The GSMaP_ISRO is a precipitation product that was developed through the Indian Space Research Organisation (ISRO) - Japan Aerospace Exploration Agency (JAXA) Implementation of Agreement (IA) specifically for the Indian subcontinent. It is currently available from March 2000 to December 2022 and offers a horizontal resolution of 0.1°X 0.1° on a latitude/longitude grid with a temporal resolution of 1 hour. The dataset is based on the Global Satellite Mapping of Precipitation (GSMaP) algorithm (Kubota et al. 2020; Kumar et al. 2021, 2022) with Indian Meteorological Department (IMD) gauge correction, and is a specialized product that focuses on the Indian landmass.
The GSMaP algorithm, designed by the JAXA, is instrumental in creating a comprehensive view of precipitation using microwave radiometers and cloud moving data from Geostationary Infrared (IR) technology. The algorithm is separated into three primary categories for effective measurement: the microwave imager, microwave sounder, and microwave-infrared (MVK) combined (Mega et al. 2019). A detailed verification of GSMaP_ISRO for the Indian summer monsoon periods of 2000-2020 against ground, satellite and various merge rainfall products is presented in Kumar et al. (2022).
The GSMaP algorithm, designed by the JAXA, is instrumental in creating a comprehensive view of precipitation using microwave radiometers and cloud moving data from Geostationary Infrared (IR) technology. The algorithm is separated into three primary categories for effective measurement: the microwave imager, microwave sounder, and microwave-infrared (MVK) combined (Mega et al. 2019). A detailed verification of GSMaP_ISRO for the Indian summer monsoon periods of 2000-2020 against ground, satellite and various merge rainfall products is presented in Kumar et al. (2022).
Data Access
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Data Version
- Version 1.0 (beta)
Data Sources
- GSMaP_MVK product, NOAA Climate Prediction Center (CPC) rainfall analysis, CPC Infrared brightness temperature, IMD gridded rain (0.25 degree), etc.
Processing Steps
-
-For gauge adjustment, the software used was JAXA MCD_V05.02, based upon Mega et al. (2019).
-Merging NOAA CPC and Indian gauges was accomplished using Matlab software.
-The algorithms pertaining to GSMaP_ISRO are provided in Kumar et al. (2022) in detail.
References
- Kubota, T., Aonashi, K., Ushio, T., Shige, S., Takayabu, Y. N., Kachi, M., and Oki, R. (2020). Global Satellite Mapping of Precipitation (GSMaP) products in the GPM era. Satellite Precipitation Measurement: Volume 1, 355-373.
Kumar, P., Gairola, R., Kubota, T., and Kishtawal, C. (2021). Hybrid assimilation of satellite rainfall product with high density gauge network to improve daily estimation: A case of Karnataka, India. Journal of the Meteorological Society of Japan. Ser. II, 99(3), 741-763.
Kumar, P., Varma, A. K., Kubota, T., Yamaji, M., Tashima, T., Mega, T., and Ushio, T. (2022). Long-Term High-Resolution Gauge Adjusted Satellite Rainfall Product Over India. Earth and Space Science, 9(12), e2022EA002595.
Mega, T., Ushio, T., Matsuda, T., Kubota, T., Kachi, M., and Oki, R. (2019) Gauge-Adjusted Global Satellite Mapping of Precipitation, IEEE Trans. Geosci. Remote Sens, 57, 4, 1928-1935.
Derivation Techniques and Algorithm
- The manuscript titled "Long-Term High-Resolution Gauge Adjusted Satellite Rainfall Product Over India" provides a description.
Limitations
- The number of gauge stations within a NOAA CPC pixel of 0.5 degree impacts the accuracy of the gauge-adjusted rainfall.
Known problems with data
- No known issues at this time.
File Naming Convention
- HDF5 file:
- Sample name : GPMMRG_MAP_YYMMDDHH00_H_L3S_MCH_03F.h5
- YY - Year
- MM - Month
- DD - Day
- HH - Hour
MetaData
| Sr. No | Core Metadata Elements | Definition |
| 1 | Metadata language | English |
| 2 | Metadata Contact | MOSDAC |
| 3 | Metadata date | November, 2023 |
| 4 | Data Lineage or Quality | IMD gauge adjusted GSMaP_ISRO Rain |
| 5 | Title | GSMaP_ISRO Rain |
| 6 | Abstract | The GSMaP_ISRO rain data has been derived through the IMD gauge based gridded rain & NOAA CPC gauge analysis adjustment of the GSMaP_MVK rain product. It offers high-quality rainfall information with excellent spatiotemporal resolution, covering a range spanning from March 2000 to December 2022. It has been developed through the ISRO-JAXA Implementation of Agreement (IA). This product provides a lat/long grid with a 0.1° X 0.1° horizontal resolution, along with hourly temporal resolution. |
| 6a | Developer | Prashant Kumar, Atul K. Varma, Takuji Kubota, Moeka Yamaji, Tomoko Tashima, Tomoaki Mega, Tomoo Ushio |
| 7 | Dataset Contact | Dr. Prashant Kumar, ASD/AOSG/EPSA Space Applications Centre, ISRO Ahmedabad-380015 prashant22@sac.isro.gov.in |
| 8 | Update Frequency | 23 years of global GSMaP_ISRO rain. Further data will be added intermittently. |
| 9 | Access Rights or Restriction | Open Access |
| 10 | Spatial Resolution | 0.1 degree |
| 11 | Language | English |
| 12 | Topic Category | Gauge adjusted satellite rainfall |
| 13 | Keywords | GSMaP_MVK, NOAA CPC rainfall analysis, CPC Infrared brightness temperature, IMD gridded rain (0.25 degree). |
| 14 | Date or period | March 2000 to December 2022 |
| 15 | Responsible Party | Dr. Prashant Kumar, ASD/AOSG/EPSA, Space Applications Centre, ISRO Ahmedabad-380015, India |
| 16 | Organization | Space Applications Centre (ISRO), Ahmedabad, India |
| 16a | Org. role | Development of high spatio-temporal resolution gauge adjusted satellite rainfall |
| 16b | Individual name |
Dr. Prashant Kumar, ASD/AOSG/EPSA, |
| 16c | Position | Scientist/Engineer - SF |
| 17 | Geographic Extent | Global |
| 18 | Geographic name, geographic Identifier | Global |
| 19 | Bounding box | lat_min: -90 , lat_max: 90, lon_min: 0, lon_max: 360 |
| 20 | Temporal Extent | March 2000 to December 2022 |
| 21 | Access Rights or Restrictions | Open Access |
| 22 | Distribution Information | Online download of data files in HDF5 format |
| 23 | Processing Level | Level 3 (Gauge adjusted satellite rainfall product) |
| 24 | Reference System | Datum: WGS84 |
