數(shù)據(jù)集描述信息

1、數(shù)據(jù)集描述信息數(shù)據(jù)集名稱中文名稱全球1×1度區(qū)域海溫月平均英文名稱數(shù)據(jù)集代碼T8107/DS010-4主題自由關(guān)鍵詞海溫學(xué)科主題詞主題詞主題詞表描述The monthly optimum interpolation (OI) fields are derived by a linear interpolation of the weekly OI fields to daily fields then averaging the daily values over a month. The monthly fields are in the same format and spati

2、al resolution as the weekly fields.The OI sea surface temperature (SST) analysis is produced weekly on a one-degree grid. The analysis uses in situ and satellite SST's plus SST's simulated by sea-ice cover. Before the analysis is computed, the satellite data is adjusted for biases using the

3、method of Reynolds (1988) and Reynolds and Marsico (1993). A description of the OI analysis can be found in Reynolds and Smith (1994). The bias correction improves the large scale accuracy of the OI. Examples of the effect of recent corrections is given by Reynolds (1993).For the more recent period,

4、 1990-present, the in situ data were obtained from radio messages carried on the Global Telecommunication System. The satellite observations were obtained from operational data produced by the National Environmental Satellite, Data and Information Service (NESDIS). During the period 1981-1989, the i

5、n situ data were obtained from the Comprehensive Ocean Atmosphere Data Set (COADS) for the 1980s. These data (see Slutz, et al., 1985, and Woodruff, et al., 1993) consist of logbook and radio reports. The satellite data were obtained from analyses of NESDIS data produced at the University of Miami&#

6、39;s Rosentiel School of Marine and Atmospheric Sciences. The OI analysis is done over all ocean areas. There is no analysis over land. The land values are filled by a Cressman interpolation to produce a complete grid for possible interpolation. The ocean and land areas are defined by a land sea mas

7、k. 類型02數(shù)據(jù)量存儲量24.1MB記錄數(shù)數(shù)據(jù)來源NCAR DS277.0數(shù)據(jù)集提供者134111更新頻率01數(shù)據(jù)集時間創(chuàng)建時間1995-01-01最近修改時間2002-12-31發(fā)布時間語種ZH字符集URL離線媒體關(guān)聯(lián)數(shù)據(jù)集關(guān)聯(lián)數(shù)據(jù)集名稱關(guān)聯(lián)類型關(guān)聯(lián)URL地址觀測時次空間編排方式（包括：空間分辨率、空間編排方式、坐標(biāo)系）經(jīng)緯度網(wǎng)格分辨率：1°×1°經(jīng)向：從179.5°W向東排到179.5°E共360點(diǎn)緯向：從89.5°S向北排到89.5°N共180個點(diǎn)。網(wǎng)格點(diǎn)數(shù)：360×18064800注意：海表溫度為1

8、76;×1°，經(jīng)緯度網(wǎng)格內(nèi)的區(qū)域平均值，上面給出的起始經(jīng)緯度值是 1°×1°經(jīng)緯度網(wǎng)格區(qū)域中心點(diǎn)的經(jīng)緯度值垂直層統(tǒng)計(jì)特征月平均要素參數(shù)表要素要素名稱海溫名稱縮寫要素編碼計(jì)量單位度層次類型層次值網(wǎng)格類型經(jīng)緯度樣本類型統(tǒng)計(jì)特征月平均數(shù)據(jù)集范圍信息學(xué)科范圍一級分類170二級分類170.15時間范圍時間點(diǎn)日期時間段開始時間日期1981.11結(jié)束時間日期2002.1空間范圍地理名稱行政區(qū)域名稱地理區(qū)域名稱經(jīng)緯度范圍點(diǎn)范圍經(jīng)度緯度平面范圍東部經(jīng)度-179.5西部經(jīng)度179.5南部緯度-89.5北部緯度89.5范圍描述地理標(biāo)識數(shù)據(jù)質(zhì)量信息數(shù)據(jù)質(zhì)量狀況數(shù)據(jù)志數(shù)

9、據(jù)集分發(fā)信息數(shù)據(jù)的傳輸格式技術(shù)要求調(diào)用程序：CALL SSTMNLY（AA，IY，IM，*）參數(shù)意義：AA 實(shí)型數(shù)組 360×180，程序返回時為所調(diào)資料 IY 整型量，年 IM 整型量，月 * 整型量，所調(diào)資料沒找到時，按此標(biāo)號返回編譯時需連接 -ldatabank 庫如年為 13 則為陸海標(biāo)志數(shù)據(jù)提供方式訪問限制使用約束收費(fèi)策略權(quán)限管理訪問時間聯(lián)系信息聯(lián)系人名稱個人名稱組織名稱中國科學(xué)院大氣物理研究所職稱名稱聯(lián)系地址通訊地址北京市9804信箱郵政編碼100029其他聯(lián)系方式傳真電子郵件URL聯(lián)系時間24小時元數(shù)據(jù)參考信息元數(shù)據(jù)時間元數(shù)據(jù)創(chuàng)建時間2003

10、-8最近修改時間2003-8聯(lián)系信息聯(lián)系人名稱個人名稱組織名稱中國科學(xué)院大氣物理研究所職稱名稱聯(lián)系地址通訊地址北京市9804信箱100029郵政編碼其他聯(lián)系方式傳真電子郵件URL聯(lián)系時間24小時元數(shù)據(jù)標(biāo)準(zhǔn)名稱元數(shù)據(jù)標(biāo)準(zhǔn)版本 附 錄: Program to read WEEKLY, MONTHLY compocp site, and CLIMATOLOGY grids. All grids are 1x1, (360,180), (longitude,latitude). Each global grid is preceeded by a single header

11、 record. The table below shows the meaning of the header record variables for each of the three SST data products. IYRST IMST IDST IYREND IMEND IDEND NDAYS INDEX - - - - WEEKLY (start date, yr/mn/day) (end date, yr/mn/day) 7 ? MONTHLY (yr/mn/1) (yr/mn/day) days/mn ? CLIM. (99/mn/1) (99/mn/day) days/

12、mn 0 - Note: numeric constants denote fixed place-holder values Following the header are integer SST values in degrees C time 100, with format (20I4). These data are read into integer array ISST, converted to degree C, and placed into real array SST. The geo-location of the SST array elements are: S

13、ST(1,1) = 179.5W, 89.5S SST(1,2) = 179.5W, 88.5S SST(2,1) = 178.5W, 89.5S SST(360,180) = 179.5E, 89.5N NOTES: 1) all values less than or equal to -1.78 C are ice 2) a land/sea mask should be used to mask out OI SST analyzed values not located in the ocean, e.g. program ls.f and data file ls.datThe m

14、onthly optimum interpolation (OI) fields are derived by a linearinterpolation of the weekly OI fields to daily fields then averagingthe daily values over a month. The monthly fields are in the sameformat and spatial resolution as the weekly fields.The OI sea surface temperature (SST) analysis is pro

15、duced weekly on aone-degree grid. The analysis uses in situ and satellite SST's plusSST's simulated by sea-ice cover. Before the analysis is computed, thesatellite data is adjusted for biases using the method of Reynolds(1988) and Reynolds and Marsico (1993). A description of the OIanalysis

16、can be found in Reynolds and Smith (1994). The bias correctionimproves the large scale accuracy of the OI. Examples of the effect ofrecent corrections is given by Reynolds (1993).For the more recent period, 1990-present, the in situ data wereobtained from radio messages carried on the Global Telecom

17、municationSystem. The satellite observations were obtained from operational dataproduced by the National Environmental Satellite, Data and InformationService (NESDIS). During the period 1981-1989, the in situ data were obtained from theComprehensive Ocean Atmosphere Data Set (COADS) for the 1980s. T

18、hesedata (see Slutz, et al., 1985, and Woodruff, et al., 1993) consist oflogbook and radio reports. The satellite data were obtained fromanalyses of NESDIS data produced at the University of Miami's RosentielSchool of Marine and Atmospheric Sciences. The OI analysis is done over all ocean areas.

19、 There is no analysisover land. The land values are filled by a Cressman interpolation toproduce a complete grid for possible interpolation. The ocean and landareas are defined by a land sea mask. REFERENCESReynolds, R. W., 1988: A real-time global sea surface temperature analysis. J. Climate, 1, 75

20、-86.Reynolds, R. W., 1993: Impact of Mount Pinatubo aerosols on satellite-derived Sea Surface Temperatures. J. Climate, 6, 768-774.Reynolds, R. W. and D. C. Marsico, 1993: An improved real-time global sea surface temperature analysis. J. Climate, 6, 114-119.Reynolds, R. W. and T. M. Smith, 1994: Improved global sea surface temperature analyses. J. Climat