Gabella, M.,
Joss, J.,
Perona, G.,
Michaelides, S.,
Range Adjustment for Ground-Based Radar, Derived With the Spaceborne
TRMM Precipitation Radar,
GeoRS(44), No. 1, January 2006, pp. 126-133.
IEEE DOI
0601
BibRef
Tarnavsky, E.[Elena],
Mulligan, M.[Mark],
Ouessar, M.[Mohamed],
Faye, A.[Abdoulaye],
Black, E.[Emily],
Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall,
RS(5), No. 12, 2013, pp. 6691-6716.
DOI Link
1402
BibRef
Boschetti, M.[Mirco],
Nutini, F.[Francesco],
Brivio, P.A.[Pietro Alessandro],
Bartholomé, E.[Etienne],
Stroppiana, D.[Daniela],
Hoscilo, A.[Agata],
Identification of environmental anomaly hot spots in West Africa from
time series of NDVI and rainfall,
PandRS(78), No. 1, April 2013, pp. 26-40.
Elsevier DOI
1304
West African Sahel; Satellite time series; Environmental anomalies;
Change detection; Monitoring; Correlation; Ecosystem; Temporal
BibRef
Stroppiana, D.[Daniela],
Boschetti, M.[Mirco],
Brivio, P.A.[Pietro A.],
Nutini, F.[Francesco],
Bartholome, E.[Etienne],
Analysis of earth observation time series to investigate the relation
between rainfall, vegetation dynamic and streamflow in the Uele' basin
(Central African Republic),
MultiTemp11(177-180).
IEEE DOI
1109
BibRef
Mishra, A.K.,
A New Technique to Estimate Precipitation at Fine Scale Using
Multifrequency Satellite Observations Over Indian Land and Oceanic Regions,
GeoRS(51), No. 7, 2013, pp. 4349-4358.
IEEE DOI
1307
Rain
BibRef
de Coning, E.[Estelle],
Optimizing Satellite-Based Precipitation Estimation for Nowcasting of
Rainfall and Flash Flood Events over the South African Domain,
RS(5), No. 11, 2013, pp. 5702-5724.
DOI Link
1312
BibRef
Xu, S.G.[Shi-Guang],
Wu, C.Y.[Chao-Yang],
Gonsamo, A.[Alemu],
Shen, Y.[Yan],
Delineation of Rain Areas with TRMM Microwave Observations Based on
PNN,
RS(6), No. 12, 2014, pp. 12118-12137.
DOI Link
1412
BibRef
Mahmud, M.R.[Mohd Rizaludin],
Numata, S.[Shinya],
Matsuyama, H.[Hiroshi],
Hosaka, T.[Tetsuro],
Hashim, M.[Mazlan],
Assessment of Effective Seasonal Downscaling of TRMM Precipitation
Data in Peninsular Malaysia,
RS(7), No. 4, 2015, pp. 4092-4111.
DOI Link
1505
BibRef
Shi, Y.[Yuli],
Song, L.[Lei],
Xia, Z.[Zhen],
Lin, Y.R.[Yu-Rong],
Myneni, R.B.[Ranga B.],
Choi, S.[Sungho],
Wang, L.[Lin],
Ni, X.L.[Xi-Liang],
Lao, C.[Cailian],
Yang, F.K.[Feng-Kai],
Mapping Annual Precipitation across Mainland China in the Period
2001-2010 from TRMM3B43 Product Using Spatial Downscaling Approach,
RS(7), No. 5, 2015, pp. 5849-5878.
DOI Link
1506
BibRef
Yong, B.[Bin],
Chen, B.[Bo],
Hong, Y.[Yang],
Gourley, J.J.[Jonathan J.],
Li, Z.[Zhe],
Impact of Missing Passive Microwave Sensors on Multi-Satellite
Precipitation Retrieval Algorithm,
RS(7), No. 1, 2015, pp. 668-683.
DOI Link
1502
BibRef
Verdin, A.,
Funk, C.,
Rajagopalan, B.,
Kleiber, W.,
Kriging and Local Polynomial Methods for Blending Satellite-Derived
and Gauge Precipitation Estimates to Support Hydrologic Early Warning
Systems,
GeoRS(54), No. 5, May 2016, pp. 2552-2562.
IEEE DOI
1604
alarm systems
BibRef
Takahashi, N.,
Hanado, H.,
Nakamura, K.,
Kanemaru, K.,
Nakagawa, K.,
Iguchi, T.,
Nio, T.,
Kubota, T.,
Oki, R.,
Yoshida, N.,
Overview of the End-of-Mission Observation Experiments of
Precipitation Radar Onboard the Tropical Rainfall Measuring Mission
Satellite,
GeoRS(54), No. 6, June 2016, pp. 3450-3459.
IEEE DOI
1606
artificial satellites
BibRef
Chen, J.Q.[Jia-Qi],
Yong, B.[Bin],
Ren, L.L.[Li-Liang],
Wang, W.G.[Wei-Guang],
Chen, B.[Bo],
Lin, J.A.[Jian-An],
Yu, Z.B.[Zhong-Bo],
Li, N.[Ning],
Using a Kalman Filter to Assimilate TRMM-Based Real-Time Satellite
Precipitation Estimates over Jinghe Basin, China,
RS(8), No. 11, 2016, pp. 899.
DOI Link
1612
BibRef
Jing, W.L.[Wen-Long],
Yang, Y.P.[Ya-Ping],
Yue, X.F.[Xia-Fang],
Zhao, X.D.[Xiao-Dan],
A Spatial Downscaling Algorithm for Satellite-Based Precipitation
over the Tibetan Plateau Based on NDVI, DEM, and Land Surface
Temperature,
RS(8), No. 8, 2016, pp. 655.
DOI Link
1609
BibRef
Jing, W.L.[Wen-Long],
Yang, Y.P.[Ya-Ping],
Yue, X.F.[Xia-Fang],
Zhao, X.D.[Xiao-Dan],
A Comparison of Different Regression Algorithms for Downscaling
Monthly Satellite-Based Precipitation over North China,
RS(8), No. 10, 2016, pp. 835.
DOI Link
1609
BibRef
Jing, W.L.[Wen-Long],
Zhang, P.Y.[Peng-Yan],
Jiang, H.[Hao],
Zhao, X.D.[Xiao-Dan],
Reconstructing Satellite-Based Monthly Precipitation over Northeast
China Using Machine Learning Algorithms,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link
1708
BibRef
Hong, S.,
Shin, D.B.,
Park, B.,
So, D.,
Development of Prototype Algorithms for Quantitative Precipitation
Nowcasts From AMI Onboard the GEO-KOMPSAT-2A Satellite,
GeoRS(54), No. 12, December 2016, pp. 7149-7156.
IEEE DOI
1612
atmospheric precipitation
BibRef
Park, N.W.[No-Wook],
Kyriakidis, P.C.[Phaedon C.],
Hong, S.[Sungwook],
Geostatistical Integration of Coarse Resolution Satellite
Precipitation Products and Rain Gauge Data to Map Precipitation at
Fine Spatial Resolutions,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
BibRef
Yuan, F.[Fei],
Zhang, L.M.[Li-Min],
Soe, K.M.W.[Khin Min Wun],
Ren, L.L.[Li-Liang],
Zhao, C.X.[Chong-Xu],
Zhu, Y.H.[Yong-Hua],
Jiang, S.[Shanhu],
Liu, Y.[Yi],
Applications of TRMM- and GPM-Era Multiple-Satellite Precipitation
Products for Flood Simulations at Sub-Daily Scales in a Sparsely
Gauged Watershed in Myanmar,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Takahashi, N.,
Surface Echo Characteristics Derived From the Wide Swath Experiment
of the Precipitation Radar Onboard TRMM Satellite During Its
End-of-Mission Operation,
GeoRS(55), No. 4, April 2017, pp. 1988-1993.
IEEE DOI
1704
atmospheric precipitation
BibRef
Burdanowitz, J.[Jörg],
Klepp, C.[Christian],
Bakan, S.[Stephan],
Buehler, S.A.[Stefan A.],
Simulation of Ship-Track versus Satellite-Sensor Differences in
Oceanic Precipitation Using an Island-Based Radar,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Duan, Y.J.[Ya-Juan],
Barros, A.P.[Ana P.],
Understanding How Low-Level Clouds and Fog Modify the Diurnal Cycle
of Orographic Precipitation Using In Situ and Satellite Observations,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link
1711
BibRef
Nash, D.[Deanna],
Ye, H.C.[Heng-Chun],
Fetzer, E.[Eric],
Spatial and Temporal Variability in Winter Precipitation across the
Western United States during the Satellite Era,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link
1711
BibRef
Yoshimoto, S.[Shuhei],
Amarnath, G.[Giriraj],
Applications of Satellite-Based Rainfall Estimates in Flood
Inundation Modeling: A Case Study in Mundeni Aru River Basin, Sri
Lanka,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link
1711
BibRef
Ulloa, J.[Jacinto],
Ballari, D.[Daniela],
Campozano, L.[Lenin],
Samaniego, E.[Esteban],
Two-Step Downscaling of Trmm 3b43 V7 Precipitation in Contrasting
Climatic Regions With Sparse Monitoring: The Case of Ecuador in
Tropical South America,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link
1708
BibRef
Zhang, Y.Y.[Yue-Yuan],
Li, Y.G.[Yun-Gang],
Ji, X.[Xuan],
Luo, X.[Xian],
Li, X.[Xue],
Fine-Resolution Precipitation Mapping in a Mountainous Watershed:
Geostatistical Downscaling of TRMM Products Based on Environmental
Variables,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link
1802
BibRef
He, Y.X.[Yu-Xiang],
Zhang, Y.[Yu],
Kuligowski, R.[Robert],
Cifelli, R.[Robert],
Kitzmiller, D.[David],
Incorporating Satellite Precipitation Estimates into a Radar-Gauge
Multi-Sensor Precipitation Estimation Algorithm,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link
1802
BibRef
Arslan, C.H.,
Aydin, K.,
Urbina, J.V.,
Dyrud, L.,
Satellite-Link Attenuation Measurement Technique for Estimating
Rainfall Accumulation,
GeoRS(56), No. 2, February 2018, pp. 681-693.
IEEE DOI
1802
Doppler radar, attenuation measurement,
geophysical signal processing, meteorological radar,
rainfall estimation
BibRef
Shen, Y.[Yan],
Hong, Z.[Zhen],
Pan, Y.[Yang],
Yu, J.J.[Jing-Jing],
Maguire, L.[Lane],
China's 1 km Merged Gauge, Radar and Satellite Experimental
Precipitation Dataset,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Militino, A.F.[Ana F.],
Ugarte, M.D.[M. Dolores],
Pérez-Goya, U.[Unai],
Improving the Quality of Satellite Imagery Based on Ground-Truth Data
from Rain Gauge Stations,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Alahacoon, N.[Niranga],
Matheswaran, K.[Karthikeyan],
Pani, P.[Peejush],
Amarnath, G.[Giriraj],
A Decadal Historical Satellite Data and Rainfall Trend Analysis
(2001-2016) for Flood Hazard Mapping in Sri Lanka,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Muhammad, W.[Waseem],
Yang, H.[Hanbo],
Lei, H.M.[Hui-Min],
Muhammad, A.[Ajmal],
Yang, D.[Dawen],
Improving the Regional Applicability of Satellite Precipitation
Products by Ensemble Algorithm,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link
1805
BibRef
Tapiador, F.J.[Francisco J.],
Marcos, C.[Cecilia],
Navarro, A.[Andres],
Jiménez-Alcázar, A.[Alfonso],
Galdón, R.M.[Raul Moreno],
Sanz, J.[Julia],
Decorrelation of Satellite Precipitation Estimates in Space and Time,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Cattani, E.[Elsa],
Merino, A.[Andrés],
Guijarro, J.A.[José A.],
Levizzani, V.[Vincenzo],
East Africa Rainfall Trends and Variability 1983-2015 Using Three
Long-Term Satellite Products,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Beusch, L.[Lea],
Foresti, L.[Loris],
Gabella, M.[Marco],
Hamann, U.[Ulrich],
Satellite-Based Rainfall Retrieval:
From Generalized Linear Models to Artificial Neural Networks,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Cánovas-García, F.[Fulgencio],
García-Galiano, S.[Sandra],
Alonso-Sarría, F.[Francisco],
Assessment of Satellite and Radar Quantitative Precipitation
Estimates for Real Time Monitoring of Meteorological Extremes Over
the Southeast of the Iberian Peninsula,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link
1808
BibRef
Kimani, M.W.[Margaret Wambui],
Hoedjes, J.C.B.[Joost C. B.],
Su, Z.B.[Zhong-Bo],
Bayesian Bias Correction of Satellite Rainfall Estimates for Climate
Studies,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link
1808
BibRef
Satgé, F.[Frédéric],
Hussain, Y.[Yawar],
Bonnet, M.P.[Marie-Paule],
Hussain, B.M.[Babar M.],
Martinez-Carvajal, H.[Hernan],
Akhter, G.[Gulraiz],
Uagoda, R.[Rogério],
Benefits of the Successive GPM Based Satellite Precipitation
Estimates IMERG-V03, -V04, -V05 and GSMaP-V06, -V07 Over Diverse
Geomorphic and Meteorological Regions of Pakistan,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Ricciardelli, E.[Elisabetta],
di Paola, F.[Francesco],
Gentile, S.[Sabrina],
Cersosimo, A.[Angela],
Cimini, D.[Domenico],
Gallucci, D.[Donatello],
Geraldi, E.[Edoardo],
Larosa, S.[Salvatore],
Nilo, S.T.[Saverio Teodosio],
Ripepi, E.[Ermann],
Romano, F.[Filomena],
Viggiano, M.[Mariassunta],
Analysis of Livorno Heavy Rainfall Event: Examples of Satellite-Based
Observation Techniques in Support of Numerical Weather Prediction,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link
1811
BibRef
Ur Rahman, K.[Khalil],
Shang, S.[Songhao],
Shahid, M.[Muhammad],
Li, J.[Jiang],
Developing an Ensemble Precipitation Algorithm from Satellite
Products and Its Topographical and Seasonal Evaluations Over Pakistan,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Zhang, R.Y.[Ruan-Yu],
Wang, Z.Z.[Zhen-Zhan],
Hilburn, K.A.[Kyle A.],
Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness
Temperatures Using the WS Algorithm,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Cersosimo, A.[Angela],
Larosa, S.[Salvatore],
Romano, F.[Filomena],
Cimini, D.[Domenico],
di Paola, F.[Francesco],
Gallucci, D.[Donatello],
Gentile, S.[Sabrina],
Geraldi, E.[Edoardo],
Nilo, S.T.[Saverio Teodosio],
Ricciardelli, E.[Elisabetta],
Ripepi, E.[Ermann],
Viggiano, M.[Mariassunta],
Downscaling of Satellite OPEMW Surface Rain Intensity Data,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Aboutalebi, M.[Mahyar],
Torres-Rua, A.F.[Alfonso F.],
Allen, N.[Niel],
Spatial and Temporal Analysis of Precipitation and Effective Rainfall
Using Gauge Observations, Satellite, and Gridded Climate Data for
Agricultural Water Management in the Upper Colorado River Basin,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Zhang, D.[Dan],
Liu, X.M.[Xiao-Mang],
Bai, P.[Peng],
Li, X.H.[Xiang-Hu],
Suitability of Satellite-Based Precipitation Products for Water
Balance Simulations Using Multiple Observations in a Humid Catchment,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Santos, C.A.G.[Celso Augusto Guimarães],
Neto, R.M.B.[Reginaldo Moura Brasil],
da Silva, R.M.[Richarde Marques],
Fernandes-Costa, S.G.[Samir Gonçalves],
Cluster Analysis Applied to Spatiotemporal Variability of Monthly
Precipitation over Paraíba State Using Tropical Rainfall Measuring
Mission (TRMM) Data,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Mega, T.,
Ushio, T.,
Takahiro, M.,
Kubota, T.,
Kachi, M.,
Oki, R.,
Gauge-Adjusted Global Satellite Mapping of Precipitation,
GeoRS(57), No. 4, April 2019, pp. 1928-1935.
IEEE DOI
1904
hydrological techniques, hydrology, rain, remote sensing by radar,
Gauge-adjusted Global satellite mapping,
spaceborne radar
BibRef
Dong, H.,
Zou, X.,
Striping Noise Mitigation for Tropical Rainfall Measuring Mission
Microwave Imager Observations,
GeoRS(57), No. 4, April 2019, pp. 2449-2463.
IEEE DOI
1904
atmospheric techniques, environmental monitoring (geophysics),
feature extraction, geophysical signal processing, rain,
Tropical Rainfall Measuring Mission Microwave Imager (TMI)
BibRef
Ma, Q.M.[Qiu-Mei],
Xiong, L.H.[Li-Hua],
Xia, J.[Jun],
Xiong, B.[Bin],
Yang, H.[Han],
Xu, C.Y.[Chong-Yu],
A Censored Shifted Mixture Distribution Mapping Method to Correct the
Bias of Daily IMERG Satellite Precipitation Estimates,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Shen, X.,
Huang, D.D.,
Song, B.,
Vincent, C.,
Togneri, R.,
3-D Tomographic Reconstruction of Rain Field Using Microwave Signals
From LEO Satellites: Principle and Simulation Results,
GeoRS(57), No. 8, August 2019, pp. 5434-5446.
IEEE DOI
1908
atmospheric techniques, geophysics computing, microwave links,
rain, signal reconstruction, 3-D tomographic reconstruction,
signal-to-noise ratio (SNR) estimation
BibRef
Jiang, W.W.[Wei-Wei],
Zhan, Y.F.[Ya-Feng],
Xi, S.[Shen],
Huang, D.D.[Defeng David],
Lu, J.H.[Jian-Hua],
Compressive Sensing-Based 3-D Rain Field Tomographic Reconstruction
Using Simulated Satellite Signals,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI
2112
Rain, Satellites, Attenuation, Satellite broadcasting,
Compressed sensing, Receivers, Microwave theory and techniques,
tomographic reconstruction
BibRef
Kanemaru, K.,
Kubota, T.,
Iguchi, T.,
Improvements in the Beam-Mismatch Correction of Precipitation Radar
Data After the TRMM Orbit Boost,
GeoRS(57), No. 9, September 2019, pp. 7161-7169.
IEEE DOI
1909
Orbits, Spaceborne radar, Extraterrestrial measurements,
Degradation, Satellites, Radar measurements, Algorithm,
tropical rainfall measuring mission (TRMM)
BibRef
Hayatbini, N.[Negin],
Kong, B.[Bailey],
Hsu, K.L.[Kuo-Lin],
Nguyen, P.[Phu],
Sorooshian, S.[Soroosh],
Stephens, G.[Graeme],
Fowlkes, C.C.[Charless C.],
Nemani, R.[Ramakrishna],
Ganguly, S.[Sangram],
Conditional Generative Adversarial Networks (cGANs) for Near
Real-Time Precipitation Estimation from Multispectral GOES-16
Satellite Imageries: PERSIANN-cGAN,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link
1910
BibRef
Levizzani, V.[Vincenzo],
Cattani, E.[Elsa],
Satellite Remote Sensing of Precipitation and the Terrestrial Water
Cycle in a Changing Climate,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link
1910
BibRef
Belabid, N.[Nasreddine],
Zhao, F.[Feng],
Brocca, L.[Luca],
Huang, Y.B.[Yan-Bo],
Tan, Y.M.[Yu-Min],
Near-Real-Time Flood Forecasting Based on Satellite Precipitation
Products,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link
1902
BibRef
Kumar, A.[Ashish],
Ramsankaran, R.[Raaj],
Brocca, L.[Luca],
Munoz-Arriola, F.[Francisco],
A Machine Learning Approach for Improving Near-Real-Time
Satellite-Based Rainfall Estimates by Integrating Soil Moisture,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link
1910
BibRef
Moraux, A.[Arthur],
Dewitte, S.[Steven],
Cornelis, B.[Bruno],
Munteanu, A.[Adrian],
Deep Learning for Precipitation Estimation from Satellite and Rain
Gauges Measurements,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Wu, J.P.[Jian-Ping],
Liu, L.Y.[Li-Yang],
Sun, C.H.[Cai-Hong],
Su, Y.X.[Yong-Xian],
Wang, C.J.[Chang-Jian],
Yang, J.[Ji],
Liao, J.Y.[Jia-Yuan],
He, X.L.[Xiao-Lei],
Li, Q.[Qian],
Zhang, C.Q.[Chao-Qun],
Zhang, H.O.[Hong-Ou],
Estimating Rainfall Interception of Vegetation Canopy from MODIS
Imageries in Southern China,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Pullman, M.,
Gurung, I.,
Maskey, M.,
Ramachandran, R.,
Christopher, S.A.,
Applying Deep Learning to Hail Detection: A Case Study,
GeoRS(57), No. 12, December 2019, pp. 10218-10225.
IEEE DOI
1912
Deep learning, Storms, Weather forecasting, Satellites,
Spaceborne radar, Artificial intelligence, event detection, neural networks
BibRef
Fan, D.[Dong],
Wu, H.[Hua],
Dong, G.[Guotao],
Jiang, X.G.[Xiao-Guang],
Xue, H.Z.[Hua-Zhu],
A Temporal Disaggregation Approach for TRMM Monthly Precipitation
Products Using AMSR2 Soil Moisture Data,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Li, N.[Nan],
Wang, Z.[Zhenhui],
Chen, X.[Xi],
Austin, G.[Geoffrey],
Studies of General Precipitation Features with TRMM PR Data:
An Extensive Overview,
RS(11), No. 1, 2019, pp. xx-yy.
DOI Link
1901
Survey, Precipitation.
BibRef
Wang, L.[Lei],
Chen, R.S.[Ren-Sheng],
Han, C.T.[Chun-Tan],
Yang, Y.[Yong],
Liu, J.F.[Jun-Feng],
Liu, Z.W.[Zhang-Wen],
Wang, X.Q.[Xi-Qiang],
Liu, G.H.[Guo-Hua],
Guo, S.H.[Shu-Hai],
An Improved Spatial-Temporal Downscaling Method for TRMM
Precipitation Datasets in Alpine Regions: A Case Study in
Northwestern China's Qilian Mountains,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link
1904
BibRef
Li, Y.[Yun],
Guo, B.[Bin],
Wang, K.[Kaicun],
Wu, G.[Guocan],
Shi, C.M.[Chun-Ming],
Performance of TRMM Product in Quantifying Frequency and Intensity of
Precipitation during Daytime and Nighttime across China,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Retalis, A.[Adrianos],
Katsanos, D.[Dimitris],
Tymvios, F.[Filippos],
Michaelides, S.[Silas],
Comparison of GPM IMERG and TRMM 3B43 Products over Cyprus,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Elnashar, A.[Abdelrazek],
Zeng, H.W.[Hong-Wei],
Wu, B.F.[Bing-Fang],
Zhang, N.[Ning],
Tian, F.[Fuyou],
Zhang, M.[Miao],
Zhu, W.W.[Wei-Wei],
Yan, N.[Nana],
Chen, Z.Q.[Ze-Qiang],
Sun, Z.Y.[Zhi-Yu],
Wu, X.H.[Xing-Hua],
Li, Y.[Yuan],
Downscaling TRMM Monthly Precipitation Using Google Earth Engine and
Google Cloud Computing,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Li, X.H.[Xiang-Hu],
Li, Z.[Zhen],
Lin, Y.L.[Ya-Ling],
Suitability of TRMM Products with Different Temporal Resolution
(3-Hourly, Daily, and Monthly) for Rainfall Erosivity Estimation,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Ebtehaj, A.,
Kummerow, C.D.,
Turk, F.J.,
Metric Learning for Approximation of Microwave Channel Error
Covariance: Application for Satellite Retrieval of Drizzle and Light
Snowfall,
GeoRS(58), No. 2, February 2020, pp. 903-912.
IEEE DOI
2001
Ocean temperature, Brightness temperature, Sea surface,
Bayes methods, Microwave radiometry, Channel error covariance,
satellite snowfall detection
BibRef
Chen, H.,
Chandrasekar, V.,
Cifelli, R.,
Xie, P.,
A Machine Learning System for Precipitation Estimation Using
Satellite and Ground Radar Network Observations,
GeoRS(58), No. 2, February 2020, pp. 982-994.
IEEE DOI
2001
Satellites, Spaceborne radar, Meteorology,
Extraterrestrial measurements, Sea measurements,
satellite observations
BibRef
Lolli, S.[Simone],
Vivone, G.[Gemine],
Lewis, J.R.[Jasper R.],
Sicard, M.[Michaël],
Welton, E.J.[Ellsworth J.],
Campbell, J.R.[James R.],
Comerón, A.[Adolfo],
d'Adderio, L.P.[Leo Pio],
Tokay, A.[Ali],
Giunta, A.[Aldo],
Pappalardo, G.[Gelsomina],
Overview of the New Version 3 NASA Micro-Pulse Lidar Network (MPLNET)
Automatic Precipitation Detection Algorithm,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link
2001
BibRef
Lu, X.Y.[Xin-Yu],
Tang, G.Q.[Guo-Qiang],
Wang, X.Q.[Xiu-Qin],
Liu, Y.[Yan],
Wei, M.[Ming],
Zhang, Y.X.[Ying-Xin],
The Development of a Two-Step Merging and Downscaling Method for
Satellite Precipitation Products,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Huang, W.R.[Wan-Ru],
Liu, P.Y.[Pin-Yi],
Chang, Y.H.[Ya-Hui],
Liu, C.Y.[Chian-Yi],
Evaluation and Application of Satellite Precipitation Products in
Studying the Summer Precipitation Variations over Taiwan,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link
2002
BibRef
Wehbe, Y.[Youssef],
Temimi, M.[Marouane],
Adler, R.F.[Robert F.],
Enhancing Precipitation Estimates Through the Fusion of Weather
Radar, Satellite Retrievals, and Surface Parameters,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Li, Z.[Zhi],
Chen, M.Y.[Meng-Ye],
Gao, S.[Shang],
Hong, Z.[Zhen],
Tang, G.Q.[Guo-Qiang],
Wen, Y.X.[Yi-Xin],
Gourley, J.J.[Jonathan J.],
Hong, Y.[Yang],
Cross-Examination of Similarity, Difference and Deficiency of Gauge,
Radar and Satellite Precipitation Measuring Uncertainties for Extreme
Events Using Conventional Metrics and Multiplicative Triple
Collocation,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Mosaffa, H.[Hamidreza],
Sadeghi, M.[Mojtaba],
Hayatbini, N.[Negin],
Gorooh, V.A.[Vesta Afzali],
Asanjan, A.A.[Ata Akbari],
Nguyen, P.[Phu],
Sorooshian, S.[Soroosh],
Spatiotemporal Variations of Precipitation over Iran Using the
High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR
Dataset,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Zhao, Q.,
Liu, Y.,
Ma, X.,
Yao, W.,
Yao, Y.,
Li, X.,
An Improved Rainfall Forecasting Model Based on GNSS Observations,
GeoRS(58), No. 7, July 2020, pp. 4891-4900.
IEEE DOI
2006
Global navigation satellite system, Forecasting,
Atmospheric modeling, Delays, Software, Predictive models,
zenith total delay (ZTD)
BibRef
Takahashi, N.,
Analysis of Surface Cross-Sectional Data Taken During the 90° Yaw
Experiment of the TRMM Precipitation Radar,
GeoRS(58), No. 8, August 2020, pp. 5729-5738.
IEEE DOI
2007
Satellites, Sea surface, Spaceborne radar, Rain, Earth, Wind speed,
Radar cross section, spaceborne precipitation radar (PR)
BibRef
Kanemaru, K.,
Iguchi, T.,
Masaki, T.,
Kubota, T.,
Estimates of Spaceborne Precipitation Radar Pulsewidth and Beamwidth
Using Sea Surface Echo Data,
GeoRS(58), No. 8, August 2020, pp. 5291-5303.
IEEE DOI
2007
Spaceborne radar, Shape, Band-pass filters, Sea surface,
Radar measurements, Pulse measurements,
tropical rainfall measuring mission (TRMM)
BibRef
Boluwade, A.[Alaba],
Remote sensed-based rainfall estimations over the East and West
Africa regions for disaster risk management,
PandRS(167), 2020, pp. 305-320.
Elsevier DOI
2008
Disaster management, Flood management, Precipitation analysis,
Satellite observations, Uganda, Ghana, Satellite Rainfall,
GPM
BibRef
Colli, M.,
Cassola, F.,
Martina, F.,
Trovatore, E.,
Delucchi, A.,
Maggiolo, S.,
Caviglia, D.D.,
Rainfall Fields Monitoring Based on Satellite Microwave Down-Links
and Traditional Techniques in the City of Genoa,
GeoRS(58), No. 9, September 2020, pp. 6266-6280.
IEEE DOI
2008
Rain, Microwave theory and techniques, Microwave measurement,
Sensors, Monitoring, Urban areas, Atmosphere,
satellite-to-earth microwave down-links (SMLs)
BibRef
Le, X.H.[Xuan-Hien],
Lee, G.[Giha],
Jung, K.[Kwansue],
An, H.U.[Hyun-Uk],
Lee, S.[Seungsoo],
Jung, Y.H.[Young-Hun],
Application of Convolutional Neural Network for Spatiotemporal Bias
Correction of Daily Satellite-Based Precipitation,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Lagasio, M.[Martina],
Meroni, A.N.[Agostino N.],
Boni, G.[Giorgio],
Pulvirenti, L.[Luca],
Monti-Guarnieri, A.[Andrea],
Haagmans, R.[Roger],
Hobbs, S.[Stephen],
Parodi, A.[Antonio],
Meteorological OSSEs for New Zenith Total Delay Observations: Impact
Assessment for the Hydroterra Geosynchronous Satellite on the October
2019 Genoa Event,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
Observing System Simulation Experiments.
Extreme rainfall events.
BibRef
Wang, C.,
Xu, J.,
Tang, G.,
Yang, Y.,
Hong, Y.,
Infrared Precipitation Estimation Using Convolutional Neural Network,
GeoRS(58), No. 12, December 2020, pp. 8612-8625.
IEEE DOI
2012
Estimation, Satellites, Meteorology, Remote sensing, Clouds,
Feature extraction, Deep learning,
infrared (IR) precipitation estimation
BibRef
Csurgai-Horváth, L.[László],
Small Scale Rain Field Sensing and Tomographic Reconstruction with
Passive Geostationary Satellite Receivers,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Usowicz, B.[Boguslaw],
Lipiec, J.[Jerzy],
Lukowski, M.[Mateusz],
Slominski, J.[Jan],
Improvement of Spatial Interpolation of Precipitation Distribution
Using Cokriging Incorporating Rain-Gauge and Satellite (SMOS) Soil
Moisture Data,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Lyu, F.,
Tang, G.,
Behrangi, A.,
Wang, T.,
Tan, X.,
Ma, Z.,
Xiong, W.,
Precipitation Merging Based on the Triple Collocation Method Across
Mainland China,
GeoRS(59), No. 4, April 2021, pp. 3161-3176.
IEEE DOI
2104
Merging, Satellites, Meteorology, Estimation, Benchmark testing,
Remote sensing, Uncertainty, China, merging, precipitation, snowfall,
triple collocation (TC)
BibRef
Tang, G.Q.[Guo-Qiang],
Characterization of the Systematic and Random Errors in Satellite
Precipitation Using the Multiplicative Error Model,
GeoRS(59), No. 7, July 2021, pp. 5407-5416.
IEEE DOI
2106
Satellites, Systematics, Additives, Rain, Mathematical model,
Error analysis, Additive model, China, multiplicative model,
systematic and random errors
BibRef
Kumah, K.K.[Kingsley K.],
Hoedjes, J.C.B.[Joost C. B.],
David, N.[Noam],
Maathuis, B.H.P.[Ben H. P.],
Gao, H.O.[H. Oliver],
Su, B.Z.[Bob Z.],
The MSG Technique: Improving Commercial Microwave Link Rainfall
Intensity by Using Rain Area Detection from Meteosat Second
Generation,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Zhang, Y.H.[Yu-Hang],
Ye, A.[Aizhong],
Nguyen, P.[Phu],
Analui, B.[Bita],
Sorooshian, S.[Soroosh],
Hsu, K.[Kuolin],
Error Characteristics and Scale Dependence of Current Satellite
Precipitation Estimates Products in Hydrological Modeling,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Sun, L.[Luyao],
Chen, H.[Haonan],
Li, Z.[Zhe],
Han, L.[Lei],
Cross Validation of GOES-16 and NOAA Multi-Radar Multi-Sensor (MRMS)
QPE over the Continental United States,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
quantitative precipitation estimation.
BibRef
Shi, J.[Jiayong],
Wang, B.[Bing],
Wang, G.Q.[Guo-Qing],
Yuan, F.[Fei],
Shi, C.X.[Chun-Xiang],
Zhou, X.[Xiong],
Zhang, L.M.[Li-Min],
Zhao, C.X.[Chong-Xu],
Are the Latest GSMaP Satellite Precipitation Products Feasible for
Daily and Hourly Discharge Simulations in the Yellow River Source
Region?,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Hinge, G.[Gilbert],
Mohamed, M.M.[Mohamed M.],
Long, D.[Di],
Hamouda, M.A.[Mohamed A.],
Meta-Analysis in Using Satellite Precipitation Products for Drought
Monitoring: Lessons Learnt and Way Forward,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Ren, J.[Jing],
Xu, G.R.[Gui-Rong],
Zhang, W.G.[Wen-Gang],
Leng, L.[Liang],
Xiao, Y.J.[Yan-Jiao],
Wan, R.[Rong],
Wang, J.C.[Jun-Chao],
Evaluation and Improvement of FY-4A AGRI Quantitative Precipitation
Estimation for Summer Precipitation over Complex Topography of
Western China,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Dou, Y.H.[Yan-Hong],
Ye, L.[Lei],
Zhang, J.Y.[Jia-Yan],
Zhang, C.[Chi],
Zhou, H.[Huicheng],
Evaluation of Seven Near-Real-Time Satellite-Based Precipitation
Products for Wet Seasons in the Nierji Basin, China,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Liu, Q.[Qian],
Chiu, L.S.[Long S.],
Hao, X.J.[Xian-Jun],
Yang, C.W.[Chao-Wei],
Spatiotemporal Trends and Variations of the Rainfall Amount,
Intensity, and Frequency in TRMM Multi-satellite Precipitation
Analysis (TMPA) Data,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Lepetit, P.[Pierre],
Ly, C.[Camille],
Barthès, L.[Laurent],
Mallet, C.[Cécile],
Viltard, N.[Nicolas],
Lemaitre, Y.[Yvon],
Rottner, L.[Lucie],
Using Deep Learning for Restoration of Precipitation Echoes in Radar
Data,
GeoRS(60), 2022, pp. 1-14.
IEEE DOI
2112
Clutter, Image restoration, Radar, Training, Radar imaging,
Image segmentation, Task analysis, Blind inpainting, deep learning,
weak supervision
BibRef
Asgarimehr, M.[Milad],
Hoseini, M.[Mostafa],
Semmling, M.[Maximilian],
Ramatschi, M.[Markus],
Camps, A.[Adriano],
Nahavandchi, H.[Hossein],
Haas, R.[Rüdiger],
Wickert, J.[Jens],
Remote Sensing of Precipitation Using Reflected GNSS Signals:
Response Analysis of Polarimetric Observations,
GeoRS(60), 2022, pp. 1-12.
IEEE DOI
2112
Rain, Sea surface, Sea measurements,
Global navigation satellite system, Salinity (geophysical),
surface-roughening
BibRef
Tang, X.[Xuan],
Yin, Z.R.[Zhao-Rui],
Qin, G.H.[Guang-Hua],
Guo, L.[Li],
Li, H.X.[Hong-Xia],
Integration of Satellite Precipitation Data and Deep Learning for
Improving Flash Flood Simulation in a Poor-Gauged Mountainous
Catchment,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Luo, T.[Ting],
Xie, Y.[Yanan],
Wang, R.[Rui],
Yu, X.Y.[Xue-Ying],
An Analytic Solution to Precipitation Attenuation Expression with
Spaceborne Synthetic Aperture Radar Based on Volterra Integral
Equation,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Ramadhan, R.[Ravidho],
Marzuki, M.[Marzuki],
Yusnaini, H.[Helmi],
Muharsyah, R.[Robi],
Suryanto, W.[Wiwit],
Sholihun, S.[Sholihun],
Vonnisa, M.[Mutya],
Battaglia, A.[Alessandro],
Hashiguchi, H.[Hiroyuki],
Capability of GPM IMERG Products for Extreme Precipitation Analysis
over the Indonesian Maritime Continent,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link
2201
BibRef
Guo, H.[Hao],
Li, M.[Min],
Nzabarinda, V.[Vincent],
Bao, A.[Anming],
Meng, X.C.[Xiang-Chen],
Zhu, L.[Li],
de Maeyer, P.[Philippe],
Assessment of Three Long-Term Satellite-Based Precipitation Estimates
against Ground Observations for Drought Characterization in
Northwestern China,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Liu, K.W.[Kang-Wen],
He, J.Y.[Jie-Ying],
Chen, H.N.[Hao-Nan],
Precipitation Retrieval from Fengyun-3D Microwave Humidity and
Temperature Sounder Data Using Machine Learning,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Zhang, D.S.[Da-Sheng],
Yang, M.X.[Ming-Xiang],
Ma, M.H.[Mei-Hong],
Tang, G.Q.[Guo-Qiang],
Wang, T.C.[Tse-Chun],
Zhao, X.[Xun],
Ma, S.Y.[Su-Ying],
Wu, J.[Jin],
Wang, W.[Wei],
Can GPM IMERG Capture Extreme Precipitation in North China Plain?,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Liao, L.[Liang],
Meneghini, R.[Robert],
GPM DPR Retrievals: Algorithm, Evaluation, and Validation,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
Dual-frequency precipitation radar (DPR) aboard the
Global Precipitation Measurement (GPM) satellite.
BibRef
Chua, Z.W.[Zhi-Weng],
Kuleshov, Y.[Yuriy],
Watkins, A.B.[Andrew B.],
Choy, S.[Suelynn],
Sun, C.[Chayn],
A Two-Step Approach to Blending GSMaP Satellite Rainfall Estimates
with Gauge Observations over Australia,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Kaur, I.[Inderpreet],
Eriksson, P.[Patrick],
Barlakas, V.[Vasileios],
Pfreundschuh, S.[Simon],
Fox, S.[Stuart],
Fast Radiative Transfer Approximating Ice Hydrometeor Orientation and
Its Implication on IWP Retrievals,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Zhao, Y.C.[Ying-Cheng],
Liu, X.C.[Xi-Chuan],
Pu, K.[Kang],
Ye, J.[Jin],
Xian, M.H.[Ming-Hao],
Research on the Method of Rainfall Field Retrieval Based on the
Combination of Earth-Space Links and Horizontal Microwave Links,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Li, Y.[Yu],
Pang, B.[Bo],
Ren, M.F.[Mei-Fang],
Shi, S.[Shulan],
Peng, D.Z.[Ding-Zhi],
Zhu, Z.F.[Zhong-Fan],
Zuo, D.[Depeng],
Evaluation of Performance of Three Satellite-Derived Precipitation
Products in Capturing Extreme Precipitation Events over Beijing,
China,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Gao, Y.B.[Yan-Bo],
Guan, J.P.[Ji-Ping],
Zhang, F.H.[Fu-Han],
Wang, X.D.[Xiao-Dong],
Long, Z.Y.[Zhi-Yong],
Attention-Unet-Based Near-Real-Time Precipitation Estimation from
Fengyun-4A Satellite Imageries,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Ye, X.Y.[Xiang-Yu],
Guo, Y.H.[Yu-Han],
Wang, Z.G.[Zhong-Gen],
Liang, L.F.[Liao-Feng],
Tian, J.[Jiayu],
Extensive Evaluation of Four Satellite Precipitation Products and
Their Hydrologic Applications over the Yarlung Zangbo River,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Yan, Y.[Yan],
Wang, G.H.[Gui-Hua],
Nanding, N.[Nergui],
Chen, W.[Weitian],
Hydrological Evaluation of Satellite-Based Precipitation Products in
Hunan Province,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Kidd, C.[Chris],
Matsui, T.[Toshi],
Blackwell, W.[William],
Braun, S.[Scott],
Leslie, R.[Robert],
Griffith, Z.[Zach],
Precipitation Estimation from the NASA TROPICS Mission:
Initial Retrievals and Validation,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Li, X.[Xianghu],
Ye, X.C.[Xu-Chun],
Xu, C.[Chengyu],
Assessment of Satellite-Based Precipitation Products for Estimating
and Mapping Rainfall Erosivity in a Subtropical Basin, China,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Jiang, S.H.[Shan-Hu],
Ding, Y.[Yu],
Liu, R.L.[Ruo-Lan],
Wei, L.Y.[Lin-Yong],
Liu, Y.T.[Ya-Ting],
Ren, M.M.[Ming-Ming],
Ren, L.L.[Li-Liang],
Assessing the Potential of IMERG and TMPA Satellite Precipitation
Products for Flood Simulations and Frequency Analyses over a Typical
Humid Basin in South China,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Dong, W.C.[Wen-Chang],
Wang, G.X.[Gen-Xu],
Guo, L.[Li],
Sun, J.Y.[Ju-Ying],
Sun, X.Y.[Xiang-Yang],
Evaluation of Three Gridded Precipitation Products in Characterizing
Extreme Precipitation over the Hengduan Mountains Region in China,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Woldegebrael, S.M.[Surafel M.],
Kidanewold, B.B.[Belete B.],
Melesse, A.M.[Assefa M.],
Seasonal Flow Forecasting Using Satellite-Driven Precipitation Data
for Awash and Omo-Gibe Basins, Ethiopia,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Xu, Y.[Yike],
Arevalo, J.[Jorge],
Ouyed, A.[Amir],
Zeng, X.B.[Xu-Bin],
Precipitation over the U.S. Coastal Land/Water Using Gauge-Corrected
Multi-Radar/Multi-Sensor System and Three Satellite Products,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Zhu, H.Q.[Hui-Qin],
Chen, S.[Sheng],
Li, Z.[Zhi],
Gao, L.[Liang],
Li, X.Y.[Xiao-Yu],
Comparison of Satellite Precipitation Products: IMERG and GSMaP with
Rain Gauge Observations in Northern China,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Kumar, S.[Sonu],
Amarnath, G.[Giriraj],
Ghosh, S.[Surajit],
Park, E.[Edward],
Baghel, T.[Triambak],
Wang, J.Y.[Jing-Yu],
Pramanik, M.[Malay],
Belbase, D.[Devesh],
Assessing the Performance of the Satellite-Based Precipitation
Products (SPP) in the Data-Sparse Himalayan Terrain,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Wang, H.F.[Hao-Fei],
Zhang, P.[Peng],
Yin, D.[Dekui],
Li, Z.Q.[Zheng-Qiang],
Shang, H.Z.[Hua-Zhe],
Xu, H.[Hanlie],
Shang, J.[Jian],
Gu, S.Y.[Song-Yan],
Hu, X.Q.[Xiu-Qing],
Shortwave Infrared Multi-Angle Polarization Imager (MAPI) Onboard
Fengyun-3 Precipitation Satellite for Enhanced Cloud Characterization,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link
2210
BibRef
Geng, L.C.[Liang-Chao],
Geng, H.T.[Huan-Tong],
Min, J.Z.[Jin-Zhong],
Zhuang, X.R.[Xiao-Ran],
Zheng, Y.[Yu],
AF-SRNet: Quantitative Precipitation Forecasting Model Based on
Attention Fusion Mechanism and Residual Spatiotemporal Feature
Extraction,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Dong, Z.Z.[Zi-Zhen],
Wang, L.[Lin],
Yang, R.[Ruowen],
Cao, J.[Jie],
Hu, P.[Peng],
Impact of Quasi-Biweekly Oscillation on Southeast Asian Cold Surge
Rainfall Monitored by TRMM Satellite Observation,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link
2211
BibRef
Kazemzadeh, M.[Majid],
Hashemi, H.[Hossein],
Jamali, S.[Sadegh],
Uvo, C.B.[Cintia B.],
Berndtsson, R.[Ronny],
Huffman, G.J.[George J.],
Detecting the Greatest Changes in Global Satellite-Based
Precipitation Observations,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Xie, Y.H.[Yan-Hui],
Chen, M.[Min],
Zhang, S.T.[Shu-Ting],
Shi, J.C.[Jian-Cheng],
Liu, R.X.[Rui-Xia],
Impacts of FY-4A Atmospheric Motion Vectors on the Henan 7.20
Rainstorm Forecast in 2021,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Wang, H.L.[He-Long],
Chen, W.L.[Wen-Long],
Hu, Z.K.[Zu-Kang],
Xu, Y.P.[Yue-Ping],
Shen, D.T.[Ding-Tao],
Optimal Rain Gauge Network Design Aided by Multi-Source Satellite
Precipitation Observation,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Simanjuntak, F.[Febryanto],
Jamaluddin, I.[Ilham],
Lin, T.H.[Tang-Huang],
Siahaan, H.A.W.[Hary Aprianto Wijaya],
Chen, Y.N.[Ying-Nong],
Rainfall Forecast Using Machine Learning with High Spatiotemporal
Satellite Imagery Every 10 Minutes,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Tang, X.[Xuan],
Li, H.X.[Hong-Xia],
Qin, G.H.[Guang-Hua],
Huang, Y.Y.[Yuan-Yuan],
Qi, Y.L.[Yong-Liang],
Evaluation of Satellite-Based Precipitation Products over Complex
Topography in Mountainous Southwestern China,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Lee, G.[Giha],
Nguyen, D.H.[Duc Hai],
Le, X.H.[Xuan-Hien],
A Novel Framework for Correcting Satellite-Based Precipitation
Products for Watersheds with Discontinuous Observed Data, Case Study
in Mekong River Basin,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link
2302
BibRef
Baig, F.[Faisal],
Abrar, M.[Muhammad],
Chen, H.[Haonan],
Sherif, M.[Mohsen],
Evaluation of Precipitation Estimates from Remote Sensing and
Artificial Neural Network Based Products (PERSIANN) Family in an Arid
Region,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Li, Y.P.[Yun-Ping],
Zhang, K.[Ke],
Bardossy, A.[Andras],
Shen, X.J.[Xiao-Ji],
Cheng, Y.[Yujia],
Evaluation and Error Decomposition of IMERG Product Based on Multiple
Satellite Sensors,
RS(15), No. 6, 2023, pp. 1710.
DOI Link
2304
BibRef
Li, Y.[Yu],
Pang, B.[Bo],
Zheng, Z.Q.[Zi-Qi],
Chen, H.M.[Hao-Ming],
Peng, D.Z.[Ding-Zhi],
Zhu, Z.F.[Zhong-Fan],
Zuo, D.P.[De-Peng],
Assessment of the Urban Extreme Precipitation by Satellite Estimates
over Mainland China,
RS(15), No. 7, 2023, pp. 1805.
DOI Link
2304
BibRef
Estébanez-Camarena, M.[Mónica],
Taormina, R.[Riccardo],
van de Giesen, N.[Nick],
ten Veldhuis, M.C.[Marie-Claire],
The Potential of Deep Learning for Satellite Rainfall Detection over
Data-Scarce Regions, the West African Savanna,
RS(15), No. 7, 2023, pp. 1922.
DOI Link
2304
BibRef
Huang, X.T.[Xing-Tao],
Wu, Z.H.[Zu-Hang],
Xie, Y.Q.[Yan-Qiong],
Zhang, Y.[Yun],
Zhang, L.F.[Li-Feng],
Zheng, H.[Hepeng],
Xiao, W.[Wupeng],
Precipitation Microphysics of Locally-Originated Typhoons in the
South China Sea Based on GPM Satellite Observations,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link
2306
BibRef
Pan, X.S.[Xin-Shun],
Wu, H.[Huan],
Chen, S.R.[Si-Rong],
Nanding, N.[Nergui],
Huang, Z.J.[Zhi-Jun],
Chen, W.T.[Wei-Tian],
Li, C.Q.[Chao-Qun],
Li, X.M.[Xiao-Meng],
Evaluation and Applicability Analysis of GPM Satellite Precipitation
over Mainland China,
RS(15), No. 11, 2023, pp. 2866.
DOI Link
2306
BibRef
Liu, Z.F.[Zhao-Fei],
Comprehensive Evaluation of High-Resolution Satellite Precipitation
Products over the Qinghai-Tibetan Plateau Using the New Ground
Observation Network,
RS(15), No. 13, 2023, pp. 3381.
DOI Link
2307
BibRef
Awasthi, N.[Nitesh],
Tripathi, J.N.[Jayant Nath],
Petropoulos, G.P.[George P.],
Gupta, D.K.[Dileep Kumar],
Singh, A.K.[Abhay Kumar],
Kathwas, A.K.[Amar Kumar],
Performance Assessment of Global-EO-Based Precipitation Products
against Gridded Rainfall from the Indian Meteorological Department,
RS(15), No. 13, 2023, pp. 3443.
DOI Link
2307
BibRef
Xiang, J.[Jie],
Wang, H.[Hao],
Li, Z.[Zhi],
Bu, Z.C.[Zhi-Chao],
Yang, R.[Rong],
Liu, Z.H.[Zhi-Hao],
Case Study on the Evolution and Precipitation Characteristics of
Southwest Vortex in China: Insights from FY-4A and GPM Observations,
RS(15), No. 16, 2023, pp. 4114.
DOI Link
2309
BibRef
Papacharalampous, G.[Georgia],
Tyralis, H.[Hristos],
Doulamis, N.[Nikolaos],
Doulamis, A.[Anastasios],
Ensemble Learning for Blending Gridded Satellite and Gauge-Measured
Precipitation Data,
RS(15), No. 20, 2023, pp. 4912.
DOI Link
2310
BibRef
Wu, H.[Hao],
Yong, B.[Bin],
Shen, Z.[Zhehui],
Spatial Reconstruction of Quantitative Precipitation Estimates
Derived from Fengyun-2G Geostationary Satellite in Northeast China,
RS(15), No. 21, 2023, pp. 5251.
DOI Link
2311
BibRef
Magoffin, R.H.[Rachel Huber],
Hales, R.C.[Riley C.],
Erazo, B.[Bolívar],
Nelson, E.J.[E. James],
Larco, K.[Karina],
Miskin, T.J.[Taylor James],
Evaluating the Performance of Satellite Derived Temperature and
Precipitation Datasets in Ecuador,
RS(15), No. 24, 2023, pp. 5713.
DOI Link
2401
BibRef
Campo, C.[Chloe],
Tamagnone, P.[Paolo],
Schumann, G.[Guy],
Automated Surface Runoff Estimation with the Spectral Unmixing of
Remotely Sensed Multispectral Imagery,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link
2401
BibRef
Peinó, E.[Eric],
Bech, J.[Joan],
Udina, M.[Mireia],
Polls, F.[Francesc],
Disentangling Satellite Precipitation Estimate Errors of Heavy
Rainfall at the Daily and Sub-Daily Scales in the Western
Mediterranean,
RS(16), No. 3, 2024, pp. 457.
DOI Link
2402
BibRef
Alharbi, R.S.[Raied Saad],
Dao, V.[Vu],
Arellano, C.J.[Claudia Jimenez],
Nguyen, P.[Phu],
Comprehensive Evaluation of Near-Real-Time Satellite-Based
Precipitation: PDIR-Now over Saudi Arabia,
RS(16), No. 4, 2024, pp. 703.
DOI Link
2402
BibRef
Chen, X.[Xingru],
Letu, H.[Husi],
Shang, H.Z.[Hua-Zhe],
Ri, X.[Xu],
Tang, C.Q.[Chen-Qian],
Ji, D.[Dabin],
Shi, C.[Chong],
Teng, Y.P.[Yu-Peng],
Rainfall Area Identification Algorithm Based on Himawari-8 Satellite
Data and Analysis of its Spatiotemporal Characteristics,
RS(16), No. 5, 2024, pp. 747.
DOI Link
2403
BibRef
Wang, Z.[Zunya],
Li, Q.Q.[Qing-Quan],
Towards Improved Satellite Data Utilization in China: Insights from
an Integrated Evaluation of GSMaP-GNRT6 in Rainfall Patterns,
RS(16), No. 5, 2024, pp. 755.
DOI Link
2403
BibRef
Huang, Y.[Yang],
Bao, Y.S.[Yan-Song],
Petropoulos, G.P.[George P.],
Lu, Q.F.[Qi-Feng],
Huo, Y.F.[Yan-Feng],
Wang, F.[Fu],
Precipitation Estimation Using FY-4B/AGRI Satellite Data Based on
Random Forest,
RS(16), No. 7, 2024, pp. 1267.
DOI Link
2404
BibRef
Zhang, J.B.[Jian-Bin],
Gao, Z.[Zhiqiu],
Li, Y.[Yubin],
Jiang, Y.[Yuncong],
Impacts of Fengyun-4A and Ground-Based Observation Data Assimilation
on the Forecast of Kaifeng's Heavy Rainfall (2022) and Mechanism
Analysis of the Event,
RS(16), No. 10, 2024, pp. 1663.
DOI Link
2405
BibRef
Torcasio, R.C.[Rosa Claudia],
Papa, M.[Mario],
del Frate, F.[Fabio],
Mascitelli, A.[Alessandra],
Dietrich, S.[Stefano],
Panegrossi, G.[Giulia],
Federico, S.[Stefano],
Data Assimilation of Satellite-Derived Rain Rates Estimated by Neural
Network in Convective Environments: A Study over Italy,
RS(16), No. 10, 2024, pp. 1769.
DOI Link
2405
BibRef
Nan, L.J.[Lin-Jiang],
Yang, M.X.[Ming-Xiang],
Wang, H.[Hao],
Wang, H.[Hejia],
Dong, N.P.[Ning-Peng],
An Innovative Correction-Fusion Approach for Multi-Satellite
Precipitation Products Conditioned by Gauge Background Fields over
the Lancang River Basin,
RS(16), No. 11, 2024, pp. 1824.
DOI Link
2406
BibRef
Gutierrez, S.R.M.[Silvia Roxana Mattos],
Fenta, A.A.[Ayele Almaw],
Meshesha, T.M.[Taye Minichil],
Belay, A.S.[Ashebir Sewale],
Unveiling the Accuracy of New-Generation Satellite Rainfall Estimates
across Bolivia's Complex Terrain,
RS(16), No. 12, 2024, pp. 2211.
DOI Link
2406
BibRef
Wang, B.[Bingli],
Cheng, W.[Wei],
Bao, Y.S.[Yan-Song],
Wang, S.D.[Shu-Dong],
Petropoulos, G.P.[George P.],
Fan, S.Y.[Shui-Yong],
Mao, J.J.[Jia-Jia],
Jin, Z.Q.[Zi-Qi],
Yang, Z.[Zihui],
Effects of Assimilating Ground-Based Microwave Radiometer and FY-3D
MWTS-2/MWHS-2 Data in Precipitation Forecasting,
RS(16), No. 14, 2024, pp. 2682.
DOI Link
2408
BibRef
Ji, X.P.[Xian-Pu],
Song, X.J.[Xiao-Jiang],
Guo, A.[Anboyu],
Liu, K.[Kai],
Cao, H.[Haijin],
Feng, T.[Tao],
Oceanic Precipitation Nowcasting Using a UNet-Based Residual and
Attention Network and Real-Time Himawari-8 Images,
RS(16), No. 16, 2024, pp. 2871.
DOI Link
2408
BibRef
Louise, L.,
Christian, B.,
Danny, L.S.,
Agnes, B.,
Seydou, B.T.,
Testing satellite rainfall estimates for yield simulation of a
rainfed cereal in West Africa,
MultiTemp15(1-4)
IEEE DOI
1511
crops
BibRef
Mahrooghy, M.[Majid],
Anantharaj, V.G.[Valentine G.],
Younan, N.H.[Nicolas H.],
Aanstoos, J.V.[James V.],
Optimal wavelet features for an infrared satellite precipitation
estimate algorithm,
AIPR10(1-6).
IEEE DOI
1010
BibRef
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Evaluation and Comparison of Rainfall Analysis, Rain, Precipitation Products .