数据集描述信息.

1、数据集描述信息数据集名称中文名称全球1 x 1度区域海温30年气候月平均英文名称数据集代码T8004-2/ DS010-6主题自由关键词海温学科主题词主题词主题词表描述The monthly optimum interpolation(01) fieldsare derived by a linearinterpolation of the weekly OI fields to daily fields then averaging the daily values over a month. The monthly fields are inthe same format and spat

2、ialresolution 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 satelliteobservations were obtained from operationaldata produced by the NationalEnvironmental Satellite, Data and Information Service (NESDIS).During the period 1981-1989, the in situ

5、 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. Thesatellitedata were obtained from analyses of NESDIS data produced at theUniversity of Miami's Rose

6、ntiel 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 interpolationto produce a complete gridfor possible interpolation. The ocean and land areas are defined by a land sea mask.类型02数据量存储量1

7、9.9MB记录数数据来源NCAR DS277.0数据集提供者134111更新频率01数据集时间创建时间1995-01-01最近修改时间2002-12-31发布时间语种ZH字符集URL离线媒体关联数据关联数据集名称集关联类型关联URL地址观测时次空间编排方式（包括：空间分辨 率、空间编排方式、坐标系）经纬度网格分辨率：1 °x 1 °经向：从179.5 ° W佝东排到179.5 ° E共360点纬向：从89.5 ° S向北排到89.5 ° N共180个点。网格点数：360 X 180 = 64800注意：海表温度为1°X 1&

8、#176;,经纬度网格内的区域平均值，上面给岀的起始经纬度值是1 °X 1°经纬度网格区域中心点的经纬度值垂直层统计特征气候月平均要素参数要素要素名称海温表名称缩写度要素编码计量单位层次类型层次值网格类型经纬度样本类型统计特征气候月平均数据集范学科范围一级分类170围信息二级分类170.15时间范围时间点日期时间段开始时间日期1981.11结束时间日期1997.12空间范围地理名称行政区域名称地理区域名称经纬度范围点范围经度纬度平面范围东部经度-179.5西部经度179.5南部纬度-89.5北部纬度89.5范围描述地理标识数数据质量状况据质量信息志 据 数数据集*IM,集分

9、发信息意 数 参88,1X3 AAIM*月舸 *,*, 型型 整整3为 月 如库称 名 人 个真 传L RU时 r 22元时 据 数 元数据间参考信息称 名 人 个真 传L RU时22附录: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 record. The tablebelow shows the me

10、aning of the header record variables for each ofthe three SST data products.IYRST IMST IDSTIYREND IMEND IDENDNDAYS INDEXWEEKL Y (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/mnNote: numeric constants denote fixed place-holder value

11、sFollowing 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:SST(1,1)= 179.5W, 89.5SSST(1,2)= 179.5W, 88.5SSST(2,1)= 178.5W, 89.

12、5SSST(360,180) = 179.5E, 89.5NNOTES:1) all values less than or equal to -1.78 C are ice2) a land/sea mask should be used to mask out OI SST analyzed valuesnot located in the ocean, e.g. program ls.f and data file ls.datThe monthly optimum interpolation (OI) fields are derived by a linear interpolati

13、on 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 spatial 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 satellit

14、e SST's plus SST's simulated by sea-ice cover. Before the analysis is computed, the satellite data is adjusted for biases using the 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 impro

15、ves the large scale accuracy of the OI. Examples of the effect of recent corrections is given by Reynolds (1993).For the more recent period, 1990-present, the in situ data were obtained from radio messages carried on the Global Telecommunication System. The satellite observations were obtained from

16、operational data produced by the National Environmental Satellite, Data and Information Service (NESDIS).During the period 1981-1989, the in 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

17、) consist of logbook and radio reports. The satellite data were obtained from analyses of NESDIS data produced at the University of Miami'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

18、 by a Cressman interpolation to produce a complete grid for possible interpolation. The ocean and land areas are defined by a land sea mask.REFERENCESReynolds, R. W., 1988: A real-time global sea surface temperature analysis. J. Climate, 1, 75-86.Reynolds, R. W., 1993: Impact of Mount Pinatubo aeros

19、ols 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. Climate

20、, 7, 929-948.Slutz, R. J., S. J. Lubker, J. D. Hiscox, S. D. Woodruff, R. L.Jenne, D. H. Joseph, P. M. Steuer, J. D. Elms, 1985:Comprehensive Ocean-Atmosphere Data Set: Release 1. NOAA Environmental Research Laboratory, Boulder, CO, 268 pp.Woodruff, S.D., S. J. Lubker, K. Wolter, S.J. Worley, and J.

21、D. Elms,1993: Comprehensive Ocean-Atmosphere Data Set (COADS) Release 1a: 1980-1992. Earth System Monitor, V ol. 4, No. 1, September 1993, NOAA.Richard W. Reynolds(INTERNET: )Diane C. Stokes(INTERNET: )Climate Modeling Branch W/NP24Environmental Mode

22、ling CenterNational Centers for Environmental PredictionWorld Weather Building, Room 8075200 Auth RoadCamp Springs, MD 20746 USAPHONE: (301) 763-8396FAX:(301) 763-8125AbstractIn response to the development of a new higher resolution sea surface temperature (SST) analysis at the National Meteorologic

23、al Center (NMC), a new monthly 1-degree global sea surface temperature climatology was constructed from two intermediate climatologies: the 2-degree SST climatology presently used at NMC and a 1-degree SST climatology derived from the new analysis. The 2-degree SST climatology used a 30-year 1950-79

24、 base period between roughly 40S and 60N based on in situ (ship and buoy) SST data supplemented by 4 years (1982-85) of satellite SST retrievals. The 1-degree SST climatology was based on monthly analyses using in situ SST data, satellite SST retrievals, and sea-ice coverage data over a 12-year peri

25、od (1982-93). The final climatology was combined from these two products so that a 1-degree resolution was maintained and the base period was adjusted to the 1950-79 period wherever possible (approximately 40S and 60N). Compared to the 2-degree climatology, the 1-degree climatology resolves equatori

26、al upwelling and fronts much better. This leads to a better matching of the scales of the new analysis and climatology. In addition, because the magnitudes of large-scale features are consistently maintained in both the older 2-degree and the new 1-degree climatologies, climate monitoring of large-s

27、cale anomalies will be minimally affected by the analysis change. The use of 12 years of satellite SST retrievals makes this new climatology useful for many additional purposes because its effective resolution actually approaches 1-degree everywhere over the global ocean and because the mean SST values are more accurate south of 40S than climatologies without these data.Reynolds, R. W. and T. M. Smith, 1994