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Volume 7 Issue 4

Oct.  1990

Article Contents

Use of Surface Observations to Estimate Upper Air Humidity for the Objective Analysis of Relative Humidity over Indian Region


doi: 10.1007/BF03342567

  • In the present study objective analyses of relative humidity (RH) at surface and at the levels of 850,700 and 500 hPa have been made using Gandins (1963) optimum interpolation scheme. As the horizontal resolution of the radiosonde stations is rather inadequate for upper air humidity analysis, a scheme has been developed, following Rasmussen (1982) to estimate the upper air RH from the surface observations like surface RH, present weather and cloud cover. The relative humidities at the levels 850, 700 and 500 hPa were related to the surface observations through three separate regression relations. The RH values at 850, 700 and 500 hPa levels were estimated from the surface RH, cloud coverage and present weather using the above regression relations and subsequently the objective analyses at 00 GMT for the period from 4 July to 8 July 1979, were made using these estimated data along with the observed radiosonde data. Objective analyses were also made for the same period using only the radiosonde data for comparison to study the impact of those estimated data. Root mean square errors were computed for all the five days by interpolating RH at the observing stations from the objectively analysed field and comparing them with the actually observed RH to examine how best the analyses (with and without estimated data) fitted the observations. Lastly they were compared with satellite cloud pictures. This study shows that the estimated upper air RH values have positive impact on the analysis of upper air RH and could be used over radiosonde date sparse region and even over oceanic regions.
  • [1] LI Tao, ZHENG Xiaogu, DAI Yongjiu, YANG Chi, CHEN Zhuoqi, ZHANG Shupeng, WU Guocan, WANG Zhonglei, HUANG Chengcheng, SHEN Yan, LIAO Rongwei, 2014: Mapping Near-surface Air Temperature, Pressure, Relative Humidity and Wind Speed over Mainland China with High Spatiotemporal Resolution, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 1127-1135.  doi: 10.1007/s00376-014-3190-8
    [2] HUANG Yi, WANG Meihua, MAO Jietai, 2004: Retrieval of Upper Tropospheric Relative Humidity by the GMS-5 Water Vapor Channel: A Study of the Technique, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 53-60.  doi: 10.1007/BF02915680
    [3] S. K. Sinha, D. R. Talwalkar, S. Rajamani, 1987: ON SOME ASPECTS OF OBJECTIVE ANALYSIS OF HUMI-DITY OVER INDIAN REGION BY THE OPTIMUM INTERPOLATION METHOD, ADVANCES IN ATMOSPHERIC SCIENCES, 4, 332-342.  doi: 10.1007/BF02663603
    [4] Jingpeng ZHANG, Tianbao ZHAO, Zhi LI, Chunxiang LI, Zhen LI, Kairan YING, Chunxiang SHI, Lipeng JIANG, Wenyu ZHANG, 2021: Evaluation of Surface Relative Humidity in China from the CRA-40 and Current Reanalyses, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1958-1976.  doi: 10.1007/s00376-021-0333-6
    [5] Zhen LI, Zhongwei YAN, Yani ZHU, Nicolas FREYCHET, Simon TETT, 2020: Homogenized Daily Relative Humidity Series in China during 1960−2017, ADVANCES IN ATMOSPHERIC SCIENCES, 37, 318-327.  doi: 10.1007/s00376-020-9180-0
    [6] GAO Zhiqiu, BIAN Lingen, CHEN Zhigang, Michael SPARROW, ZHANG Jiahua, 2006: Turbulent Variance Characteristics of Temperature and Humidity over a Non-uniform Land Surface for an Agricultural Ecosystem in China, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 365-374.  doi: 10.1007/s00376-006-0365-y
    [7] Yidan SI, Shenshen LI, Liangfu CHEN, Chao YU, Zifeng WANG, Yang WANG, Hongmei WANG, 2018: Validation and Spatiotemporal Distribution of GEOS-5-Based Planetary Boundary Layer Height and Relative Humidity in China, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 479-492.  doi: 10.1007/s00376-017-6275-3
    [8] Julian X.L. Wang, Dian J. Gaffen, 2001: Trends in Extremes of Surface Humidity, Temperature, and Summertime Heat Stress in China, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 742-751.
    [9] Kyu Rang KIM, Tae Heon KWON, Yeon-Hee KIM, Hae-Jung KOO, Byoung-Cheol CHOI, Chee-Young CHOI, 2009: Restoration of an Inner-City Stream and Its Impact on Air Temperature and Humidity Based on Long-Term Monitoring Data, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 283-292.  doi: 10.1007/s00376-009-0283-x
    [10] M. Y. Totagi, D. R. Talwalkar, S. Rajamani, S. S. Singh, 1992: Analysis-Prediction Experiments over Indian Region Using Primitive Equation Barotropic Model, ADVANCES IN ATMOSPHERIC SCIENCES, 9, 477-482.  doi: 10.1007/BF02677080
    [11] Keyi CHEN, Niels BORMANN, Stephen ENGLISH, Jiang ZHU, 2018: Assimilation of Feng-Yun-3B Satellite Microwave Humidity Sounder Data over Land, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 268-275.  doi: 10.1007/s00376-017-7088-0
    [12] Zhang Ying, Shen Xinyong, Zhang Ming, 1990: Analysis and Study of a Mesoscale Inertia-Gravitational Wave in Upper Air, ADVANCES IN ATMOSPHERIC SCIENCES, 7, 220-226.  doi: 10.1007/BF02919160
    [13] Xianhong MENG, Shihua LYU, Zhaoguo LI, Yinhuan AO, Lijuan WEN, Lunyu SHANG, Shaoying WANG, Mingshan DENG, Shaobo ZHANG, Lin ZHAO, Hao CHEN, Di MA, Suosuo LI, Lele SHU, Yingying AN, Hanlin NIU, 2023: Dataset of Comparative Observations for Land Surface Processes over the Semi-Arid Alpine Grassland against Alpine Lakes in the Source Region of the Yellow River, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1142-1157.  doi: 10.1007/s00376-022-2118-y
    [14] Jeong-Hyeong LEE, Keon-Tae SOHN, 2007: Prediction of Monthly Mean Surface Air Temperature in a Region of China, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 503-508.  doi: 10.1007/s00376-007-0503-1
    [15] Yuli ZHANG, Chuanxi LIU, Yi LIU, Rui YANG, 2019: Intraseasonal Oscillation of Tropospheric Ozone over the Indian Summer Monsoon Region, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 417-430.  doi: 10.1007/s00376-018-8113-7
    [16] Lu Longhua, Chen Xianji, Zhu Fukang, 1985: THE INTERANNUAL VARIATION OF MEDIUM-RANGE OSCILLATION CHARACTERISTICS IN THE UPPER TROPOSPHERE OVER THE SUBTROPICAL REGION, ADVANCES IN ATMOSPHERIC SCIENCES, 2, 54-62.  doi: 10.1007/BF03179737
    [17] S.K. Sinha, S. Rajamani, 1995: Multivariate Objective Analysis of Wind and Height Fields in the Tropics, ADVANCES IN ATMOSPHERIC SCIENCES, 12, 233-244.  doi: 10.1007/BF02656836
    [18] Yushan SONG, Daren LÜ, Qian LI, Jianchun BIAN, Xue WU, Dan LI, 2016: The Impact of Cut-off Lows on Ozone in the Upper Troposphere and Lower Stratosphere over Changchun from Ozonesonde Observations, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 135-150.  doi: 10.1007/s00376-015-5054-2
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    [20] S. S. Dugam, S. B. Kakade, R. K. Verma, 1990: Global Annual Mean Surface Air Temperature Anomalies and Their Link with Indian Summer Monsoon Failures, ADVANCES IN ATMOSPHERIC SCIENCES, 7, 245-248.  doi: 10.1007/BF02919162

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Manuscript History

Manuscript received: 10 October 1990
Manuscript revised: 10 October 1990
通讯作者: 陈斌, bchen63@163.com
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Use of Surface Observations to Estimate Upper Air Humidity for the Objective Analysis of Relative Humidity over Indian Region

  • 1. Indian Institute of Tropical Meteorology, Pune-411008, India,Indian Institute of Tropical Meteorology, Pune-411008, India,Indian Institute of Tropical Meteorology, Pune-411008, India,Indian Institute of Tropical Meteorology, Pune-411008, India,Indian Institute of Tropical Meteorology, Pune-411008, India,Indian Institute of Tropical Meteorology, Pune-411008, India

Abstract: In the present study objective analyses of relative humidity (RH) at surface and at the levels of 850,700 and 500 hPa have been made using Gandins (1963) optimum interpolation scheme. As the horizontal resolution of the radiosonde stations is rather inadequate for upper air humidity analysis, a scheme has been developed, following Rasmussen (1982) to estimate the upper air RH from the surface observations like surface RH, present weather and cloud cover. The relative humidities at the levels 850, 700 and 500 hPa were related to the surface observations through three separate regression relations. The RH values at 850, 700 and 500 hPa levels were estimated from the surface RH, cloud coverage and present weather using the above regression relations and subsequently the objective analyses at 00 GMT for the period from 4 July to 8 July 1979, were made using these estimated data along with the observed radiosonde data. Objective analyses were also made for the same period using only the radiosonde data for comparison to study the impact of those estimated data. Root mean square errors were computed for all the five days by interpolating RH at the observing stations from the objectively analysed field and comparing them with the actually observed RH to examine how best the analyses (with and without estimated data) fitted the observations. Lastly they were compared with satellite cloud pictures. This study shows that the estimated upper air RH values have positive impact on the analysis of upper air RH and could be used over radiosonde date sparse region and even over oceanic regions.

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