can reach above 30℃, combined with large diurnal temperature differences, it becomes very difficult to accurately capture surface temperature variation by using the model. In contrast, in January and December, the 80 cm soil depth simulations were less accurate than the results of simulations at the first two soil layers. Furthermore, simulated values of soil temperature at the top two layers (5 cm and 20 cm) did not fit well with observed values for the summer and autumn. However, similar to monthly variation, the daily variation in modeled soil temperature at 80 cm showed a bad fit with observed data in January and December, whereas the fit was good in other periods. For hourly variation at 5 cm soil depth, the
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