前往小程序,Get更优阅读体验!
立即前往
首页
学习
活动
专区
工具
TVP
发布
社区首页 >专栏 >Google Earth Engine——TRMM/34B2产品包含一个网格化的、经TRMM调整的、合并的红外降水(毫米/小时)和降水误差的有效值估计,时间分辨率为3小时,空间分辨率为0.25度。

Google Earth Engine——TRMM/34B2产品包含一个网格化的、经TRMM调整的、合并的红外降水(毫米/小时)和降水误差的有效值估计,时间分辨率为3小时,空间分辨率为0.25度。

作者头像
此星光明
发布2024-02-02 12:23:54
1220
发布2024-02-02 12:23:54
举报

The Tropical Rainfall Measuring Mission (TRMM) is a joint mission between NASA and the Japan Aerospace Exploration Agency (JAXA) designed to monitor and study tropical rainfall. The 34B2 product contains a gridded, TRMM-adjusted, merged infrared precipitation (mm/hr) and RMS precipitation-error estimate, with a 3-hour temporal resolution and a 0.25 degree spatial resolution.

See the algorithm description and the file specification for details.

热带降水测量任务(TRMM)是美国航天局和日本宇宙航空研究开发机构(JAXA)的一项联合任务,旨在监测和研究热带降水。34B2产品包含一个网格化的、经TRMM调整的、合并的红外降水(毫米/小时)和降水误差的有效值估计,时间分辨率为3小时,空间分辨率为0.25度。

详见算法说明和文件说明。

文件。

PI文件

TRMM产品的文件规范

TRMM第6和第7版之间的比较

自述文件

本产品中使用的TMPA算法的细节

TRMM的数据差距

从TMPA到IMERG的过渡

Dataset Availability

1998-01-01T00:00:00 - 2019-12-31T00:00:00

Dataset Provider

NASA GES DISC at NASA Goddard Space Flight Center

Collection Snippet

ee.ImageCollection("TRMM/3B42")

Resolution

27830 meters

Bands Table

Name

Description

Min

Max

Units

precipitation

Merged microwave/IR precipitation estimate

0

100

mm/hr

relativeError

Merged microwave/IR precipitation random error estimate

0

100

mm/hr

satPrecipitationSource

Flag to show source of data

satPrecipitationSource Bitmask

Bits 0-5: Source 0: No observation1: AMSU2: TMI3: AMSR4: SSMI5: SSMI/S6: MHS7: TCI30: AMSU/MHS average31: Conical scanner average50: IR

HQprecipitation

Pre-gauge-adjusted microwave precipitation estimate

0

100

mm/hr

IRprecipitation

Pre-gauge-adjusted infrared precipitation estimate

0

100

mm/hr

satObservationTime

Satellite observation time minus the time of the granule. In case of overlapping satellite observations, the two or more observation times are equal-weighting averaged.

-90

90

Minutes

  • Bits 0-5: Source
    • 0: No observation
    • 1: AMSU
    • 2: TMI
    • 3: AMSR
    • 4: SSMI
    • 5: SSMI/S
    • 6: MHS
    • 7: TCI
    • 30: AMSU/MHS average
    • 31: Conical scanner average
    • 50: IR

HQprecipitationPre-gauge-adjusted microwave precipitation estimate0100mm/hrIRprecipitationPre-gauge-adjusted infrared precipitation estimate0100mm/hrsatObservationTimeSatellite observation time minus the time of the granule. In case of overlapping satellite observations, the two or more observation times are equal-weighting averaged.-9090Minutes

使用说明:

This dataset is in the public domain and is available without restriction on use and distribution. See NASA's Earth Science Data & Information Policy for additional information.

引用:

Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, P. Arkin, E.J. Nelkin, 2003: The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present). J. Hydrometeor., 4(6), 1147-1167.

Huffman, G.J., 1997: Estimates of Root-Mean-Square Random Error for Finite Samples of Estimated Precipitation, J. Appl. Meteor., 1191-1201.

Huffman, G.J., 2012: Algorithm Theoretical Basis Document (ATBD) Version 3.0 for the NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (I-MERG). GPM Project, Greenbelt, MD, 29 pp.

Huffman, G.J., R.F. Adler, P. Arkin, A. Chang, R. Ferraro, A. Gruber, J. Janowiak, A. McNab, B. Rudolph, and U. Schneider, 1997: The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset, Bul. Amer. Meteor. Soc., 78, 5-20.

Huffman, G.J., R.F. Adler, D.T. Bolvin, G. Gu, E.J. Nelkin, K.P. Bowman, Y. Hong, E.F. Stocker, D.B. Wolff, 2007: The TRMM Multi-satellite Precipitation Analysis: Quasi-Global, Multi-Year, Combined-Sensor Precipitation Estimates at Fine Scale. J. Hydrometeor., 8(1), 38-55.

Huffman, G.J., R.F. Adler, M. Morrissey, D.T. Bolvin, S. Curtis, R. Joyce, B McGavock, J. Susskind, 2001: Global Precipitation at One-Degree Daily Resolution from Multi-Satellite Observations. J. Hydrometeor., 2(1), 36-50.

Huffman, G.J., R.F. Adler, B. Rudolph, U. Schneider, and P. Keehn, 1995: Global Precipitation Estimates Based on a Technique for Combining Satellite-Based Estimates, Rain Gauge Analysis, and NWP Model Precipitation Information, J. Clim., 8, 1284-1295

代码:

代码语言:javascript
复制
var dataset = ee.ImageCollection('TRMM/3B42')
                  .filter(ee.Filter.date('2018-04-01', '2018-04-10'));
var precipitation =
    dataset.select(['precipitation', 'HQprecipitation', 'IRprecipitation']);
var precipitationVis = {
  min: 0.0,
  max: 12.0,
  gamma: 5.0,
};
Map.setCenter(-79.98, 23.32, 4);
Map.addLayer(precipitation, precipitationVis, 'Precipitation');
本文参与 腾讯云自媒体同步曝光计划,分享自作者个人站点/博客。
原始发表:2024-02-01,如有侵权请联系 cloudcommunity@tencent.com 删除

本文分享自 作者个人站点/博客 前往查看

如有侵权,请联系 cloudcommunity@tencent.com 删除。

本文参与 腾讯云自媒体同步曝光计划  ,欢迎热爱写作的你一起参与!

评论
登录后参与评论
0 条评论
热度
最新
推荐阅读
领券
问题归档专栏文章快讯文章归档关键词归档开发者手册归档开发者手册 Section 归档