Please wait a minute...
img img
Adv. Search
Advances in Earth Science  2019, Vol. 34 Issue (11): 1120-1130    DOI: 10.11867/j.issn.1001-8166.2019.11.1120
    
Overview of Researches on All-Sky Satellite Microwave Data Variational Assimilation
Fangli Dou1,2,3(),Qifeng Lu3(),Yang Guo3
1. Chinese Academy of Meteorological Sciences, Beijing 100081, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. Key Laboratory of Radiometric Calibration and Validation for Environment Satellites, National Satellite Meteorological Center, Beijing 100081, China
Download:  HTML  PDF (842KB) 
Export:  BibTeX | EndNote (RIS)      
Abstract  

As the important components of the earth’s atmospheric system, cloud and precipitation strongly affect the global hydrology and energy cycles through the interaction of solar and infrared radiation with cloud droplets and the release of latent heat in precipitation development. The microwave observations in cloudy and rainy conditions have a large amount of information closely related to the development of weather systems, especially the severe weather systems like typhoon and rainstorm. Nevertheless, satellite microwave observations are usually only assimilated in clear-sky above the ocean and their cloud and precipitation content is discarded. Over the past two decades, several Numerical Weather Prediction (NWP) centers have gradually developed the “all-sky” approach to make use of the cloud- and precipitation-affected microwave radiances. It’s been proved that the all-sky assimilation can be used to improve the first guessed mass, wind, humidity, cloud and precipitation through the tracer effect. For providing an investigated reference for the future research of all-weather assimilation in domestic numerical weather forecast, this paper reviewed the all-sky assimilation methods using microwave observation data, analyzed the advantages and disadvantages of each method, and discussed the key technical problems and the existing difficulties and challenges in this field. With the development and application of the new generation of NWP model in China, advancing the domestic research of all-weather data assimilation technology will bring more scientific and practical benefits in the future.

Key words:  All-sky      Cloud and precipitation      Microwave      Data assimilation      1 DVar.     
Received:  01 July 2019      Published:  31 December 2019
ZTFLH:  P456.7  
Fund: the National Natural Science Foundation of China ”Research on improving the high-frequency microwave scattering radiative transfer model in the microwave all-sky assimilation”(41905034)
Corresponding Authors:  Qifeng Lu     E-mail:  doufl@cma.gov.cn;luqf@cma.gov.cn
About author:  Dou Fangli (1986-), female, Binzhou City, Shandong Province, Assistant professor. Research areas include microwave remote sensing, data assimilation. E-mail:doufl@cma.gov.cn
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Fangli Dou
Qifeng Lu
Yang Guo

Cite this article: 

Fangli Dou,Qifeng Lu,Yang Guo. Overview of Researches on All-Sky Satellite Microwave Data Variational Assimilation. Advances in Earth Science, 2019, 34(11): 1120-1130.

URL: 

http://www.adearth.ac.cn/EN/10.11867/j.issn.1001-8166.2019.11.1120     OR     http://www.adearth.ac.cn/EN/Y2019/V34/I11/1120

Fig.1  Flowchart describing the “1D+4DVar”(solid lines) and the direct 4DVar(dotted lines) methods for the all-sky assimilation
机构业务同化的微波资料预备同化的微波资料同化方案湿控制变量
ECMWFSSMIS,GMI,AMSR-2,MHS,MWHS-2和SAPHIRATMS,AMSU-A和ATMS混合四维变分相对湿度
JMAGMI,AMSR-2和SSMISMWRI,MHS,ATMS,MWHS-2,SAPHIR和AMSU-A混合四维变分对数绝对湿度
NCEPAMSU-AGMI,AMSR-2,MHS和ATMS混合四维变分相对湿度、总水混合比
Met OfficeMHS,ATMS,SSMIS,MWHS-2,SAPHIR,GMI,AMSU-A和ATMS混合四维变分水汽、云冰、云水混合比
Météo-FranceMHS,ATMS,SSMIS,MWHS-2,SAPHIR和GMI混合四维变分绝对湿度
DWDMHS,ATMS,SSMIS,MWHS-2,SAPHIR和GMI混合三维变分水汽、云冰、云水混合比
Table 1  The status of all-sky assimilation operation in global NWP centers
1 Yang Jun,Chen Baojun,Yin Yan,et al. Physics of Clouds and Precipitation[M]. Beijing:China Meteorological Press,2011.
1 杨军,陈宝君,银燕,等.云降水物理学[M].北京:气象出版社,2011.
2 Lopez P. Cloud and precipitation parameterizations in modeling and variational data assimilation:A review[J]. Journal of the Atmospheric Sciences,2007,64(11):3 766-3 784.
3 Kalnay E.Atmospheric Modeling,Data Assimilation and Predictability [M]. UK:Cambridge University Press,2003.
4 Bauer P,Geer A J,Lopez P,et al. Direct 4D-Var assimilation of all-sky radiances. Part I: Implementation[J].Quarterly Journal of the Royal Meteorological Society,2010,136(652):1 868-1 885.
5 Kelly G,Thepaut J N.Evaluation of the impact of the space component of the global observation system through observing system experiments[EB/OL].
5 Newsletter ECMWF,No.113,ECMWF,Reading,UK,2007,16-28.[2019-08-07]..
6 Geer A J,Lonitz K,Weston P,et al. All-sky satellite data assimilation at operational weather forecasting centres[J].Quarterly Journal of the Royal Meteorological Society,2018,144:1 191-1 217.
7 Geer A J,Bauer P,Lopez P,et al. Direct 4D-Var assimilation of all-sky radiances. Part II:Assessment[J]. Quarterly Journal of the Royal Meteorological Society,2010,136(652):1 886-1 905.
8 Zhu Y Q, Liu E, Mahajan R,et al. All-sky microwave radiance assimilation in NCEP’s GSI analysis system[J]. Monthly Weather Review,2016,136(7):4 709-4 733.
9 Yang C, Liu Z, Bresch J,et al. AMSR2 all-sky radiance assimilation and its impact on the analysis and forecast of Hurricane Sandy with a limited-area data assimilation system[J]. Tellus A,2016,68(1). DOI:.
doi: 10.3402/tellusa.v68.30917
10 Errico R M, Bauer P, Mahfouf J, et al. Issues regarding the assimilation of cloud and precipitation data[J]. Journal of the Atmospheric Sciences,2007,64(11):3 785-3 798.
11 Eyre J R, Kelly G A, Mcnally A P, et al. Assimilation of TOVS radiance information through one-dimensional variational analysis[J]. Quarterly Journal of the Royal Meteorological Society,1993,119(514):1 427-1 463.
12 Phalippou L.Variational retrieval of humidity profile,wind speed and cloud liquid-water path with the SSM/I:Potential for numerical weather prediction[J]. Quarterly Journal of the Royal Meteorological Society,1996,122(530):327-355.
13 Puri K, Miller M J. The use of satellite data in the specification of convective heating for diabatic initialization and moisture adjustment in numerical weather prediction models[J]. Monthly Weather Review,1990,118(1):67-93.
14 Heckley W A, Kelly G, Tiedtke M, et al. On the use of satellite-derived heating rates for data assimilation within the tropics[J].Monthly Weather Review,1990,118(9):1 743-1 757.
15 Hou A Y, Zhang S Q, Silva A D, et al. Improving global analysis and short-range forecast using rainfall and moisture observations derived from TRMM and SSM/I passive microwave sensors[J]. Bulletin of the American Meteorological Society,2001,82(4):659-679.
16 Hou A Y, Zhang S Q, Reale O, et al. Variational continuous assimilation of TMI and SSM/I rain rates:Impact on GEOS-3 Hurricane analyses and forecasts[J]. Monthly Weather Review,2004,132(8):2 094-2 109.
17 Peng S, Zou X. Assimilation of NCEP multi-sensor hourly rainfall data using 4D-Var approach:A case study of the squall line on April 5,1999[J]. Meteorology and Atmospheric Physics,2002,81(3/4):237-255.
18 Treadon R E. Assimilation of Satellite Derived Precipitation Estimates with the NCEP GDAS[D]. Tallahassee:The Florida State University,1997.
19 Tsuyuki T. Variational data assimilation in the tropics using precipitation data. Part III:Assimilation of SSM/I precipitation rates[J]. Monthly Weather Review,1997,125(7):1 447-1 464.
20 Gérard E, Saunders R W. Four-dimensional variational assimilation of special sensor microwave/imager total column water vapour in the ECMWF model[J]. The Quarterly Journal of the Royal Meteorological Society,1999,125(560):3 077-3 101.
21 Marecal V, Mahfouf J. Four-Dimensional variational assimilation of total column water vapor in rainy areas[J]. Monthly Weather Review,2002,130(1):43-58.
22 Marecal V, Mahfouf J. Experiments on 4D-Var assimilation of rainfall data using an incremental formulation[J]. Quarterly Journal of the Royal Meteorological Society,2003,129(594):3 137-3 160.
23 Bauer P, Lopez P, Benedetti A, et al. Implementation of 1D+4D-Var assimilation of precipitation-affected microwave radiances at ECMWF. Part I:1D-Var[J]. Quarterly Journal of the Royal Meteorological Society,2006,132(620):2 277-2 306.
24 Bauer P, Lopez P, Salmond D,et al. Implementation of 1D-4DVAR assimilation of precipitation-affected microwave radiances at ECMWF. Part II:4DVAR[J]. Quarterly Journal of the Royal Meteorological Society,2006,132(620):2 307-2 332.
25 Bauer P, Auligne T, Bell W, et al. Satellite cloud and precipitation assimilation at operational NWP centres[J]. Quarterly Journal of the Royal Meteorological Society,2011,137(661):1 934-1 951.
26 Kazumori M, Geer A J, English S J. Effects of all-sky assimilation of GCOM-W/AMSR2 radiances in the ECMWF numerical weather prediction system[J]. Quarterly Journal of the Royal Meteorological Society,2016,142(695):721-737.
27 Deblonde G, Mahfouf J F, Bilodeau B, et al. One-dimensional variational data assimilation of SSM/I observations in rainy atmospheres at MSC[J]. Monthly Weather Review,2007,135(1):152-172.
28 Koizumi K, Ishikawa Y, Tsuyuki T. Assimilation of precipitation data to the JMA mesoscale model with a 4Dvar and its impact on precipitation forecasts[J]. Scientific Online Letters on the Atmosphere,2005,1:45-48.
29 Takayuki T, Isao T, Kazumasa A, et al. Improvement of spin-up of precipitation calculation with use of observed rainfall in the initialization scheme[J]. Atmosphere,1997,35:353-368.
30 Kelly G A, Bauer P, Geer A J, et al. Impact of SSM/I observations related to moisture,clouds,and precipitation on global NWP forecast skill[J]. Monthly Weather Review,2010,136(7):2 713-2 726.
31 Liu Yongliang. Application Research of 1D-Var Retrieval Technology in Cloud-and Precipitation-effected Satellite Microwave Observation Data Assimilation[D]. Changsha:National University of Defense Technology,2013.
31 刘永亮. 一维变分反演技术在云水污染卫星微波观测资料同化中的应用研究[D]. 长沙:国防科学技术大学,2013.
32 Zhang Sibo. Research on the Direct Variational Assimilation of Cloudy Satellite Microwave Radiances[D].Nanjing:Nanjing University of Information Science & Technology,2015.
32 张思勃. 云区卫星微波资料直接变分同化研究[D]. 南京:南京信息工程大学,2015.
33 Geer A J, Baordo F. Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies[J]. Atmospheric Measurement Techniques,2014,7(6):1 839-1 860.
34 Zhang M, Zupanski M, Kim M, et al. Assimilating AMSU-A radiances in the TC core area with NOAA operational HWRF (2011) and a hybrid data assimilation system:Danielle (2010)[J]. Monthly Weather Review,2013,141(11):3 889-3 907.
35 Lawrence H, Bormann N, Geer A J, et al. Evaluation and assimilation of the microwave sounder MWHS-2 onboard FY-3C in the ECMWF numerical weather prediction system[J]. IEEE Transactions on Geoscience & Remote Sensing,2018,56(6):3 333-3 349.
36 Su Jie, Zhu Keyun, Zhang Jie. Application of RTTOV scattering module to FY-3 MWHS data assimilation[J]. Meteorology,2013,39(11):1 461-1 472.
36 苏捷,朱克云,张杰. RTTOV散射模块在FY-3MWHS资料同化中的应用[J]. 气象,2013,39(11):1 461-1 472.
37 Moreau E, Lopez P,Bauer P,et al. Variational retrieval of temperature and humidity profiles using rain rates versus microwave brightness temperatures[J]. Quarterly Journal of the Royal Meteorological Society,2004,130(598):827-852.
38 Chen S, Vandenberghe F, Petty G W, et al. Application of SSM/I satellite data to a hurricane simulation[J]. Quarterly Journal of the Royal Meteorological Society,2004,130(598):801-825.
39 Tiedtke M. Representation of clouds in large-scale models[J]. Monthly Weather Review,1993,121(11):3 040-3 061.
40 Okamoto K. Assimilation of overcast cloudy infrared radiances of the geostationary MTSAT-1R imager[J]. Quarterly Journal of the Royal Meteorological Society,2013,139(672):715-730.
41 Sundqvist H. A parameterization scheme for non-convective condensation including prediction of cloud water content[J].Quarterly Journal of the Royal Meteorological Society,1978,104(441):677-690.
42 Ma Leiming, Bao Xuwei. Research progress on physical parameterization schemes in numerical weather prediction models[J].Advances in Earth Science,2017,32(7):679-687.
42 马雷鸣,鲍旭炜. 数值天气预报模式物理过程参数化方案的研究进展[J].地球科学进展,2017,32(7):679-687.
43 Gettelman A, Morrison H, Ghan S J, et al. A new two-moment bulk stratiform cloud microphysics scheme in the Community Atmosphere Model,version 3 (CAM3). Part II:Single-Column and Global Results[J]. Journal of Climate,2008,21(15):3 660-3 679.
44 Vukicevic T, Errico R M. Linearization and adjoint of parameterized moist diabatic processes[J]. Tellus A,1993,45(5):493-510.
45 ?upanski D. The effects of discontinuities in the Betts-Miller cumulus convection scheme on four-dimensional variational data assimilation[J]. Tellus A,1993,45(5):511-524.
46 Zou X. Tangent linear and adjoint of on-off processes and their feasibility for use in 4-dimensional variational data assimilation[J]. Tellus A,1998,49(1):3-31.
47 Mahfouf J. Influence of physical processes on the tangent-linear approximation[J]. Tellus A,1999,51(2):147-166.
48 Mahfouf J F,Rabier J. The ECMWF operational implementation of four dimensional variational assimilation. Part II:Experimental results with improved physics[J]. Quarterly Journal of the Royal Meteorological Society,1991,126:1 171-1 190.
49 Saunders R,Rayer P,Brunel P,et al. A comparison of radiative transfer models for simulating Atmospheric Infrared Sounder (AIRS) radiances[J]. Journal of Geophysical Research Atmospheres,2007,112(D1). DOI:.
doi: 10.1029/2006JD007088
50 Weng F. Advances in radiative transfer modeling in support of satellite data assimilation[J]. Journal of the Atmospheric Sciences,2009,64(11):3 799.
51 Liu Q,Ruprecht E. Radiative transfer model:Matrix operator method[J]. Applied Optics,1996,35(21):4 229-4 237.
52 Bennartz R,Greenwald T. Current problems in scattering radiative transfer modelling for data assimilation[J]. Quarterly Journal of the Royal Meteorological Society,2011, 137(661):1 952-1 962.
53 Dong Peiming,Wang Haijun,Han Wei,et al. The effect of water content on the simulation of satellite microwave observation in cloudy and rainy area[J]. Journal of Applied Meteorological Science,2009,20(6):682-691.
53 董佩明,王海军,韩威,等. 水物质对云雨区卫星微波观测模拟影响[J]. 应用气象学报,2009,20(6):682-691.
54 Dong Peiming,Huang Jiangping,Liu Guiqing,et al. Assimilation of FY-3A microwave observations and simulation of brightness temperature under cloudy and rainy condition[J]. Journal of Tropical Meteorology,2014,30(2):302-310.
54 董佩明,黄江平,刘桂青,等. FY-3A微波探测资料的直接同化应用及云雨条件下的亮温模拟[J]. 热带气象学报,2014,30(2):302-310.
55 Liu Shuosong,Dong Peiming,Han Wei,et al. Simulative study of satellite microwave observations for Typhoon Luosha using RTTOV and CRTM and the comparison[J]. Acta Meteorologica Sinica,2012,70(3):585-597.
55 刘硕松,董佩明,韩威,等.RTTOV和CRTM对“罗莎”台风卫星微波观测的模拟研究与比较[J]. 气象学报,2012,70(3):585-597.
56 Wiedner M C,Prigent C,Pardo J R,et al. Modeling of passive microwave responses in convective situations using output from mesoscale models:Comparison with TRMM/TMI satellite observations[J]. Journal of Geophysical Research,2004,109(D6):D06214.
57 Doherty A M,Sreerekha T R,O"Keeffe U M,et al. Ice hydrometeor microphysical assumptions in radiative transfer models at AMSU-B frequencies[J]. Quarterly Journal of the Royal Meteorological Society,2007,133(626):1 205-1 212.
58 Surussavadee C,Staelin D H. Comparison of AMSU millimeter-wave satellite observations,MM5/TBSCAT predicted radiances,and electromagnetic models for hydrometeors[J]. IEEE Transactions on Geoscience and Remote Sensing,2006,44(10):2 667-2 678.
59 Wang Gen,Zhang Hua,Yang Yin. Research progress of quality control for AIRS data[J]. Advances in Earth Science,2017,32(2):139-150.
59 王根,张华,杨寅. 高光谱大气红外探测器AIRS资料质量控制研究进展[J]. 地球科学进展,2017,32(2):139-150.
60 Amerault C,Zou X. Preliminary steps in assimilating SSM/I brightness temperatures in a hurricane prediction scheme[J].Journal of Atmospheric and Oceanic Technology,2003,20(8):1 154-1 169.
61 Amerault C,Zou X. Comparison of model-produced and observed microwave radiances and estimation of background error covariances for hydrometeor variables within hurricanes[J]. Monthly Weather Review,2006,134(3):745-758.
62 Parrish D F,Derber J C. The national meteorological center’s spectral statistical-interpolation analysis system[J]. Monthly Weather Review,1992,120(8):1 747-1 763.
63 Geer A J,Bauer P. Observation errors in all-sky data assimilation[J]. Quarterly Journal of the Royal Meteorological Society,2011,137(661):2 024-2 037.
64 Minamide M,Zhang F. Adaptive observation error inflation for assimilating all-sky satellite radiance[J]. Monthly Weather Review,2017,145(3):1 063-1 081.
65 Kim M J,Jin J,McCarty W,et al.All-sky microwave radiance data assimilation in NASA GEOS-5 system:Developments,impacts,and future plans[C]//20th Conference on Integrated Observing Assimilation Systems for the Atmosphere,Oceans,and Landsurface. New Orleans LA, 2016.
66 Guerbette J,Mahfouf J F,Plu M. Towards the assimilation of all-sky microwave radiances from the SAPHIR humidity sounder in a limited area NWP model over tropical regions[J]. Tellus,2016,68. DOI:.
doi: 10.3402/tellusa.v68.28620
67 Madhulatha A,George J P,Rajagopal E N. All-sky radiance simulation of Megha-Tropiques SAPHIR microwave sensor using multiple scattering radiative transfer model for data assimilation applications[J]. Journal of Earth System Science,2017,126(2). DOI:.
doi: 10.1007/s12040-017-0805-3
[1] CHEN Chong-cheng, WANG Xiao-qin, WANG Qin-min, HUANG Xuan. ANALYSIS ON LAND USE CHANGE BY USING INTEGRATED REMOTE SENSING CHANGE DETECTION TECHNIQUES[J]. Advances in Earth Science, 2002, 17(5): 748 -753 .
[2] JIANG Yuan, ZHAO Hai-xia, LIU Xiao-cong, CHANG Yu-tao. HUMAN IMPACT ON THE MEADOW VEGETATION IN DONGLING MOUNTAIN, BEIJING AND MEASURES FOR CONSERVATION OF THE MEADOW VEGETATION[J]. Advances in Earth Science, 2002, 17(2): 235 -240 .
[3] LIU Yulin. A NEW METHOD OF K-Ar DATING: PEAK COMPARISON METHOD[J]. Advances in Earth Science, 2004, 19(2): 312 -315 .
[4] Lan Jian,Hong Jieli,Li Pixue. Seasonal Variability of Cool-core Eddy in the Western South China Sea[J]. Advances in Earth Science, 2006, 21(11): 1145 -1152 .
[5] Shen Yanbo,Zhao Zongci,Shi Guangyu2. The Progress in Variation of Surface Solar Radiation, Factors and Probable Climatic Effects[J]. Advances in Earth Science, 2008, 23(9): 915 -924 .
[6] Dai Jing, Sun Bainian, Xie Sanping, Wu Jingyu, Li Na. Carpinus miofangiana from the Pliocene of Tengchong in Yunnan Province and its Palaeoclimatic Significance[J]. Advances in Earth Science, 2009, 24(9): 1024 -1032 .
[7] YANG Xin;YAN Junping;LIU Baoyuan. THE ANALYSIS ON THE CHANGE CHARACTERISTICS AND DRIVING FORCES OF WUDINGHE RIVER RUNOFF[J]. Advances in Earth Science, 2005, 20(6): 637 -642 .
[8] Xu Zhongmin,Zhong Fanglei,Jiao Wenxian. Expectation of the Research on Human Factors' Function in Water-Ecology-Economy System[J]. Advances in Earth Science, 2008, 23(7): 723 -731 .
[9] Shen Chengde, Yi Weixi, Liu Dongsheng. ADVANCE IN 10Be STUDY IN CHINESE LOESS[J]. Advances in Earth Science, 1995, 10(6): 590 -596 .
[10] Zeng Jingjing, Qu Jiansheng, Zhang Zhiqiang. Review of the International Greenhouse Gas Emission Reduction Scenario Programs[J]. Advances in Earth Science, 2009, 24(4): 436 -443 .