N: 60 S: -60 E: 180 W: -180
Description
TMPA (3B42RT) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG datasets (doi: 10.5067/GPM/IMERG/3B-HH-E/06, 10.5067/GPM/IMERG/3B-HH-L/06).
These data were output from the TRMM Multi-satellite Precipitation Analysis (TMPA), the Near Real-Time (RT) processing stream. The latency was about seven hours from the observation time, although processing issues may delay or prevent this schedule. Users should be mindful that the price for the short latency of these data is the reduced quality as compared to the research quality product.
Each file is a snapshot considered to represent the three-hour period centered on the "nominal" file time. So, e.g., 00 UTC nominally represents the period from 2230 UTC of the previous day to 0130 UTC of the current day. Estimates outside the band 50 degree N-S are considered highly experimental.
GES DISC initially receives these data from the Precipitation Processing System (PPS) in binary format. However, before archiving, the data are scaled to real numbers, and re-arranged to a standard grid so that the first grid cell is at 180W, 60S. Thus formatted, data are stored into CF-1.6 compliant netCDF-4 files and archived. This format is machine-independent, self-explanatory, provides extremely efficient seamless compression, and gives various options for previewing the data without downloading it.
Apart from these technical differences, all other science content details remain the same, and users are strongly encouraged to read the provider's documentation that is linked to from here.
Product Summary
Citation
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
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Documents
READ-ME
GENERAL DOCUMENTATION
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Spatial Downscaling of Satellite-Based Precipitation Data over the Qaidam Basin, China | Wang, Yuanzheng, Yan, Changzhen, Ma, Qimin, Jia, Xiaopeng | Total Surface Precipitation Rate | |
| Flood risk assessment and hydrological simulation in the Upper Krishna River Basin, India | Ande, Ravi, Mehta, Darshan, Maurya, Vandana, Birbal, Prashant, Furze, James N., Verma, Shashikant | Total Surface Precipitation Rate | |
| Performance Evaluation of Four Satellite-based Precipitation Products (SPPs) in Hydrological Modelling Across Five Northern Moroccan Catchments | Et-Takaouy, Chaimaa, Aqnouy, Mourad, Coffin, Richard, En-Nagre, Khalid, Chahid, Morad, Stitou El Messari, Jamal Eddine | Total Surface Precipitation Rate | |
| Limitations of satellite precipitation products in capturing extreme precipitation events: An object-based evaluation over China | Gu, Hongji, Shen, Dingtao, Chen, Jinming, Zhang, Chunxiao, Xiao, Shuting, Yu, Fei | Total Surface Precipitation Rate | |
| Multidimensional evaluation of four high-resolution precipitation products based on REOF zones in the upper and middle Hanjiang River Basin | Bo, Huijuan, Huang, Xiaole, Yang, Shaokang, Luo, Lichuan, Guo, Lingyun, Yue, Juan, Zhang, Ni, Long, Lihua, Pan, Wei, Wei, Chong, Zhang, Yi | Total Surface Precipitation Rate | |
| Dense gauge observations-based evaluation of gridded precipitation in southwest china and its implication for future data development | Zhang, Zhuqing, Zhao, Long, Jiang, Yaozhi, Zhou, Jianhong, Yu, Wenping, Luo, Qi, Zhou, Heng | Total Surface Precipitation Rate | |
| Mass deposition of microbes from wildfire smoke to the sea surface | Yue, Siyao, Cheng, Yafang, Zheng, Lishan, Lai, Senchao, Wang, Shan, Song, Tianli, Li, Linjie, Li, Ping, Zhu, Jialei, Li, Meng, Wei, Lianfang, Ma, Chaoqun, Jin, Rui, Zhang, Yingyi, Sun, Yele, Wang, Zifa, Kawamura, Kimitaka, Liu, CongQiang, Su, Hang, Andreae, Meinrat O., Fu, Pingqing | Total Surface Precipitation Rate | |
| Integrating categorical and standard triple collocation to improve precipitation fusion over the five largest freshwater lakes in China | Li, Lingjie, Tang, Guoqiang, Wang, Yintang, Gao, Rui, Liu, Yong, Zhao, Wenpeng, Chen, Cheng | Total Surface Precipitation Rate | |
| Improvements in Precipitation Product with Newer NASA/GPM IMERG Algorithm on TRMM/TMPA Data During Summer Monsoon Period over India | Reddy, M. Venkatarami, Kumar, K. Niranjan, Mitra, Ashis. K., Amarjyothi, K., Momin, Imranali M., Mohandas, Saji, Prasad, V. S. | Total Surface Precipitation Rate | |
| Evaluating the Hydrological Applicability of Satellite Precipitation Products Using a Differentiable, Physics-Based Hydrological Model in the Xiangjiang River Basin, China | Yan, Shixiong, Jiang, Changbo, Long, Yuannan, Wang, Xinkui | Total Surface Precipitation Rate | |
| Performance Assessment of Multiple Satellite Rainfall Products in the Levant Region | Jayousi, Fakhry, O'Loughlin, Fiachra | Total Surface Precipitation Rate | |
| Land use and climate change exacerbate the root zone maximum water deficit in the Loess Plateau | Zhao, Zikun, Gao, Hongkai, Xi, Qiaojuan, Wang, Yahui, Jia, Xiaoxu, Wu, Pute, Zhuo, La | Total Surface Precipitation Rate | |
| Dual correction of rainfall and root zone soil moisture estimates for improving streamflow simulations | Ramesh, Visweshwaran, Patil, Amol, Ramsankaran, RAAJ | Total Surface Precipitation Rate | |
| Calibration of Near Real-Time Satellite Precipitation Products Using Deep Learning Techniques and Multi-source Data | Hoang-Gia, Anh-Duc, Nguyen, An Hung, Ngo, Truong Xuan, Nguyen, Thanh Thi Nhat | Total Surface Precipitation Rate | |
| Bias Correction Methods Applied to Satellite Rainfall Products over the Western Part of Saudi Arabia | Elsebaie, Ibrahim H., Kawara, Atef Q., Alharbi, Raied, Alnahit, Ali O. | Total Surface Precipitation Rate | |
| Comparison and hydrological evaluation of different precipitation data for a large tropical region: the Blue Nile Basin in Ethiopia | Zargar, Morteza, Bronstert, Axel, Francke, Till, Zimale, Fasikaw A., Worku, Kindie Bitew, Wiegels, Rebecca, Lorenz, Christof, Hageltom, Yasir, Sawadogo, Windmanagda, Kunstmann, Harald | Total Surface Precipitation Rate | |
| Evaluation of the Artificial Neural NetworksDynamic Infrared Rain Rate near Real-Time (PDIR-Now) Satellites Ability to Monitor Annual Maximum Daily Precipitation in Mainland China | Zhu, Yanping, Chang, Gaosong, Zhang, Wenjiang, Guo, Jingyu, Li, Xiaodong | Total Surface Precipitation Rate | |
| Towards More Reliable Gridded Precipitation Estimates: Gauge-Based Multi-Scale Evaluation and Machine Learning Bias Correction | Saghiry, Soumia, Loudyi, Dalila, Laassilia, Oussama, Arshad, Arfan, Dhaouadi, Latifa, Ali, Riaz, Alaoui, Meryem El | Total Surface Precipitation Rate | |
| Understanding the performance of global precipitation products for hydrological modeling in the data-scarce morphologically complex central Himalayan region | Sandilya, Sneha, Singh, Sunayana, Kumar, Sonu, Rajput, Jitendra | Total Surface Precipitation Rate | |
| Impact of satellite precipitation estimation methods on the hydrological response: case study Wadi Nu'man basin, Saudi Arabia | Adem, Esubalew, Elfeki, Amro, Chaabani, Anis, Alwegdani, Abdullah, Hussain, Sajjad, Elhag, Mohamed | Total Surface Precipitation Rate | |
| Multi-Sensor Precipitation Estimation from Space: Data Sources, Methods and Validation | Guo, Ruifang, Fan, Xingwang, Zhou, Han, Liu, Yuanbo | Total Surface Precipitation Rate | |
| Enhancing drought monitoring through spatial downscaling: A geographically weighted regression approach using TRMM 3B43 precipitation in the Urmia Lake Basin | Choursi, Sima Kazempour, Erfanian, Mahdi, Abghari, Hirad, Miryaghoubzadeh, Mirhassan, Javan, Khadijah | Total Surface Precipitation Rate | |
| Development of an R-CLIPER model using GSMaP and TRMM precipitation data for tropical cyclones affecting Vietnam | Thu, Hang Nguyen, Thanh, Nga Pham Thi, Thanh, Hang Vu, Thanh, Ha Pham, Tuan, Long Trinh, Thi, The Doan, Duy, Thuc Tran, Phuong, Hao Nguyen Thi | Total Surface Precipitation Rate | |
| Brazil: Environmentally Integrated Basin Experiments (EIBEX) Driven by Hydrological Change, Sustainable Practices, and Water Security in Brazil | Filho, Otto Correa Rotunno, de Oliveira Nascimento, Nilo, de Araujo, Ligia Maria Nascimento, Rodriguez, Daniel Andres, de Araujo, Afonso Augusto Magalhaes, Fernandes, Nelson Ferreira, de Figueiredo Teixeira, Alexandre Lima, Moreira, Daniel Medeiros, Cancado, Vanessa Lucena, Rodrigues, Nivia Carla, Laender, Felipe, Eleuterio, Julian Cardoso, Silva, Talita, Vincon-Leite, Brigitte | Total Surface Precipitation Rate | |
| An Innovative CorrectionFusion Approach for Multi-Satellite Precipitation Products Conditioned by Gauge Background Fields over the Lancang River Basin | Nan, Linjiang, Yang, Mingxiang, Wang, Hao, Wang, Hejia, Dong, Ningpeng | Total Surface Precipitation Rate |
Variables
The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.
For questions on a specific variable, please use the Earthdata Forum.
| Name Sort descending | Description | Units | Data Type | Fill Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|
| lat | lat | degrees_north | float32 | N/A | N/A | N/A | N/A |
| lon | lon | degrees_east | float32 | N/A | N/A | N/A | N/A |
| precipitation | precipitation | mm/hr | float32 | -99999 | N/A | N/A | N/A |
| precipitation_error | precipitation_error | mm/hr | float32 | -99999 | N/A | N/A | N/A |
| source | source | Index Value | int16 | N/A | N/A | N/A | N/A |
| uncal_precipitation | uncal_precipitation | mm/hr | float32 | -99999 | N/A | N/A | N/A |