设为首页
加入收藏
Verification and Correction on ASCAT Wind Velocities Within the Offshore East China Sea
-
摘要: 基于2010—2014年ASCAT反演风速、华东沿海14个浮标站和浙江沿海249个自动气象站资料，对华东沿海ASCAT反演风速进行检验和订正。研究表明：站点ASCAT风速误差不仅与离岸距离相关，而且与站点周围地形有关，误差较大的5个浮标站均位于舟山群岛附近海区，平均偏大4.79 m·s-1，其他海区浮标站的ASCAT反演风速平均偏差仅为0.46 m·s-1。ASCAT反演风速与浮标站风速的线性回归可有效减小反演风速误差，订正后误差大幅减小，误差越大的站点订正效果越好。相距160 km内的浮标站点间风速误差呈正相关，且站点间距越小，误差正相关越明显。考虑带影响半径的反距离权重，采用邻站方程订正法和邻站误差订正法分别对华东沿海ASCAT反演风速进行订正，均能明显减小平均偏差和均方根误差，两种方法订正效果接近，即两种方法均有较好的订正效果，可用于实际业务。Abstract: Based on ASCAT wind velocities, observations of 14 meteorological buoys in the offshore East China Sea, and 249 automatic weather stations (AWS) along coastal Zhejiang Province from 2010 to 2014, verification and correction methods are implemented on ASCAT wind velocities and buoy observations. The analysis indicates ASCAT wind velocities are overestimated for all the 14 buoys in comparison with observations, but only 5 of them, all located off Zhoushan Archipelago, hold deviations greater than 2 m·s-1 with mean bias of 4.79 m·s-1, and the mean bias for the rest buoys is only 0.46 m·s-1. Results also imply ASCAT wind velocities are not only related to distances away from the coastal line, but also to the local terrains. Regression methods are applied to investigate relations between ASCAT wind velocities and observations at all the buoys with regression and independent test samples ratio of 70% to 30%. It shows that linear regression can help reduce ASCAT wind deviations at all the buoys, decreasing the mean bias from 2.02 m·s-1 down to 0.14 m·s-1, especially at those stations with big errors. The relation of ASCAT deviations among buoys is also studied, indicating there is a positive correlation between the ASCAT wind errors and distances for buoys within 160 km, the closer the distances between buoys are, the bigger the coefficients are, with the logarithmic fitting taking advantages of the linear fitting. Two methods, namely regression and deviation, are carried out to make corrections on ASCAT wind velocities, with effective radius taken into account while doing inverse distance weighing interpolations. Results show the mean deviations and root mean square errors decrease obviously after revision, two methods reduce the mean biases by 1.86 m·s-1 (67.9%) and 1.74 m·s-1 (64.2%), and reduce the root mean square errors by 1.19 m·s-1 (29.2%) and 0.89 m·s-1 (29.6%), repectively. Case study on the regression method is carried out with corrected ASCAT wind velocities compared with the 10 m wind fields at lead time 0 h of European Centre for Medium-Range Weather Forecasts (ECMWF) fine model (resolution of 0.25°×0.25°). It shows that two methods are proved positive and can help decrease mean wind deviation. Further analysis shows that the deviation method gets the least mean deviation when AWS observations are taken into account, implying that the enhancement of station resolution can help increase the correction result.
-
Key words:
- ASCAT;
- buoys;
- wind velocity corrections
-
图 1 2010年9月—2014年9月站点间ASCAT风速误差相关系数与距离的关系
Fig. 1 The distribution of coefficients of ASCAT velocity errors to station distances from Sep 2010 to Sep 2014
图 2 2014年1月18日08：00 ASCAT风速订正前后与ECMWF风速的偏差 (单位：m·s-1；黑色圆点为浮标站) (a) 订正前，(b) 邻站方程订正法，(c) 邻站误差订正法，(d) 考虑自动气象站资料的邻站误差订正法
Fig. 2 ASCAT wind deviations relative to ECMWF at 0800 BT 18 Jan 2014(unit:m·s-1; dark dots:locations of buoys) (a) without corrections, (b) corrected by regression, (c) corrected by considering errors, (d) corrected by considering errors with AWS data
表 1 浮标站点地理信息
Table 1 Geographical information of buoys
站号 站名 所属省市 位置 离岸距离/km A5999 口外船标站 上海 31.10°N，122.53°E 62 A5904 南漕船标站 上海 30.99°N，122.53°E 60 A5901 东海浮标站 上海 31.00°N，124.50°E 248 A5906 海礁浮标站 上海 30.69°N，123.20°E 127 A5903 洋山浮标站 上海 30.63°N，122.01°E 30 A5902 航道浮标站 上海 30.55°N，122.37°E 59 A5905 黄泽洋船标站 上海 30.50°N，122.53°E 75 58573 舟山浮标站 浙江 29.75°N，122.75°E 61 58599 平湖油田站 上海 29.07°N，124.91°E 283 58696 春晓油田站 上海 28.51°N，125.01°E 305 58768 温州浮标站 浙江 27.55°N，121.40°E 64 58767 宁德浮标站 福建 26.99°N，121.00°E 53 58951 福州浮标站 福建 25.50°N，120.30°E 63 59334 厦门浮标站 福建 23.63°N，118.20°E 53 
下载: 导出CSV
表 2 浮标站ASCAT风速检验
Table 2 Verification of ASCAT velocities at buoys
站号 平均偏差/(m·s-1) 均方根误差/(m·s-1) 样本量 A5999 2.82 3.46 409 A5904 2.40 3.15 313 A5901 0.55 1.93 249 A5906 0.27 1.09 258 A5903 10.03 11.23 179 A5902 4.92 5.81 386 A5905 3.78 4.39 184 58573 1.08 1.79 1118 58599 0.50 2.64 268 58696 1.11 3.02 289 58768 -0.03 1.25 1000 58767 0.17 2.18 120 58951 0.23 1.23 142 59334 0.25 1.43 143
下载: 导出CSV
表 3 回归订正前后ASCAT风速独立检验样本误差对比
Table 3 Error comparison of ASCAT velocities before and after regressions
站号 样本量 平均偏差/(m·s-1) 均方根误差/(m·s-1) 回归 检验 订正前 订正后 订正前 订正后 A5999 300 109 2.61 -0.26 3.23 1.92 A5904 220 93 1.82 -0.79 2.67 2.12 A5901 180 69 0.86 0.39 2.08 1.92 A5906 180 78 -0.01 -0.31 0.97 1.04 A5903 120 59 8.95 -0.59 10.07 2.61 A5902 280 106 4.20 -0.64 5.09 2.67 A5905 130 54 3.90 0.77 4.40 2.00 58573 800 318 1.19 0.16 1.99 1.60 58599 190 78 1.49 1.25 3.39 3.41 58696 200 89 2.21 1.54 3.74 3.44 58768 700 300 0.04 0.08 1.38 1.38 58767 80 40 0.44 0.42 3.40 3.39 58951 100 42 0.55 0.42 1.92 1.90 59334 100 43 0.00 -0.42 1.64 1.70
下载: 导出CSV
表 4 不同订正方法ASCAT风速订正误差对比
Table 4 Comparison of two methods on ASCAT velocity corrections
订正方法 站号 样本量 平均偏差/(m·s-1) 均方根误差/(m·s-1) 订正前 订正后 订正前 订正后 邻站方程订正法 A5999 409 2.82 0.64 3.46 2.09 A5904 313 2.40 -0.13 3.15 2.06 A5901 249 0.55 0.49 1.93 1.91 A5906 258 0.27 -0.98 1.09 1.44 A5903 179 10.03 6.25 11.23 7.46 A5902 386 4.92 1.57 5.81 3.24 A5905 184 3.78 0.18 4.39 2.03 58573 1118 1.08 0.14 1.79 1.46 58599 268 0.50 -0.17 2.64 2.61 58696 289 1.11 0.81 3.02 2.94 邻站误差订正法 A5999 130 2.74 0.94 3.41 1.96 A5904 115 2.01 -0.31 2.97 1.52 A5901 51 1.07 0.94 2.21 2.14 A5906 236 0.33 -1.30 1.08 1.79 A5903 167 10.62 7.98 11.58 9.02 A5902 262 3.77 0.09 4.65 2.50 A5905 184 3.78 0.72 4.39 2.32 58573 268 1.19 -0.01 1.99 1.51 58599 237 0.58 -0.03 2.68 1.84 58696 238 1.03 0.67 2.92 2.06
下载: 导出CSV
-
[1] 方翔, 咸迪, 李小龙, 等.QuikSCAT洋面风资料及其在热带气旋分析中的应用.气象, 2007, 33(3):33-39. doi: 10.7519/j.issn.1000-0526.2007.03.005 [2] 鲁小琴, 雷小途.用地理信息系统改进热带气旋的客观定位精度.应用气象学报, 2005, 16(6):841-848. doi: 10.11898/1001-7313.20050610 [3] 刘宇迪, 任景鹏, 周鑫.散射计风场的三维变分对海雾数值模拟的影响.应用气象学报, 2011, 22(4):472-481. doi: 10.11898/1001-7313.20110410 [4] Osamu Isoguchi, Hiroshi Kawamura.Coastal wind jets flowing into Tsushima and effect on wind-wave development.J Atmos Sci, 2007, 64(1):564-578. [5] Bi L, Jung J A, Morgan M C, et al.Assessment of assimilating ASCATsurface wind retrievals in the NCEP Global Data Assimilation System.Mon Wea Rev, 2011, 139(11):3405-3421. doi: 10.1175/2011MWR3391.1 [6] 沈春, 项杰, 蒋国荣, 等.中国近海ASCAT风场反演结果验证分析.海洋预报, 2013, 30(4):27-32. doi: 10.11737/j.issn.1003-0239.2013.04.004 [7] 张增海, 曹越男, 刘涛, 等.ASCAT散射计风场在我国近海的初步检验与应用.气象, 2014, 40(4):473-481. doi: 10.7519/j.issn.1000-0526.2014.04.010 [8] 高留喜, 朱蓉, 常蕊.QuikSCAT和ASCAT卫星反演风场在中国南海北部的适用性研究.气象, 2014, 40(10):1240-1247. doi: 10.7519/j.issn.1000-0526.2014.10.008 [9] 谢小萍, 魏建苏, 黄亮.ASCAT近岸风场产品与近岸浮标观测风场对比.应用气象学报, 2014, 25(4):445-453. doi: 10.11898/1001-7313.20140407 [10] 杨晓君, 张增海.ASCAT洋面风资料在中国北方海域的真实性检验.海洋预报, 2014, 31(5):8-12. doi: 10.11737/j.issn.1003-0239.2014.05.002 [11] 安大伟, 谷松岩, 杨忠东, 等.散射计海面非气旋风场块状模糊去除方法.应用气象学报, 2012, 23(4):485-492. doi: 10.11898/1001-7313.20120412 [12] 刘小宁, 鞠晓慧, 范邵华.空间回归检验方法在气象资料质量检验中的应用.应用气象学报, 2006, 17(1):37-42. doi: 10.11898/1001-7313.20060106 [13] 尹嫦姣, 江志红, 吴息, 等.空间差值检验方法在地面气象资料质量控制中的应用.气候与环境研究, 2010, 15(3):229-236. http://www.cnki.com.cn/Article/CJFDTOTAL-QHYH201003003.htm [14] 魏娜, 孙娴, 姜创业, 等.台站迁移对陕西省气温资料均一性的影响及其偏差订正.气象, 2012, 38(12):1532-1537. http://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201212012.htm [15] 何志军, 封秀燕, 何利德, 等.气象观测资料的四方位空间一致性检验.气象, 2010, 36(5):118-122. doi: 10.7519/j.issn.1000-0526.2010.05.018 [16] 温华洋, 华连生, 金素文, 等.基于空间一致性的双套站数据选取方法探索.气象, 2013, 39(8):1069-1075. doi: 10.7519/j.issn.1000-0526.2013.08.014 [17] 徐晶晶, 胡非, 肖子牛, 等.风能模式预报的相似误差订正.应用气象学报, 2013, 24(6):731-740. doi: 10.11898/1001-7313.20130610 -
图(2) / 表(4)
计量
- 摘要浏览量: 2778
- HTML全文浏览量: 1170
- PDF下载量: 968
- 被引次数: 0
