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往返式探空观测资料的质量控制及不确定性分析

王丹 王金成 田伟红 郭启云

王丹, 王金成, 田伟红, 等. 2020. 往返式探空观测资料的质量控制及不确定性分析[J]. 大气科学, 44(4): 865−884 doi:  10.3878/j.issn.1006-9895.1912.19203
引用本文: 王丹, 王金成, 田伟红, 等. 2020. 往返式探空观测资料的质量控制及不确定性分析[J]. 大气科学, 44(4): 865−884 doi:  10.3878/j.issn.1006-9895.1912.19203
WANG Dan, WANG Jincheng, TIAN Weihong, et al. 2020. Quality Control and Uncertainty Analysis of Return Radiosonde Data [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 865−884 doi:  10.3878/j.issn.1006-9895.1912.19203
Citation: WANG Dan, WANG Jincheng, TIAN Weihong, et al. 2020. Quality Control and Uncertainty Analysis of Return Radiosonde Data [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 865−884 doi:  10.3878/j.issn.1006-9895.1912.19203

往返式探空观测资料的质量控制及不确定性分析

doi: 10.3878/j.issn.1006-9895.1912.19203
基金项目: 国家重点研究发展计划项目2018YFC1506205、2017YFC1502102,中国气象局数值预报(GRAPES)发展专项GRAPES-FZZX-2019
详细信息
    作者简介:

    王丹,女,1987年出生,硕士,主要从事观测资料质量控制和同化应用研究。E-mail: wangd@cma.gov.cn

    通讯作者:

    王金成,E-mail: wangjc@cma.gov.cn

  • 中图分类号: P412

Quality Control and Uncertainty Analysis of Return Radiosonde Data

Funds: National Key Reasearch and Development Program of China (Grants 2018YFC1506205, 2017YFC1502102), China Meteorological Administration Special Numerical Weather Prediction (GRAPES) Development Fund (Grant GRAPES-FZZX-2019)
  • 摘要: 为了推动新型探测资料在数值预报模式中的应用,本文进行了往返式探空资料同化应用前重要的基础性研究工作。基于国内首次往返式探空观测资料,首先建立了面向业务化应用的往返式探空资料质量控制方案,通过对比和分析质量控制前后观测样本的统计特征,论证了质量控制方案的合理性,质量控制后探测要素抽样分布更为合理,要素间一致性得到提高。进而以数值天气预报高时间分辨率的模式预报场和同站址业务常规探空观测资料为参考,分析质量控制后资料的不确定性,结果表明往返探空探测精度达到了世界气象组织WMO(World Meteorological Center)规定的突破目标,部分探测要素甚至实现了理想目标,探测资料具有可用性。最后结合数值模式背景场探讨往返探空资料的可同化性,研究表明往返探空的风场观测和夜间温度观测满足变分同化系统的高斯、无偏假定,可直接同化;气压、湿度和日间温度观测在资料同化前需要开展偏差订正工作,从而更有效的发挥资料价值。本文的研究工作为今后往返探空资料在模式中的同化应用奠定了基础。
  • 图  1  (a)往返探空试验区布局及(b)以安庆站2018年6月11日12时(协调世界时,下同)为例的观测轨迹示意图。图a中实心黑点代表往返探空气球施放站点,空心三角代表GPS接收机布设点

    Figure  1.  (a) Return radiosonde network distribution and (b) an example of observation trajectory for return radiosonde at Anqing station at 1200 UTC on 11 June 2018. In Fig. 1a, the black dots represent return radiosonde launch stations and triangles represent GPS (Global Positioning System) receiver locations

    图  2  往返探空质量控制流程图,图中QC_FLAGS代表质量控制标识

    Figure  2.  Quality control flow of return radiosonde, QC_FLAGS represents quality control flag

    图  3  往返探空观测资料集的(a)上升段、(b)平漂段、(c)下降段风切变阈值随时间的演变。蓝色线为标准差均值廓线,红色线为最小二乘法拟合廓线,绿色线为SW判断阈值。往返探空观测资料集的数据采集时间为2018年6月10日至7月10日,数据采集地点为安庆、长沙、赣州、南昌、武汉、宜昌6个观测站,下同

    Figure  3.  Time evolutions of wind shear threshold in (a) ascending stage, (b) drifting stage, and (c) descending stage of return radiosonde data set. Blue lines represent the mean profiles of standard deviation, red lines represent the least square fitting profiles, and green lines represent the wind shear (SW) thresholds. Return radiosonde data set is derived from six observation stations (Anqing, Changsha, Ganzhou, Nanchang, Wuhan, Yichang) from 10 June to 10 July 2018, the same below

    图  4  (a)以武汉站2018年7月4日00时为例的温度僵值示例、(c)以长沙站2018年6月15日00时为例的湿度僵值示例、(e)以宜昌站2018年6月18日00时为例的纬向风僵值示例及其(b、d、f)对应拟合斜率随时间的演变

    Figure  4.  Time evolutions of (a) an example of rigid temperature at Wuhan station at 0000 UTC 4 July 2018, (c) an example of rigid relative humidity at Changsha station at 0000 UTC 15 June 2018, (e) an example of rigid zonal wind at Yichang station at 0000 UTC 18 June 2018, and (b, d, f) corresponding fitting slopes in examples of rigid profiles

    图  5  (a–c)以赣州站2018年6月11日00时为例的不一致性温度观测、(d–f)以宜昌站2018年6月11日00时为例的不一致性温度观测、(g–i)以安庆站2018年6月22日00时为例的不一致性相对湿度观测随时间的演变。左列为观测值、中列为观测变量的时间变率a、右列为离群距离Z。图中蓝色×代表可疑观测,红色实线代表离群距离阈值Zqc

    Figure  5.  Time evolutions of (a–c) an example of inconsistent temperature of Ganzhou station at 0000 UTC 11 June 2018, (d–f) an example of inconsistent temperature of Yichang station at 0000 UTC 11 June 2018, (g–i) an example of inconsistent relative humidity (RH) of Anqing station at 0000 UTC 22 June 2018. Left column indicates observations, middle column indicates corresponding time variability a, and right column indicates outlier distance score Z. The blue crosses represent suspicious observations, red lines denote the threshold (Zqc) of outlier distance score

    图  6  往返探空观测资料集(a)上升段、(b)平漂段、(c)下降段探空气球上升速度随时间的演变。红色点代表错误观测,蓝色点代表可疑观测

    Figure  6.  Time evolutions of ascending speed of sounding balloon in the (a) ascending stage, (b) drifting stage, and (c) descending stage of return radiosonde data set. Red dots represent error observations and blue dots represent suspicious observations

    图  7  以南昌站2018年7月3日00时为例的异常气压的(a)原始观测、(b)经过气压离群值检查后观测及(c)增加静力学检查后观测随时间的演变。黑色星代表气压观测值,红色线代表反算气压值

    Figure  7.  Time evolutions of abnormal pressure at Nanchang station from (a) raw observations, (b) observations after outlier check, and (c) observations after hydrostatic check at 0000 UTC 3 July 2018. Black stars represent raw pressure observations and red lines represent the inverse calculated pressure value

    图  8  往返探空观测资料集的质量控制前(第一、三行)和质量控制后(第二、四行)的(a、d)纬向风、(b、e)经向风、(c、f)温度、(g、j)气压、(h、k)位势高度、(i、l)相对湿度的观测值在不同百分位的抽样随时间的演变

    Figure  8.  Time evolutions of observation samplings at different percentiles of (a, d) zonal wind, (b, e) meridinal wind, (c, f) temperature, (g, j) pressure, (h, k) geopotential height, and (i, l) RH of return radiosonde for raw data (the first and third panels) and data after quality control (second and fourth panels) from return radiosonde data set

    图  9  往返探空观测资料集的上升段(左)、平漂段(中)、下降段(右)质量控制前(黑色线)和质量控制后(红色线)的(a、b、c)纬向风、(d、e、f)温度、(g、h、i)气压、(j、k、l)位势高度和(m、n、o)湿度的时间变率随时间的演变

    Figure  9.  Time evolutions of time-variability of (a, b, c) zonal wind (u), (d, e, f) temperature, (g, h, i) pressure, (j, k, l) geopotential height (GH), and (m, n, o) relative humidity for ascending stage (left column), drifting stage (middle column), descending stage (right column) of return radiosonde data set before (black lines) and after (red lines) quality control

    图  10  往返探空观测资料集的水平风相对于GRAPES模式背景场的标准差和偏差的垂直分布

    Figure  10.  Vertical distributions of STD (Standard deviation) and bias of horizontal wind between return radiosonde data set and GRAPES (Global/Regional Assimilation and Prediction System) model background field

    图  11  图10,但为温度的标准差和偏差的垂直分布

    Figure  11.  As in Fig. 10, but for vertical distribution of STD and bias for temperature

    图  12  图10,但为相对湿度的标准差和偏差的垂直分布

    Figure  12.  As in Fig. 10, but for vertical distribution of STD and bias for relative humidity

    图  13  图10,但为气压的标准差和偏差的垂直分布

    Figure  13.  As in Fig. 10, but for vertical distribution of STD and bias for pressure

    图  14  往返探空观测资料集与GRAPES模式背景场差值的概率密度分布

    Figure  14.  Probability density distribution (PDF) of differences between return radiosonde data set and GRAPES model background field

    表  1  2018年6月10日至7月10日往返探空观测资料统计信息

    Table  1.   Statistical information of return radiosonde data from 10 June to 10 July 2018

    站点名称总探
    测次数
    平漂
    成功率
    上升段平均
    观测时长/h
    上升段平均
    球炸高度/m
    平漂段平均
    观测时长/h
    下降段平均
    观测时长/h
    下降段平均
    终止高度/m
    安庆5945.8%1.5127060.15.541.011813.4
    长沙6046.7%1.4327433.25.140.754135.2
    赣州5944.1%1.3426006.95.220.774554.9
    南昌6142.6%1.4827315.15.380.912596.9
    武汉6243.5%1.4627050.35.720.91861.7
    宜昌6246.8%1.3826144.65.210.883563.5
    下载: 导出CSV

    表  2  往返探空观测资料集观测要素质量控制前后的样本数、时间变率均值、时间变率标准差、以及资料剔除率

    Table  2.   The sample numbers, mean value of time variability, standard deviation of time variability, and the data rejection rate of observation elements from return radiosonde data set before and after quality control

    样本数时间变率的均值时间变率的标准差资料剔除率
    质量控制前质量控制后质量控制前质量控制后质量控制前质量控制后
    纬向风25609902465230−0.001 m s−2−0.001 m s−20.52 m s−20.25 m s−23.74%
    温度25609902453340−0.008 °C s−1−0.009 °C s−10.17 °C s−10.16 °C s−14.20%
    气压25609902454410−0.103 hPa s−1−0.101 hPa s−10.38 hPa s−10.32 hPa s−14.16%
    位势高度256099025014002.525 gpm s−12.474 gpm s−18.17 gpm s−18.12 gpm s−12.33%
    相对湿度25609902479280−0.007% s−1−0.007% s−10.57% s−10.44% s−13.19%
    下载: 导出CSV

    表  3  往返探空观测数据集的纬向风、经向风、温度、相对湿度、气压相对于模式背景场的标准差

    Table  3.   Standard deviations of zonal wind, meridional wind, temperature, relative humidity, pressure between return radiosonde data set and GRAPES model background field

    探测阶段垂直层次OMB标准差
    纬向风/m s−1经向风/m s−1日间温度/K夜间温度/K相对湿度气压/hPa
    上升段对流层顶以下2.422.841.030.9215.58%0.63
    上升段对流层顶以上3.013.561.871.470.54
    平漂段对流层顶以上3.133.306.031.540.49
    下降段对流层顶以下2.502.741.160.8016.48%0.75
    下降段对流层顶以上2.813.232.331.450.61
    下载: 导出CSV

    表  4  往返探空观测数据集上升段观测相对于同站址业务探空的标准差和偏差

    Table  4.   Standard deviations and biases between return radiosonde data set and operational radiosonde at the same site

    探测要素垂直层次标准差偏差
    纬向风对流层顶以下3.24 m s−1−0.44 m s−1
    对流层顶以上3.14 m s−10.50 m s−1
    经向风对流层顶以下3.59 m s−10.30 m s−1
    对流层顶以上3.37 m s−1−0.96 m s−1
    温度对流层顶以下1.38 K0.42 K
    对流层顶以上2.73 K0.12 K
    气压对流层顶以下0.90 hPa−0.76 hPa
    对流层顶以上0.64 hPa−1.82 hPa
    相对湿度对流层顶以下16.28%5.51%
    下载: 导出CSV
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  • 收稿日期:  2019-08-19
  • 网络出版日期:  2020-01-15
  • 刊出日期:  2020-07-25

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