Global Precipitation Measurement (GPM) is an international satellite mission to provide next-generation observations of rain and snow worldwide every three hours. The Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified algorithm that provides rainfall estimates combining data from all passive-microwave instruments in the GPM Constellation.
This algorithm is intended to intercalibrate, merge, and interpolate all satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, precipitation gauge analyses, and potentially other precipitation estimators at fine time and space scales for the TRMM and GPM eras over the entire globe. The system is run several times for each observation time, first giving a quick estimate and successively providing better estimates as more data arrive. The final step uses monthly gauge data to create research-level products. See IMERG Technical Documentation for more details on the algorithm.
Documentation:
- Algorithm Theoretical Basis Document
- IMERG Quality Index
- Caveats for IMERG extension into TRMM era
- IMERG Technical Documentation
- Release notes; New Morphing algorithm
- Remote-Sensing Reflectance
- Anomalies
This collection contains provisional products that are regularly replaced with updated versions when the data become available. The products are marked with a metadata property called 'status'. When a product is initially made available, the property value is 'provisional'. Once a provisional product has been updated with the final version, this value is updated to 'permanent'.
This collection contains data from:
- GPM_3IMERGHH_V06 doi:10.5067/GPM/IMERG/3B-HH-L/06
- GPM_3IMERGHH_06 doi:10.5067/GPM/IMERG/3B-HH/06
全球降水测量(GPM)是一项国际卫星任务,每三小时对全世界的雨雪进行一次新一代的观测。全球降水测量的综合多卫星检索(IMERG)是一种统一的算法,提供来自全球降水测量星座中所有无源微波仪器的数据的降水估计。
该算法旨在对所有卫星微波降水估计值进行相互校准、合并和内插,同时还包括微波校准的红外(IR)卫星估计值、降水仪分析,以及可能的其他降水估计值,其时间和空间尺度为TRMM和GPM时代的全球范围。该系统对每个观测时间都要运行数次,首先给出一个快速估计,随着更多数据的到来,陆续提供更好的估计。最后一步使用月度测绘数据来创建研究级产品。关于算法的更多细节,见IMERG技术文件。
文件。
算法的理论基础文件
IMERG质量指数
IMERG扩展到TRMM时代的注意事项
IMERG技术文档
发布说明;新的变形算法
遥感反射率
异常情况
这个集合包含了临时产品,当数据可用时,会定期用更新的版本替换。这些产品都标有一个名为 "状态 "的元数据属性。当一个产品最初被提供时,其属性值为 "临时"。一旦一个临时产品被更新为最终版本,这个值就会被更新为 "永久"。
这个集合包含的数据来自。
GPM_3IMERGHH_V06 doi:10.5067/GPM/IMERG/3B-HH-L/06
GPM_3IMERGHH_06 doi:10.5067/GPM/IMERG/3B-HH/06
Dataset Availability
2000-06-01T00:00:00 - 2021-09-28T00:00:00
Dataset Provider
NASA GES DISC at NASA Goddard Space Flight Center
Collection Snippet
ee.ImageCollection("NASA/GPM_L3/IMERG_V06")
Dataset Availability
2000-06-01T00:00:00 - 2021-09-28T00:00:00
Dataset Provider
NASA GES DISC at NASA Goddard Space Flight Center
Collection Snippet
Copied
ee.ImageCollection("NASA/GPM_L3/IMERG_V06")
Tags
precipitationgeophysicalweatherclimatenasagpmimergjaxahalf-hourly
DESCRIPTIONBANDSTERMS OF USECITATIONSDOIS
Resolution
11132 meters
Bands Table
Name | Description | Min* | Max* | Units |
HQobservationTime | PMW source time | 0 | 29 | min. into half hour |
HQprecipSource | PMW source sensor identifier | |||
HQprecipSource Bitmask |
|
|||
HQprecipitation | merged PMW precipitation | 0 | 120 | mm/hr |
IRkalmanFilterWeight | Kalman filter weight for IR | 0 | 100 | % |
IRprecipitation | IR precipitation | 0 | 79.5 | mm/hr |
precipitationCal | snapshot precipitation - calibrated | 0 | 174 | mm/hr |
precipitationUncal | snapshot precipitation - uncalibrated | 0 | 120 | mm/hr |
probabilityLiquidPrecipitation | probability of liquid precipitation phase | 0 | 100 | % |
randomError | calibrated-precipitation random error | 0.24 | 250 | mm/hr |
* = Values are estimated
引用:
'Huffman, G.J., E.F. Stocker, D.T. Bolvin, E.J. Nelkin, Jackson Tan (2019), GPM IMERG Final Precipitation L3 1 month 0.1 degree x 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], 10.5067/GPM/IMERG/3B-MONTH/06'
代码:
// GPM V6 30 minute data around hurricane Dorian for a single day. var range = ee.Date('2019-09-03').getRange('day'); var dataset = ee.ImageCollection('NASA/GPM_L3/IMERG_V06') .filter(ee.Filter.date(range)); // Select the max precipitation and mask out low precipitation values. var precipitation = dataset.select('precipitationCal').max(); var mask = precipitation.gt(0.5); var precipitation = precipitation.updateMask(mask); var palette = [ '000096','0064ff', '00b4ff', '33db80', '9beb4a', 'ffeb00', 'ffb300', 'ff6400', 'eb1e00', 'af0000' ]; var precipitationVis = {min: 0.0, max: 15.0, palette: palette}; Map.addLayer(precipitation, precipitationVis, 'Precipitation'); Map.setCenter(-76, 33, 3);