MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS Ⅱ: IMPACTS ON RAINSTORM FORECASTING
Satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy rainfall.However,we have not fully taken advantage of satellite observations in the data assimilation of numerical weather predictions,especially those in infrar...
Saved in:
Published in | Journal of Tropical Meteorology Vol. 17; no. 3; pp. 221 - 230 |
---|---|
Main Author | |
Format | Journal Article |
Language | English |
Published |
Guangzhou
Guangzhou Institute of Tropical & Marine Meteorology
01.09.2011
Guangzhou Institute of Tropical and Marine Meteorology,CMA,Guangzhou 510080 China |
Subjects | |
Online Access | Get full text |
ISSN | 1006-8775 |
DOI | 10.3969/j.issn.1006-8775.2011.03.004 |
Cover
Abstract | Satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy rainfall.However,we have not fully taken advantage of satellite observations in the data assimilation of numerical weather predictions,especially those in infrared channels. It is common to only assimilate radiances under clear-sky conditions since it is extremely difficult to simulate infrared transmittance in cloudy sky.On the basis of the Global and Regional Assimilation and Prediction Enhanced System 3-dimensional variance(GRAPES-3DVar),cloud liquid water content, ice-water content and cloud cover are employed as governing variables in the assimilation system.This scheme can improve the simulation of infrared transmittance by a fast radiative transfer model for TOVS (RTTOV)and adjust the atmospheric and cloud parameters based on infrared radiance observations.In this paper,we investigate a heavy rainfall over Guangdong province on May 26,2007,which is right after the onset of a South China Sea monsoon.In this case,channels of the Moderate Resolution Imaging Spectroradiometer(MODIS)for observing water vapor(Channel 27)and cloud top altitude(Channel 36)are selected for the assimilation.The process of heavy rainfall is simulated by the Weather Research and Forecasting(WRF)model.Our results show that the assimilated MODIS data can improve the distribution of water vapor and temperature in the first guess field and indirectly adjust the upper-level wind field.The tendency of adjustment agrees well with the satellite observations.The assimilation scheme has positive impacts on the short-range forecasting of rainstorm. |
---|---|
AbstractList | Satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy rainfall.However,we have not fully taken advantage of satellite observations in the data assimilation of numerical weather predictions,especially those in infrared channels. It is common to only assimilate radiances under clear-sky conditions since it is extremely difficult to simulate infrared transmittance in cloudy sky.On the basis of the Global and Regional Assimilation and Prediction Enhanced System 3-dimensional variance(GRAPES-3DVar),cloud liquid water content, ice-water content and cloud cover are employed as governing variables in the assimilation system.This scheme can improve the simulation of infrared transmittance by a fast radiative transfer model for TOVS (RTTOV)and adjust the atmospheric and cloud parameters based on infrared radiance observations.In this paper,we investigate a heavy rainfall over Guangdong province on May 26,2007,which is right after the onset of a South China Sea monsoon.In this case,channels of the Moderate Resolution Imaging Spectroradiometer(MODIS)for observing water vapor(Channel 27)and cloud top altitude(Channel 36)are selected for the assimilation.The process of heavy rainfall is simulated by the Weather Research and Forecasting(WRF)model.Our results show that the assimilated MODIS data can improve the distribution of water vapor and temperature in the first guess field and indirectly adjust the upper-level wind field.The tendency of adjustment agrees well with the satellite observations.The assimilation scheme has positive impacts on the short-range forecasting of rainstorm. P412.27; Satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy rainfall.However,we have not fully taken advantage of satellite observations in the data assimilation of numerical weather predictions,especially those in infrared channels.It is common to only assimilate radiances under clear-sky conditions since it is extremely difficult to simulate infrared transmittance in cloudy sky.On the basis of the Global and Regional Assimilation and Prediction Enhanced System 3-dimensional variance (GRAPES-3DVar),cloud liquid water content,ice-water content and cloud cover are employed as governing variables in the assimilation system.This scheme can improve the simulation of infrared transmittance by a fast radiative transfer model for TOVS (RTTOV) and adjust the atmospheric and cloud parameters based on infrared radiance observations.In this paper,we investigate a heavy rainfall over Guangdong province on May 26,2007,which is right after the onset of a South China Sea monsoon.In this case,channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) for observing water vapor (Channel 27) and cloud top altitude (Channel 36) are selected for the assimilation.The process of heavy rainfall is simulated by the Weather Research and Forecasting (WRF) model.Our results show that the assimilated MODIS data can improve the distribution of water vapor and temperature in the first guess field and indirectly adjust the upper-level wind field.The tendency of adjustment agrees well with the satellite observations.The assimilation scheme has positive impacts on the short-range forecasting of rainstorm. |
Author | 丁伟钰 万齐林 黄燕燕 陈子通 张诚忠 |
AuthorAffiliation | Guangzhou Institute of Tropical and Marine Meteorology,CMA |
AuthorAffiliation_xml | – name: Guangzhou Institute of Tropical and Marine Meteorology,CMA,Guangzhou 510080 China |
Author_xml | – sequence: 1 fullname: 丁伟钰 万齐林 黄燕燕 陈子通 张诚忠 |
BookMark | eNpF0EtOwzAQBmAvikR53MEgNiwa7DjxY2mSUCw1SRW7C1aVm0dpBSlNWgEH4BLsuAen4QJcgVRFMJuRRp_-kf4j0KtXdQnABUYOEVRcLZ1F29YORogOOGO-4yKMHUQchLwe6P_dD8Fp2y5RN9THHqd9UMdpqDS8ztTw1iSR1tBE8TjKpJlkEQylkVBqrWI1kkalCZwkYZTBYJROwjsYpEmodmcNv94-vj_foYrHMjAadjKTKtEmzWJ4k2ZRILVRyfAEHFT2oS1Pf_cxmNxEJrgdjNKhCuRokGPmbga-b4vc9d0c05lf5QUnhOYYM1sgPCuYh_zS8ooIhhlB1CuomGErhOWCCC9nFTkGl_vcZ1tXtp5Pl6ttU3cfp02xfnmZTctdQ4h0_XT2fG-fmtV6W7abf8w54kIQvkNne5Tfr-r5etFFPjWLR9u8TolwGfVcTn4AGSpxEQ |
ClassificationCodes | P412.27 |
ContentType | Journal Article |
Copyright | Copyright Guangzhou Institute of Tropical & Marine Meteorology Sep 2011 Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
Copyright_xml | – notice: Copyright Guangzhou Institute of Tropical & Marine Meteorology Sep 2011 – notice: Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
DBID | 2RA 92L CQIGP W94 ~WA 7TG 7TN ABUWG AEUYN AFKRA ATCPS AZQEC BENPR BHPHI BKSAR BVBZV CCPQU DWQXO F1W GNUQQ H96 HCIFZ KL. L.G PATMY PCBAR PHGZM PHGZT PKEHL PQEST PQQKQ PQUKI PRINS PYCSY 2B. 4A8 92I 93N PSX TCJ |
DOI | 10.3969/j.issn.1006-8775.2011.03.004 |
DatabaseName | 维普期刊资源整合服务平台 中文科技期刊数据库-CALIS站点 中文科技期刊数据库-7.0平台 中文科技期刊数据库-自然科学 中文科技期刊数据库- 镜像站点 Meteorological & Geoastrophysical Abstracts Oceanic Abstracts ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland Agricultural & Environmental Science Collection ProQuest Central Essentials ProQuest Natural Science Collection Earth, Atmospheric & Aquatic Science Collection East & South Asia Database ProQuest One ProQuest Central Korea ASFA: Aquatic Sciences and Fisheries Abstracts ProQuest Central Student Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources SciTech Premium Collection Meteorological & Geoastrophysical Abstracts - Academic Aquatic Science & Fisheries Abstracts (ASFA) Professional Environmental Science Database Earth, Atmospheric & Aquatic Science Database ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China Environmental Science Collection Wanfang Data Journals - Hong Kong WANFANG Data Centre Wanfang Data Journals 万方数据期刊 - 香港版 China Online Journals (COJ) China Online Journals (COJ) |
DatabaseTitle | Aquatic Science & Fisheries Abstracts (ASFA) Professional ProQuest Central Student ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Central China Earth, Atmospheric & Aquatic Science Collection ProQuest Central ProQuest One Sustainability Meteorological & Geoastrophysical Abstracts Oceanic Abstracts Natural Science Collection ProQuest Central Korea Agricultural & Environmental Science Collection ProQuest Central (New) ProQuest One Academic Eastern Edition Earth, Atmospheric & Aquatic Science Database East & South Asia Database Environmental Science Collection Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources ProQuest One Academic UKI Edition ASFA: Aquatic Sciences and Fisheries Abstracts Environmental Science Database ProQuest One Academic Meteorological & Geoastrophysical Abstracts - Academic ProQuest One Academic (New) |
DatabaseTitleList | |
Database_xml | – sequence: 1 dbid: BENPR name: ProQuest Central url: http://www.proquest.com/pqcentral?accountid=15518 sourceTypes: Aggregation Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Meteorology & Climatology |
DocumentTitleAlternate | MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS Ⅱ: IMPACTS ON RAINSTORM FORECASTING |
EndPage | 230 |
ExternalDocumentID | rdqxxb_e201103004 2416174401 39276428 |
Genre | General Information |
GroupedDBID | -01 -0A -SA -S~ 2B. 2C. 2RA 3V. 5GY 5VR 7XC 8FE 8FH 8R4 8R5 92E 92I 92L 92M 92Q 93N 9D9 9DA ABDBF ABUWG ACGFS AENEX AFKRA AFRAH AFUIB ALMA_UNASSIGNED_HOLDINGS ATCPS BENPR BHPHI BKSAR BPHCQ BVBZV CAJEA CAJUS CCEZO CCPQU CCVFK CHBEP CQIGP CW9 D1K EOJEC ESX FA0 HCIFZ JUIAU K6- OBODZ PATMY PCBAR PQQKQ PROAC PYCSY Q-- Q-0 Q2X R-A RT1 S.. T8Q TCJ TGP TUS U1F U1G U5A U5K W94 ~LG ~WA 7TG 7TN ABJNI ACUHS AEUYN AZQEC DWQXO F1W GNUQQ H96 KL. L.G PHGZM PHGZT PKEHL PQEST PQUKI PRINS 4A8 PMFND PSX |
ID | FETCH-LOGICAL-c172t-55adc252c16b5fcd8336c117ad01bd7405ea8f397173064d69b1a99a89394c7f3 |
IEDL.DBID | BENPR |
ISSN | 1006-8775 |
IngestDate | Thu May 29 03:58:57 EDT 2025 Sat Jul 26 00:54:58 EDT 2025 Wed Feb 14 09:54:31 EST 2024 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 3 |
Keywords | rainstorm MODIS brightness temperature data assimilation |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c172t-55adc252c16b5fcd8336c117ad01bd7405ea8f397173064d69b1a99a89394c7f3 |
Notes | Satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy rainfall.However,we have not fully taken advantage of satellite observations in the data assimilation of numerical weather predictions,especially those in infrared channels. It is common to only assimilate radiances under clear-sky conditions since it is extremely difficult to simulate infrared transmittance in cloudy sky.On the basis of the Global and Regional Assimilation and Prediction Enhanced System 3-dimensional variance(GRAPES-3DVar),cloud liquid water content, ice-water content and cloud cover are employed as governing variables in the assimilation system.This scheme can improve the simulation of infrared transmittance by a fast radiative transfer model for TOVS (RTTOV)and adjust the atmospheric and cloud parameters based on infrared radiance observations.In this paper,we investigate a heavy rainfall over Guangdong province on May 26,2007,which is right after the onset of a South China Sea monsoon.In this case,channels of the Moderate Resolution Imaging Spectroradiometer(MODIS)for observing water vapor(Channel 27)and cloud top altitude(Channel 36)are selected for the assimilation.The process of heavy rainfall is simulated by the Weather Research and Forecasting(WRF)model.Our results show that the assimilated MODIS data can improve the distribution of water vapor and temperature in the first guess field and indirectly adjust the upper-level wind field.The tendency of adjustment agrees well with the satellite observations.The assimilation scheme has positive impacts on the short-range forecasting of rainstorm. MODIS brightness temperature data; assimilation; rainstorm DING Wei-yu,WAN Qi-lin,HUANG Yan-yan,CHEN Zi-tong,ZHANG Cheng-zhong(Guangzhou Institute of Tropical and Marine Meteorology,CMA,Guangzhou 510080 China) 44-1409/P SourceType-Scholarly Journals-1 ObjectType-General Information-1 content type line 14 |
PQID | 880899384 |
PQPubID | 105712 |
PageCount | 10 |
ParticipantIDs | wanfang_journals_rdqxxb_e201103004 proquest_journals_880899384 chongqing_primary_39276428 |
PublicationCentury | 2000 |
PublicationDate | 2011-09-01 |
PublicationDateYYYYMMDD | 2011-09-01 |
PublicationDate_xml | – month: 09 year: 2011 text: 2011-09-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | Guangzhou |
PublicationPlace_xml | – name: Guangzhou |
PublicationTitle | Journal of Tropical Meteorology |
PublicationTitleAlternate | Journal of Tropical Meteorology |
PublicationTitle_FL | Journal of Tropical Meteorology |
PublicationYear | 2011 |
Publisher | Guangzhou Institute of Tropical & Marine Meteorology Guangzhou Institute of Tropical and Marine Meteorology,CMA,Guangzhou 510080 China |
Publisher_xml | – name: Guangzhou Institute of Tropical & Marine Meteorology – name: Guangzhou Institute of Tropical and Marine Meteorology,CMA,Guangzhou 510080 China |
SSID | ssj0000651486 |
Score | 1.8195792 |
Snippet | Satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy rainfall.However,we... P412.27; Satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy... |
SourceID | wanfang proquest chongqing |
SourceType | Aggregation Database Publisher |
StartPage | 221 |
SubjectTerms | Data collection MODIS数据 中分辨率成像光谱仪 亮度温度 卫星观测 数据同化 暴雨预报 液态水含量 阴天 |
Title | MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS Ⅱ: IMPACTS ON RAINSTORM FORECASTING |
URI | http://lib.cqvip.com/qk/85390X/201103/39276428.html https://www.proquest.com/docview/880899384 https://d.wanfangdata.com.cn/periodical/rdqxxb-e201103004 |
Volume | 17 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
journalDatabaseRights | – providerCode: PRVEBS databaseName: Academic Search Ultimate issn: 1006-8775 databaseCode: ABDBF dateStart: 20110301 customDbUrl: https://search.ebscohost.com/login.aspx?authtype=ip,shib&custid=s3936755&profile=ehost&defaultdb=asn isFulltext: true dateEnd: 99991231 titleUrlDefault: https://search.ebscohost.com/direct.asp?db=asn omitProxy: true ssIdentifier: ssj0000651486 providerName: EBSCOhost – providerCode: PRVPQU databaseName: East & South Asia Database issn: 1006-8775 databaseCode: BVBZV dateStart: 20100301 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://search.proquest.com/eastsouthasia omitProxy: false ssIdentifier: ssj0000651486 providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central issn: 1006-8775 databaseCode: BENPR dateStart: 20100301 customDbUrl: http://www.proquest.com/pqcentral?accountid=15518 isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.proquest.com/central omitProxy: true ssIdentifier: ssj0000651486 providerName: ProQuest |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfZ3Lb9NAEIdHJRGIC-Ip0kK1QhU3U_xYP5AQcmynMaqdyHGkcrLW-ygvOU0Ion8-sxsnwIWjtdYe1rsz32-8MwNwJqQbUBFQK-SOZ3mCSktjhBUphAXFWp-FOhu5KP3p0vt4Ra-OoNjnwuhrlXubaAy1WHEdIz_HfYbSwA29DzdrSzeN0j9X9x00WN9ZQbw3FcbuwNDRTZUHMBxn5bw6BF3Q3yL-m4wjraTDIKD34Ewr18iPzr-ac_fmMNQX-NQlUD1deuHzqrteo0P5B0bv_mKdYt31X15p8hAe9DhJ4t33fwRHsnsMowJJeLUxAXPymiTfvyCWmqcn8K2YpfmCjKv8Ylrrhhukzop5VpnrDySN65jEaGCL_NIEr4hJQiDJ5WyZfiLJrExzk3dM8vwdyYt5nNQLgq9VcV4u6llVEFSVWRIv6ry8eArLSVYnU6tvuGBx5JitRSkT3KEOt_2WKi5C1_W5bQdMvLVbESDbSRYqJBg70MJF-FFrsyhiyDyRxwPlPoNBt-rkcyCOzzi6R9batkI_KUKuZOu7CsVviAgpR3B8WM_mZldYo0FWC7QeGsHJfoGb_kj9aA4bYASv-jX_M7gR69vbtpEGZ3QRseP_TnEC93exYX1X7AUMtpuf8iXCxbY9hWE8TseT037r_Aa-ysWD |
linkProvider | ProQuest |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3LctMwFL1T0uGx4c2QloeGKd05xW-bGRaOnTaicdJJnE5hY2RJLlDGadJ0WvgnfoVv4kpxwmPBrguWHnm0kK50zrm6D4AtIW3fFb5rBNxyDEe40lA0wghLJAslKzwWqGzktO91x87bI_doDb4vc2FUWOXyTtQXtZhw5SPfQTtDaWAHTh1AuS-_XqA8O3tDE9zLl5a128nirlF3EDA4AvPccF0muOVa3PQKt-QisG2Pm6bPxCuzED6SFcmCEiHZ9BUTF15YmCwMGYJ46HC_tHHe7dOpoZpUqcfcumPHNVgP1HttA9bbh-33hyunDuI5ygud0aSUeuD77g3YUso49MKdz_pct1ZDdQFRVWLVUaUdPk6q4ykC1h9k9_oFq0pWHf-Gert34MdyvRbBLiet83nR4t_-KiX53yzoXbhd828SLQ7MPViT1X1opigdJjP9wkC2SfzlE_J4_fUATtJBQkekPaR73Ux1KCFZJz3oDHW8CEmiLCIRIlJKe9rbR3TWBol7g3HyjsSDfkJ1ojah9DWh6UEUZyOCvw0j2h9lg2FKUIZ34miU0f7eQxhfyXI8gkY1qeRjIJbHOPIJVphmicRCBLyUhWeXpq1yhz3ZhI2VgeSni0okOZJbXwnIJmwu9ziv76CzfLXBTXhRG9GvwZmYXl4WudT8T1Vd2_jnFM_hZjdLe3mP9vc34dbCsa4C7Z5AYz47l0-Rmc2LZ_V5IPDhqo3oJ23ePV8 |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1bb9MwFLbGJiZeuCO6cbHQ4C0tuTkJEkJp0q5mTVq16TR4CY4dDxhK167TBv-Mv8Kv4TiXcnngbQ88Ro4s2T7H5_uOzwWhPZGbji0cW3O5YWmWsHNNwQjNkwAWJMsIc1U2chSTwcx6e2QfbaDvTS6MCqts7sTyohZzrnzkHZAzoAama3VkHRUxDvtvTheaaiClHlqbbhqVhBzkXy-AvZ29piEc9XPD6PeSYKDVDQY0DnZ7pdk2E9ywDa6TzJZcuKZJuK47TLzUM-EAlsmZK8Fi644C6oJ4mc48j4GN9yzuSBPmvYa2XOJYoFBb3cPu-8O1gwdsO1CNMrtJsXbXcexttKdYske8zudSx9vrobqYqCq3aqkyDx_nxfECjNcfwPf6BSskK45_s4D9W-hHs3dV4MtJ-3yVtfm3v8pK_pebexvdrHE59itFuoM28uIuakVAKebL8uUBv8DBl0-A78uve-gkGoV0irsTuj9IVOcSnPSicW9SxpHg0E987IOliuiw9ALiMpsDB8PRLHyHg1Ec0jKBG1P6CtNo7AfJFMNvE5_G02Q0iTDQ817gTxMa799HsytZ-wO0WcyL_CHCBmEccAbLdF0C4BAul3lGTKmbKqeY5C20sxaW9LSqUJIC6HUUsWyh3ea80_puOkvXh91Cz2qB-jW4FIvLyyzNS1yoqrHt_HOKp2gbJCUd0vhgF92o_O0q_u4R2lwtz_PHANhW2ZNaNTD6cNUC8xNZokYv |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=MODIS+BRIGHTNESS+TEMPERATURE+DATA+ASSIMILATION+UNDER+CLOUDY+CONDITIONS+%E2%85%A1%EF%BC%9A+IMPACTS+ON+RAINSTORM+FORECASTING&rft.jtitle=%E7%83%AD%E5%B8%A6%E6%B0%94%E8%B1%A1%E5%AD%A6%E6%8A%A5%EF%BC%9A%E8%8B%B1%E6%96%87%E7%89%88&rft.au=%E4%B8%81%E4%BC%9F%E9%92%B0+%E4%B8%87%E9%BD%90%E6%9E%97+%E9%BB%84%E7%87%95%E7%87%95+%E9%99%88%E5%AD%90%E9%80%9A+%E5%BC%A0%E8%AF%9A%E5%BF%A0&rft.date=2011-09-01&rft.issn=1006-8775&rft.volume=17&rft.issue=3&rft.spage=221&rft.epage=230&rft_id=info:doi/10.3969%2Fj.issn.1006-8775.2011.03.004&rft.externalDocID=39276428 |
thumbnail_s | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fimage.cqvip.com%2Fvip1000%2Fqk%2F85390X%2F85390X.jpg http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.wanfangdata.com.cn%2Fimages%2FPeriodicalImages%2Frdqxxb-e%2Frdqxxb-e.jpg |