N: 50 S: -50 E: 180 W: -180
Description
TMPA (3B42_Daily) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERGDF/DAY/06).
This daily accumulated precipitation product is generated from the research-quality 3-hourly TRMM Multi-Satellite Precipitation Analysis TMPA (3B42). It is produced at the NASA GES DISC, as a value added product. Simple summation of valid retrievals in a grid cell is applied for the data day. The result is given in (mm). The beginning and ending time for every daily granule are listed in the file global attributes, and are taken correspondingly from the first and the last 3-hourly granules participating in the aggregation. Thus the time period covered by one daily granule amounts to 24 hours, which can be inspected in the file global attributes.
Counts of valid retrievals for the day are provided for every variable, making it possible to compute conditional and unconditional mean precipitation for grid cells where less than 8 retrievals for the day are available.
Efforts have been made to make the format of this derived product as similar as possible to the new Global Precipitation Measurement CF-compliant file format.
The information provided here on the TRMM mission, and on the original 3-hr 3B42 product, remain relevant for this derived product. Note, however, this product is in netCDF-4 format.
The following describes the derivation in more details.
The daily accumulation is derived by summing valid retrievals in a grid cell for the data day. Since the 3-hourly source data are in mm/hr, a factor of 3 is applied to the sum. Thus, for every grid cell we have
Pdaily = 3 SUM{Pi 1[Pi valid]}, i=[1,Nf]
Pdaily_cnt = SUM{1[Pi valid]}
where:
Pdaily - Daily accumulation (mm)
Pi - 3-hourly input, in (mm/hr)
Nf - Number of 3-hourly files per day, Nf=8
1[.] - Indicator function; 1 when Pi is valid, 0 otherwise
Pdaily_cnt - Number of valid retrievals in a grid cell per day.
Grid cells for which Pdaily_cnt=0, are set to fill value in the Daily files.
Note that Pi=0 is a valid value.
On occasion, the 3-hourly source data have fill values for Pi in a very few grid cells. The total accumulation for such grid cells is still issued, inspite of the likelihood that thus resulting accumulation has a larger uncertainty in representing the "true" daily total. These events are easily detectable using "counts" variables that contain Pdaily_cnt, whereby users can screen out any grid cells for which
Pdaily_cnt less than Nf.
There are various ways the accumulated daily error could be estimated from the source 3-hourly error. In this release, the daily error provided in the data files is calculated as follows. First, squared 3-hourly errors are summed, and then square root of the sum is taken. Similarly to the precipitation, a factor of 3 is finally applied:
Perr_daily = 3 { SUM[ (Perr_i 1[Perr_i valid])^2 ] }^0.5 , i=[1,Nf]
Ncnt_err = SUM( 1[Perr_i valid] )
where:
Perr_daily - Magnitude of the daily accumulated error power, (mm)
Ncnt_err - The counts for the error variable
Thus computed Perr_daily represents the worst case scenario that assumes the error in the 3-hourly source data, which is given in mm/hr, accumulates first within the 3-hour period of the source data, and then continues to accumulate during the day. These values, however, can easily be converted to root mean square error estimate of the rainfall rate:
rms_err = { (Perr_daily/3) ^2 / Ncnt_err }^0.5 (mm/hr)
This estimate assumes that the error given in the 3-hourly files is representative of the error of the rainfall rate (mm/hr) within the 3-hour window of the files, and it is random throughout the day. Note, this should be interpreted as the error of the rainfall rate (mm/hr) for the day, not the daily accumulation.
Product Summary
Citation
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Documents
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Downscaling algorithms for annual TRMM data based on climatic and orographic variables over the Qinling Mountains, China | Meng, Qing, Sarukkalige, Ranjan, Fu, Guobin, Wang, Guan, Jia, Wenhao, Liu, Zhuang, Bai, Hongying, Peng, Xiaobang, Zhang, Shanhong | Total Surface Precipitation Rate | |
| Delineation of most favorable winds for southwest monsoon rainfall along Kerala coast | V. B., Adith, A. Can, Aftab, DMello, Joshua | Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Aerosol sensitivity simulations over East Asia in a | Li, Shuping, Srland, Silje Lund, Wild, Martin, Schar, Christoph | Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Accuracy of satellite precipitation products in data-scarce Inner Tibetan Plateau comprehensively evaluated using a novel ground observation network | Liu, Zhaofei | Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| A Study of Aerosol-Cloud Variability under Different Rainfall Scenarios | Srivastava, Rohit, Shah, Ruchita, Sharma, Som, Patel, Jigisha, Panicker, Dency, Vachharajani, Bhasha | Total Surface Precipitation Rate | |
| A fusion-based data assimilation framework for runoff prediction considering multiple sources of precipitation | Bahrami, Maziyar, Talebbeydokhti, Nasser, Rakhshandehroo, Gholamreza, Nikoo, Mohammad Reza, Adamowski, Jan Franklin | Total Surface Precipitation Rate | |
| Assimilation of GRACE FollowOn InterSatellite Laser Ranging Measurements Into Land Surface Models | Khaki, Mehdi, Han, ShinChan, GhobadiFar, Khosro, Yeo, InYoung, Tangdamrongsub, Natthachet | Total Surface Precipitation Rate, Gravity, Surface Soil Moisture | |
| Ensemble precipitation estimates based on an assessment of 21 gridded precipitation datasets to improve precipitation estimations across Madagascar | Ollivier, Camille C., Carriere, Simon D., Heath, Thomas, Olioso, Albert, Rabefitia, Zo, Rakoto, Heritiana, Oudin, Ludovic, Satge, Frederic | Heat Flux, Air Temperature, Skin Temperature, Specific Humidity, Water Vapor, Precipitation Rate, Snow/Ice, Evaporation, Latent Heat Flux, Latent Heat Flux, Sensible Heat Flux, Diffusion, Surface Winds, Wind Speed, U/V Wind Components, Wind Stress, Wind Stress, Surface Roughness, Planetary Boundary Layer Height, Ice Fraction, Total Surface Precipitation Rate, Longwave Radiation, Shortwave Radiation, Soil Heat Budget, Soil Heat Budget, Soil Temperature, Soil Temperature, Soil Infiltration, Soil Infiltration, Soil Moisture/Water Content, Surface Soil Moisture, Root Zone Soil Moisture, Soil Moisture/Water Content, Surface Water, Runoff Rate, Average Flow, Average Flow, Precipitation, Snow Depth, Snow Melt, Snow/Ice Temperature, Leaf Area Index (LAI), Leaf Area Index (LAI), Rain, Precipitation Amount, Snow | |
| Evolutionary Determinants of Nonseasonal Breeding in Wild Chacma Baboons | Dezeure, Jules, Burtschell, Lugdiwine, Baniel, Alice, Carter, Alecia J., Godelle, Bernard, Cowlishaw, Guy, Huchard, Elise | Total Surface Precipitation Rate, Land Surface Temperature, Emissivity | |
| Global Simulation of the Madden-Julian Oscillation With Stochastic | Shin, Jihoon, Baik, JongJin | Total Surface Precipitation Rate, Rain | |
| GIS-Based Soil Erosion Risk Assessment in the Watersheds of Bukidnon, Philippines Using the RUSLE Model | Dapin, Indie G., Ella, Victor B. | Total Surface Precipitation Rate | |
| Monsoon depressions and air-sea interactions during different phases of monsoon intraseasonal oscillation | Ray, Arkaprava, Sil, Sourav | Total Surface Precipitation Rate | |
| Unravelling the causes of 2015 winter monsoon extreme rainfall and floods over Chennai: Influence of atmospheric variability and urbanization on the hydrological ... | Konduru, Rakesh Teja, Mrudula, G., Singh, Vivek, Srivastava, Atul Kumar, Singh, Abhay K. | Total Surface Precipitation Rate | |
| The Lack of a QBOMJO Connection in Climate Models With a Nudged Stratosphere | Martin, Zane K., Simpson, Isla R., Lin, Pu, Orbe, Clara, Tang, Qi, Caron, Julie M., Chen, ChihChieh, Kim, Hyemi, Leung, L. Ruby, Richter, Jadwiga H., Xie, Shaocheng | Total Surface Precipitation Rate | |
| The changing characteristics of rainfall over the Brahmaputra Basin during 19982018 | Gogoi, Partha Pratim, Vinoj, V., Landu, Kiranmayi, Phukon, Parag | Total Surface Precipitation Rate | |
| The Combined Power of Double Mass Curves and Bias Correction for the Maximisation of the Accuracy of an Ensemble Satellite-Based Precipitation Estimate ... | Sriwongsitanon, Nutchanart, Kaprom, Chanphit, Tantisuvanichkul, Kamonpat, Prasertthonggorn, Nattakorn, Suiadee, Watchara, Bastiaanssen, Wim G. M., Williams, James Alexander | Total Surface Precipitation Rate, Droplet Size, Precipitation Rate, Radar Reflectivity | |
| Instant and delayed effects of March biomass burning aerosols over the | Zhu, Anbao, Xu, Haiming, Deng, Jiechun, Ma, Jing, Hua, Shaofeng | Geopotential Height, Altitude, Surface Temperature, Upper Air Temperature, Dew Point Temperature, Air Temperature, Cloud Top Temperature, Atmospheric Winds, Surface Winds, U/V Wind Components, Upper Level Winds, U/V Wind Components, Vertical Wind Velocity/Speed, Atmospheric Pressure, Sea Level Pressure, Cloud Top Pressure, Sea Level Pressure, Surface Pressure, Specific Humidity, Total Precipitable Water, Cloud Liquid Water/Ice, Atmospheric Water Vapor, Atmospheric Ozone, Oxygen Compounds, Boundary Layer Winds, Skin Temperature, Aerosols, Aerosol Extinction, Aerosol Optical Depth/Thickness, Angstrom Exponent, Aerosol Particle Properties, Carbonaceous Aerosols, Dust/Ash/Smoke, Organic Particles, Sulfate Particles, Sulfur Oxides, Sulfur Compounds, Sulfate, Sulfur Dioxide, Sulfur Oxides, Particulate Matter, Dimethyl Sulfide, Black Carbon, Sea Salt, PARTICULATE MATTER (PM 2.5), PARTICULATE MATTER (PM 1.0), PARTICULATE MATTER (PM 10), Total Surface Precipitation Rate, Aerosol Extinction, Aerosol Optical Depth/Thickness, Aerosol Optical Depth/Thickness, Aerosol Optical Depth/Thickness, Nitrogen Oxides, Particulates, Hydrogen Cyanide, Emissions, Non-methane Hydrocarbons/Volatile Organic Compounds, Fire Occurrence, Nitrogen Oxides, Carbon And Hydrocarbon Compounds, Aerosol Backscatter, Aerosol Radiance, Cloud Condensation Nuclei, Nitrate Particles, Trace Gases/Trace Species, Atmospheric Emitted Radiation, Emissivity, Optical Depth/Thickness, Radiative Flux, Reflectance, Transmittance, Atmospheric Stability, Humidity, Water Vapor Profiles, Cloud Condensation Nuclei, Cloud Droplet Concentration/Size, Cloud Optical Depth/Thickness, Cloud Asymmetry, Cloud Ceiling, Cloud Frequency, Cloud Height, Cloud Vertical Distribution, Cloud Emissivity, Cloud Radiative Forcing, Cloud Reflectance, Rain Storms | |
| Hydro-Meteorological Analysis of 2015 Rarh Bengal Flood in the Lower Gangetic Plain of India: Exceptional, Fast and Furious | Chatterjee, Soumen, Jana, Narayan Chandra | Total Surface Precipitation Rate | |
| Persistent Wet and Dry Spells of Indian Summer Monsoon Rainfall: A Reexamination of Definitions of Active and Break Events | Saha, Prolay, Mahanta, Rahul, Rajesh, P. V., Goswami, B. N. | Total Surface Precipitation Rate | |
| Performance evaluation of IMERG and TMPA daily precipitation products over CONUS (20002019) | Pirmoradian, Roghayeh, Hashemi, Hossein, Fayne, Jessica | Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Rainstorms Inducing Shifts of River Hydrochemistry during a Winter | Rojano, Fernando, Huber, David H., Ugwuanyi, Ifeoma R., Kemajou-Tchamba, Andrielle Larissa, Hass, Amir | Total Surface Precipitation Rate | |
| Multiscale Combined Action and Disturbance Characteristics of Pre-summer Extreme Precipitation Events over South China | Liu, Hongbo, Yan, Ruojing, Wang, Bin, Chen, Guanghua, Ling, Jian, Fu, Shenming | Total Surface Precipitation Rate | |
| The Influence of Shallow Cloud Populations on Transitions to Deep Convection in the Amazon | Barber, Katelyn A., Burleyson, Casey D., Feng, Zhe, Hagos, Samson M. | Precipitation, Brightness Temperature, Total Surface Precipitation Rate, Clouds, Cloud Properties, Cloud Fraction, Cloud Frequency, Cloud Height, Cloud Top Height, Cloud Top Temperature, Cloud Emissivity, Infrared Radiance, REFLECTED INFRARED, Visible Radiance | |
| The sensitivity of the West African monsoon circulation to intraseasonal soil moisture feedbacks | Talib, Joshua, Taylor, Christopher M., Klein, Cornelia, Harris, Bethan L., Anderson, Seonaid R., Semeena, Valiyaveetil S. | Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| The Impact of Scale-Aware Parameterization on the Next-Generation Global | Lin, Chang-Hung, Yang, Ming-Jen, Hsiao, Ling-Feng, Chen, Jen-Her | Total Surface Precipitation Rate |