195 citations as recorded by crossref.

1. ClimateBenchPress (v1.0): a benchmark for lossy compression of climate data T. Reichelt et al. https://doi.org/10.5194/gmd-19-5933-2026
2. spateGAN: Spatio‐Temporal Downscaling of Rainfall Fields Using a cGAN Approach L. Glawion et al. https://doi.org/10.1029/2023EA002906
3. The effect of altitude on the uncertainty of radar-based precipitation estimates over Switzerland E. Ghaemi et al. https://doi.org/10.1080/01431161.2023.2203339
4. Spatial and Temporal Evaluation of Radar Rainfall Nowcasting Techniques on 1,533 Events R. Imhoff et al. https://doi.org/10.1029/2019WR026723
5. A Short-Long Term Sequence Learning Network for Precipitation Nowcasting Z. Pan et al. https://doi.org/10.1109/TGRS.2024.3424250
6. Improving precipitation nowcasting via multiphysical parameter fusion in radar echo extrapolation Y. Ye et al. https://doi.org/10.1016/j.jhydrol.2026.134947
7. Rainfall Nowcasting Using Commercial Microwave Links R. Imhoff et al. https://doi.org/10.1029/2020GL089365
8. A Comparison of Sea Surface Temperature Perturbation Methods for a Convection Permitting Ensemble Prediction System Over the European Arctic R. Grote & A. Singleton https://doi.org/10.16993/tellusa.27
9. Stochastic Downscaling to Chaotic Weather Regimes using Spatially Conditioned Gaussian Random Fields with Adaptive Covariance R. Prudden et al. https://doi.org/10.1175/WAF-D-20-0217.1
10. Two-Stage Rainfall-Forecasting Diffusion Model X. Ling et al. https://doi.org/10.1109/LGRS.2024.3382241
11. Extreme Precipitation Nowcasting Using Multitask Latent Diffusion Models C. Li et al. https://doi.org/10.1109/TGRS.2025.3564916
12. Weather radar nowcasting of rainfall using optical flow with Recurrent All-Pairs Field Transforms (RAFT) J. Nielsen et al. https://doi.org/10.1016/j.atmosres.2026.109007
13. Long lead-time radar rainfall nowcasting method incorporating atmospheric conditions using long short-term memory networks K. Zhu et al. https://doi.org/10.3389/fenvs.2022.1054235
14. Climate Change Adaptations for Food Security in Vulnerable Areas of the Egyptian Nile—For Tackling the Overlooked Nexus Hazards of Hydrological Extremes and Waste Pollutions O. Chen et al. https://doi.org/10.3390/w13040412
15. 6G Visible Providing Advanced Weather Services for Autonomous Driving T. Sukuvaara et al. https://doi.org/10.3390/info15120805
16. Nowcasting of Convective Rainfall Using Volumetric Radar Observations S. Pulkkinen et al. https://doi.org/10.1109/TGRS.2020.2984594
17. Coupling strategies for precipitation nowcasting in China Q. Luo et al. https://doi.org/10.1080/02626667.2025.2587687
18. Forecasting of Local Lightning Using Spatial–Channel-Enhanced Recurrent Convolutional Neural Network W. Zhou et al. https://doi.org/10.3390/atmos15121478
19. Feature-based physics-guided diagnosis of rainfall formation, intensity and motion: independent IMERG–ERA5 validation of IRFMAD-Omega E. Asare https://doi.org/10.1016/j.pce.2026.104936
20. Incorporating IMERG satellite precipitation uncertainty into seasonal and peak streamflow predictions using the Hillslope Link hydrological model S. Hartke et al. https://doi.org/10.1016/j.hydroa.2023.100148
21. Finite-size local dimension as a tool for extracting geometrical properties of attractors of dynamical systems M. Bonte & S. Vannitsem https://doi.org/10.5194/npg-32-139-2025
22. Radar based nowcasting using TERLS C band radar A. Chhari et al. https://doi.org/10.1007/s00703-025-01104-9
23. Extreme and severe convective weather disasters: A dual-polarization radar nowcasting method based on physical constraints and a deep neural network model L. Wang et al. https://doi.org/10.1016/j.atmosres.2023.106750
24. A Radar-Based Fast Code for Rainfall Nowcasting over the Tuscany Region A. Mazza et al. https://doi.org/10.3390/rs17142467
25. Can AI be enabled to perform dynamical downscaling? A latent diffusion model to mimic kilometer-scale COSMO5.0_CLM9 simulations E. Tomasi et al. https://doi.org/10.5194/gmd-18-2051-2025
26. RadarDiff: A Conditional Diffusion Model With Time-Aware Context and Mixed Attention for Radar Echo Extrapolation H. Geng et al. https://doi.org/10.1109/JSTARS.2026.3722210
27. NowCasting-Nets: Representation Learning to Mitigate Latency Gap of Satellite Precipitation Products Using Convolutional and Recurrent Neural Networks M. Ehsani et al. https://doi.org/10.1109/TGRS.2022.3158888
28. Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data P. Costabile et al. https://doi.org/10.1029/2023WR034599
29. Enhanced radar echo extrapolation for precipitation nowcasting quality using the convolutional Kolmogorov–Arnold networks Q. Cheng et al. https://doi.org/10.1016/j.jhydrol.2025.134134
30. Precipitation nowcasting with radar data for evaluating multiple horizons using U-Net-based algorithm in Eastern Amazon R. Rocha et al. https://doi.org/10.1371/journal.pone.0342097
31. Precipitation Nowcasting Diffusion Model Based on Fluid Dynamics and Multisource Data D. Li et al. https://doi.org/10.1109/TGRS.2025.3631059
32. Impact of noise on landscapes and metrics generated with stream power models M. Morris & G. Roberts https://doi.org/10.5194/esurf-13-1003-2025
33. ThoR: A Motion-Dependent Physics-Informed Deep Learning Framework with Constraint-Centric Theory of Functional Connections for Rainfall Nowcasting K. Gia et al. https://doi.org/10.1038/s41598-025-26126-6
34. Skillful Radar-Based Heavy Rainfall Nowcasting Using Task-Segmented Generative Adversarial Network R. Wang et al. https://doi.org/10.1109/TGRS.2023.3295211
35. Improving Nowcasting of Intense Convective Precipitation by Incorporating Dual-Polarization Radar Variables into Generative Adversarial Networks P. Cai et al. https://doi.org/10.3390/s24154895
36. Advances in Deep-Learning-based Precipitation Nowcasting Techniques Q. ZHENG et al. https://doi.org/10.3724/j.1006-8775.2024.028
37. Probabilistic Forecast of Tropical Cyclone Precipitation Based on Diffusion Model P. Du et al. https://doi.org/10.3390/rs18111786
38. The Role of Weather Radar in Rainfall Estimation and Its Application in Meteorological and Hydrological Modelling—A Review Z. Sokol et al. https://doi.org/10.3390/rs13030351
39. TSPF-GAN: A lightweight temporal-spatial-pixel feature fusion GAN for radar-based precipitation nowcasting H. Zhang et al. https://doi.org/10.1007/s12145-025-02056-9
40. Assessing the Impact of Assimilated Remote Sensing Retrievals of Precipitation on Nowcasting a Rainfall Event in Attica, Greece A. Pappa et al. https://doi.org/10.3390/hydrology12080198
41. Event-Guided Spatiotemporal Transformer with Conditional Diffusion Refinement for High-Intensity Precipitation Nowcasting W. Li et al. https://doi.org/10.3390/rs18162771
42. S3NN: Exploring Stochastic Modeling in Precipitation Nowcasting Domain Z. Ma et al. https://doi.org/10.1109/TGRS.2026.3684546
43. A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts L. Harris et al. https://doi.org/10.1029/2022MS003120
44. Spatiotemporal Conditional Diffusion with a Vision-Language Model: Spatial Quality Modeling for Adaptive Fusion of Radar Forecasts X. Qian et al. https://doi.org/10.3390/atmos17101005
45. Hydrological and Hydrodynamic Responses to High-Resolution Diffusion-Enhanced Radar Rainfall Forcing in a Floodplain Reach of the Middle Yangtze River D. Feng et al. https://doi.org/10.3390/hydrology13060145
46. Four-hour thunderstorm nowcasting using a deep diffusion model for satellite data K. Dai et al. https://doi.org/10.1073/pnas.2517520122
47. Advancing very short-term rainfall prediction with blended U-Net and partial differential approaches J. Ha & J. Park https://doi.org/10.3389/feart.2023.1301523
48. Prior information assisted multi-scale network for precipitation nowcasting D. Song et al. https://doi.org/10.1016/j.cageo.2025.105851
49. Rain Motion Vectors Analysis From the Radar Network in Italy M. Montopoli et al. https://doi.org/10.1109/JSTARS.2024.3410031
50. Efficient 3D convolutional framework for rainfall nowcasting: performance–efficiency trade-offs and adaptation to data scarcity A. Abdelhalim et al. https://doi.org/10.1080/15481603.2026.2683939
51. Two-Stage Spatiotemporal Context Refinement Network for Precipitation Nowcasting D. Niu et al. https://doi.org/10.3390/rs13214285
52. Assessing Nowcast Models in the Central Mexico Region Using Radar and GOES-16 Satellite Data D. Islas-Flores & A. Magaldi https://doi.org/10.3390/atmos15020152
53. Nowcasting thunderstorm hazards using machine learning: the impact of data sources on performance J. Leinonen et al. https://doi.org/10.5194/nhess-22-577-2022
54. Real-time control enhanced blue-green infrastructure towards torrential events: A smart predictive solution H. Zhou et al. https://doi.org/10.1016/j.uclim.2023.101439
55. QWRF-Net: A quantum–wavelet framework with rectified flow for short-term precipitation field nowcasting Z. Wang et al. https://doi.org/10.1016/j.cageo.2026.106287
56. Brief communication: Training of AI-based nowcasting models for rainfall early warning should take into account user requirements G. Ayzel & M. Heistermann https://doi.org/10.5194/nhess-25-41-2025
57. scores: A Python package for verifying and evaluating models and predictions with xarray T. Leeuwenburg et al. https://doi.org/10.21105/joss.06889
58. A Systematic Modular Approach for the Coupling of Deep-Learning-Based Models to Forecast Urban Flooding Maps in Early Warning Systems J. Koltermann da Silva et al. https://doi.org/10.3390/hydrology11120215
59. Satellite based rainfall nowcasting using geospatial techniques B. Shukla et al. https://doi.org/10.1007/s00703-024-01049-5
60. Deep learning-based precipitation nowcasting integrating radar echoes and rain gauge data L. Li et al. https://doi.org/10.1016/j.jhydrol.2026.136210
61. Iterative graph deformation for aircraft trajectory planning considering ensemble forecasting of thunderstorms E. Andrés et al. https://doi.org/10.1016/j.trc.2022.103919
62. 3D-UNet-LSTM: A Deep Learning-Based Radar Echo Extrapolation Model for Convective Nowcasting S. Guo et al. https://doi.org/10.3390/rs15061529
63. A Deep Learning Method Integrating Meteorological Data for Heavy Precipitation Nowcasting in the Alps Region Y. Mu et al. https://doi.org/10.3390/app16094481
64. Designing an inundation monitoring and real-time urban flood forecasting system: a synthetic study V. Tran et al. https://doi.org/10.1016/j.jhydrol.2026.135520
65. Scale‐dependent blending of ensemble rainfall nowcasts and numerical weather prediction in the open‐source pysteps library R. Imhoff et al. https://doi.org/10.1002/qj.4461
66. Improved seasonal precipitation forecasts for the Blue Nile Basin: a deep learning approach R. Wiegels et al. https://doi.org/10.3389/fclim.2026.1691030
67. SFNL-Former: A novel spatial-frequency non-local network for precipitation forecast H. Wang et al. https://doi.org/10.1016/j.rcradv.2026.200381
68. Value of Spatially Distributed Rainfall Design Events—Creating Basin-Scale Stochastic Design Storm Ensembles V. Lindgren et al. https://doi.org/10.3390/w15173066
69. SSRF-Net: A Stagewise Scheduled Rainfall Forecasting Network With an Asymmetric Architecture W. Luo et al. https://doi.org/10.1109/TGRS.2025.3621627
70. GenLUPIN: Physics-Informed Score-Based Diffusion in a Lagrangian Framework for Spectrally Consistent Precipitation Nowcasting M. Archi Maggaukang et al. https://doi.org/10.1109/ACCESS.2026.3730270
71. Pyrad: A Real-Time Weather Radar Data Processing Framework Based on Py-ART J. Figueras i Ventura et al. https://doi.org/10.5334/jors.330
72. Use of Deep Learning for Weather Radar Nowcasting J. Cuomo & V. Chandrasekar https://doi.org/10.1175/JTECH-D-21-0012.1
73. Urban-Catchment-Scale Evaluation of Rainfall–Runoff Predictions Based on Weather Radar Nowcasts J. Nielsen et al. https://doi.org/10.1061/JHYEFF.HEENG-6896
74. Nowcasting tracks of severe convective storms in West Africa from observations of land surface state C. Taylor et al. https://doi.org/10.1088/1748-9326/ac536d
75. Solar radiation nowcasting based on geostationary satellite images and deep learning models Y. Cui et al. https://doi.org/10.1016/j.solener.2024.112866
76. RISE‐net: A deep‐learning model for improving fine‐scale summer precipitation nowcasting in the Beijing–Tianjin–Hebei region Y. Xie et al. https://doi.org/10.1002/qj.70202
77. RainForest: a random forest algorithm for quantitative precipitation estimation over Switzerland D. Wolfensberger et al. https://doi.org/10.5194/amt-14-3169-2021
78. Spatiotemporal Precipitation Nowcasting for Different Rain Types Using C-Band Dual-Polarimetric Radar Observations in Indian Core Monsoon Zone S. Das et al. https://doi.org/10.1109/LGRS.2025.3636412
79. An Enhanced Nonlinear Grid Transformation Method for Weather Radar Echo Extrapolation T. Yang et al. https://doi.org/10.3390/rs18172865
80. A look at the mathematics of radar-based nowcasting T. Buriol et al. https://doi.org/10.5902/2179460X87224
81. Multi-Channel Spectral Band Adjustment Factors for Thermal Infrared Measurements of Geostationary Passive Imagers D. Piontek et al. https://doi.org/10.3390/rs15051247
82. Experimental Study on Generative Adversarial Network for Precipitation Nowcasting C. Luo et al. https://doi.org/10.1109/TGRS.2022.3177625
83. Probabilistic Attenuation Nowcasting for the 5G Telecommunication Networks J. Pudashine et al. https://doi.org/10.1109/LAWP.2021.3068393
84. Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events G. Franch et al. https://doi.org/10.3390/atmos11030267
85. Improving U-Nets for spatiotemporal deep learning of ensemble-based atmospheric composition forecasts C. Kofroth et al. https://doi.org/10.1088/3049-4753/aeb0ab
86. Nowcasting of Meteorological Parameters and Weather Phenomena: Tools, Capabilities, and Constraints D. Kiktev et al. https://doi.org/10.3103/S1068373924070069
87. Short-term rainfall forecasting using cumulative precipitation fields from station data: a probabilistic machine learning approach D. Pirone et al. https://doi.org/10.1016/j.jhydrol.2022.128949
88. Deterministic nowcasting of geostationary satellite infrared brightness temperature using 3D U-Net diffusion model V. Afzali Gorooh et al. https://doi.org/10.1038/s41598-025-34207-9
89. Short-term solar irradiance forecasting at high spatiotemporal resolution over southern China using deep learning and Fengyun-4B satellite data Y. Qin & C. Lu https://doi.org/10.1080/01431161.2026.2716400
90. Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts E. Casellas et al. https://doi.org/10.1002/qj.4121
91. Enhancing rainfall prediction accuracy through image fusion of radar and numerical weather prediction models J. Byun et al. https://doi.org/10.1016/j.eswa.2025.130516
92. Using Conditional Generative Adversarial 3-D Convolutional Neural Network for Precise Radar Extrapolation C. Wang et al. https://doi.org/10.1109/JSTARS.2021.3083647
93. Advection-Free Convolutional Neural Network for Convective Rainfall Nowcasting J. Ritvanen et al. https://doi.org/10.1109/JSTARS.2023.3238016
94. RAP-Net: Region Attention Predictive Network for precipitation nowcasting Z. Zhang et al. https://doi.org/10.5194/gmd-15-5407-2022
95. Skilful nowcasting of extreme precipitation with NowcastNet Y. Zhang et al. https://doi.org/10.1038/s41586-023-06184-4
96. Ensemble Representation of Satellite Precipitation Uncertainty Using a Nonstationary, Anisotropic Autocorrelation Model S. Hartke et al. https://doi.org/10.1029/2021WR031650
97. A spatiotemporal mixed-enhanced generative adversarial network for radar-based precipitation nowcasting L. He et al. https://doi.org/10.1016/j.cageo.2025.105919
98. Next-gen storm nowcasting: harnessing satellite-based radar reflectivity over India A. Mishra et al. https://doi.org/10.1007/s00704-025-05650-5
99. DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties B. Harnist et al. https://doi.org/10.5194/gmd-17-3839-2024
100. Physical‐Dynamic‐Driven AI‐Synthetic Precipitation Nowcasting Using Task‐Segmented Generative Model R. Wang et al. https://doi.org/10.1029/2023GL106084
101. Performance Comparison between Deep Learning and Optical Flow-Based Techniques for Nowcast Precipitation from Radar Images M. Marrocu & L. Massidda https://doi.org/10.3390/forecast2020011
102. Temporal Super-Resolution, Ground Adjustment, and Advection Correction of Radar Rainfall Using 3-D-Convolutional Neural Networks J. Polz et al. https://doi.org/10.1109/TGRS.2024.3371577
103. Rainfall nowcasting by integrating radar and rain gauge data with machine learning for Ischia Island, Italy F. Taromideh et al. https://doi.org/10.1016/j.ejrh.2025.102273
104. PCFNet: frequency- and field-guided dual-polarization radar echo image sequence prediction T. Feng et al. https://doi.org/10.1007/s11760-026-05666-y
105. Pixel-CRN: A New Machine Learning Approach for Convective Storm Nowcasting W. Zhang et al. https://doi.org/10.1109/TGRS.2023.3267976
106. Enhancing severe weather predictions with the I-ConvGRU model: An iterative approach for radar echo time series through ConvGRU and RainNet integration R. Yang et al. https://doi.org/10.2166/hydro.2024.068
107. A quest for precipitation attractors in weather radar archives L. Foresti et al. https://doi.org/10.5194/npg-31-259-2024
108. Rainfall nowcasting models: state of the art and possible future perspectives D. De Luca et al. https://doi.org/10.1080/02626667.2025.2490780
109. HybridFlow: A Hybrid Velocity Generation Framework for Precipitation Nowcasting X. Ling et al. https://doi.org/10.1109/TGRS.2025.3646177
110. Large‐Sample Evaluation of Radar Rainfall Nowcasting for Flood Early Warning R. Imhoff et al. https://doi.org/10.1029/2021WR031591
111. Deep learning enables super-resolution hydrodynamic flooding process modeling under spatiotemporally varying rainstorms J. He et al. https://doi.org/10.1016/j.watres.2023.120057
112. Intraday probabilistic forecasts of surface solar radiation with cloud scale-dependent autoregressive advection A. Carpentieri et al. https://doi.org/10.1016/j.apenergy.2023.121775
113. Applications of directional wavelets, Universal Multifractals and anisotropic scaling in ensemble nowcasting; a review of methods with case‐studies R. Scovell https://doi.org/10.1002/qj.3780
114. Enhancing Rainfall Nowcasting Using Generative Deep Learning Model with Multi-Temporal Optical Flow J. Ha & H. Lee https://doi.org/10.3390/rs15215169
115. Exploiting radar polarimetry for nowcasting thunderstorm hazards using deep learning N. Rombeek et al. https://doi.org/10.5194/nhess-24-133-2024
116. Alleviating urban pluvial floods via dual-use water plazas orchestrated by predictive algorithms H. Zhou et al. https://doi.org/10.1016/j.jhydrol.2024.131695
117. Implications of spatially distributed rainfall design events on urban hydrological response across advection scenarios V. Lindgren et al. https://doi.org/10.1080/1573062X.2025.2541797
118. Enhancing Spatial Variability Representation of Radar Nowcasting with Generative Adversarial Networks A. Gong et al. https://doi.org/10.3390/rs15133306
119. A Customized Multi‐Scale Deep Learning Framework for Storm Nowcasting S. Yang & H. Yuan https://doi.org/10.1029/2023GL103979
120. Rad-cGAN v1.0: Radar-based precipitation nowcasting model with conditional generative adversarial networks for multiple dam domains S. Choi & Y. Kim https://doi.org/10.5194/gmd-15-5967-2022
121. On the suitability of a convolutional neural network based RCM-emulator for fine spatio-temporal precipitation A. Doury et al. https://doi.org/10.1007/s00382-024-07350-8
122. PCEED-Net: A Physics-Constrained Enhanced Encoder–Decoder Network for Precipitation Nowcasting H. Chi et al. https://doi.org/10.1109/TGRS.2026.3660822
123. Spacetime Separable Latent Diffusion Model With Intensity Structure Information for Precipitation Nowcasting X. Ling et al. https://doi.org/10.1109/TGRS.2024.3444789
124. Nowcasting convective cores using deep learning J. Ahmad et al. https://doi.org/10.1002/qj.70284
125. Fully differentiable Lagrangian convolutional neural network for physics-informed precipitation nowcasting P. Pavlík et al. https://doi.org/10.1016/j.acags.2025.100296
126. Global spatio-temporal ERA5 precipitation downscaling to km and sub-hourly scale using generative AI L. Glawion et al. https://doi.org/10.1038/s41612-025-01103-y
127. Nationwide Radar-Based Precipitation Nowcasting—A Localization Filtering Approach and its Application for Germany R. Reinoso-Rondinel et al. https://doi.org/10.1109/JSTARS.2022.3144342
128. Deep learning model based on multi-scale feature fusion for precipitation nowcasting J. Tan et al. https://doi.org/10.5194/gmd-17-53-2024
129. Spatiotemporal Prediction of Radar Echoes Based on ConvLSTM and Multisource Data M. Lu et al. https://doi.org/10.3390/rs15051279
130. GPTCast: a weather language model for precipitation nowcasting G. Franch et al. https://doi.org/10.5194/gmd-18-5351-2025
131. Coupling a Neural Network with a Spatial Downscaling Procedure to Improve Probabilistic Nowcast for Urban Rain Radars M. Marrocu & L. Massidda https://doi.org/10.3390/forecast4040046
132. Objective Nowcasting of Severe Convective Weather: Technological Progress and Outlook K. Zhou et al. https://doi.org/10.1007/s13351-025-4907-6
133. DSTP: A Dual-Domain Spatio-Temporal Predictive Network for weather radar precipitation nowcasting H. Wang et al. https://doi.org/10.1016/j.atmosres.2026.109266
134. Real-time bias correction of rainfall nowcasts using biward tracking method W. Na & C. Yoo https://doi.org/10.1016/j.jhydrol.2023.129642
135. WITHDRAWN: Incorporating IMERG satellite precipitation uncertainty into seasonal and peak streamflow predictions using the Hillslope Link hydrological model S. Hartke et al. https://doi.org/10.1016/j.jhydrol.2022.129012
136. Review on deep learning quantitative precipitation nowcasting: Advances and challenges D. Li et al. https://doi.org/10.1016/j.eswa.2025.130775
137. Fusion of multi-source precipitation records via coordinate-based generative models S. Sun et al. https://doi.org/10.1038/s41467-025-67987-9
138. An Evolution-Unet-ConvNeXt approach based on feature fusion for enhancing the accuracy of short-term precipitation forecasting Y. Su et al. https://doi.org/10.1016/j.atmosres.2025.107984
139. Reliable precipitation nowcasting using probabilistic diffusion models C. Nai et al. https://doi.org/10.1088/1748-9326/ad2891
140. Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process J. Yan et al. https://doi.org/10.5194/hess-25-3819-2021
141. Weather Radar in Complex Orography U. Germann et al. https://doi.org/10.3390/rs14030503
142. NowPrecip 2: Precipitation nowcasting in the complex terrain of Switzerland. Part II: Verification A. Ntoumos et al. https://doi.org/10.1002/qj.70181
143. Spread/error relationship and spatial error representation in precipitation nowcasting: comparison of STEPS and generative AI M. Bonte et al. https://doi.org/10.5194/wcd-7-1837-2026
144. An Improved Precipitation Nowcasting Algorithm Based on COTREC Method Z. Yang et al. https://doi.org/10.1109/TGRS.2024.3446826
145. A Hybrid Approach to Physical and Deep Learning Models for Radar-Based Precipitation Nowcasting H. Kim et al. https://doi.org/10.1109/TGRS.2025.3560454
146. Precipitation Nowcasting Based on Deep Learning over Guizhou, China D. Kong et al. https://doi.org/10.3390/atmos14050807
147. STAMP-GAN: A Spatiotemporal Attention-Modulated Generative Adversarial Network for Precipitation Nowcasting X. Ma et al. https://doi.org/10.3390/rs18173026
148. A characterisation of Alpine mesocyclone occurrence M. Feldmann et al. https://doi.org/10.5194/wcd-2-1225-2021
149. RoadSurf 1.1: open-source road weather model library V. Karsisto https://doi.org/10.5194/gmd-17-4837-2024
150. Morphology–aware spatiotemporal prediction of cumulonimbus–related radar echoes using CSDP–Net D. Wang et al. https://doi.org/10.1007/s00704-026-06276-x
151. Evaluating pySTEPS optical flow algorithms for convection nowcasting over the Maritime Continent using satellite data J. Smith et al. https://doi.org/10.5194/nhess-24-567-2024
152. A comprehensive implementation of the log, Box-Cox and log-sinh transformations for skewed and censored precipitation data Z. Huang et al. https://doi.org/10.1016/j.jhydrol.2023.129347
153. A Strategy to set up Test Dataset and Evaluation Benchmark for Radar Nowcasting of Precipitation in Italy C. Annella et al. https://doi.org/10.1109/JSTARS.2025.3568185
154. Satellite-Based Nowcasting of West African Mesoscale Storms Has Skill at up to 4-h Lead Time R. Burton et al. https://doi.org/10.1175/WAF-D-21-0051.1
155. TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting G. Franch et al. https://doi.org/10.1038/s41597-020-0574-8
156. Relevance of merging radar and rainfall gauge data for rainfall nowcasting in urban hydrology B. Shehu & U. Haberlandt https://doi.org/10.1016/j.jhydrol.2020.125931
157. Precipitation nowcasting using ground radar data and simpler yet better video prediction deep learning D. Han et al. https://doi.org/10.1080/15481603.2023.2203363
158. Skilful precipitation nowcasting using deep generative models of radar S. Ravuri et al. https://doi.org/10.1038/s41586-021-03854-z
159. Smart roofs featuring predictive control: An upgrade for mitigating precipitation extreme-induced pluvial floods H. Zhou et al. https://doi.org/10.1016/j.jenvman.2024.121504
160. Precipitation Nowcasting Using Diffusion Transformer With Causal Attention C. Li et al. https://doi.org/10.1109/TGRS.2024.3510693
161. Assessment of two approaches for very short range precipitation prediction for a convection-dominant period at different scales E. Ghaemi et al. https://doi.org/10.1016/j.atmosres.2024.107522
162. Terrain-Modulated Multi-Polarimetric Fusion for Efficient Volumetric Radar Nowcasting Y. Ye et al. https://doi.org/10.3390/rs18213707
163. An open-source framework for mosaic radar-based rainfall estimation across Thailand's watersheds N. Mahavik et al. https://doi.org/10.1007/s41324-025-00606-3
164. Application of optical flow technique to short-term rainfall forecast for some synoptic patterns in Vietnam N. Thu et al. https://doi.org/10.1007/s00704-024-05277-y
165. Three-Dimensional Gridded Radar Echo Extrapolation for Convective Storm Nowcasting Based on 3D-ConvLSTM Model N. Sun et al. https://doi.org/10.3390/rs14174256
166. Nowcasting of rain with Doppler weather radar – A comparative strategy for complex orography S. Chakraborty et al. https://doi.org/10.1007/s12040-025-02649-4
167. Diagnosing cloudbursts over Indian megacities near land-sea boundary during the 2025 Monsoon: Multi-platform observations, atmospheric drivers and model predictability G. Rakshit et al. https://doi.org/10.1016/j.atmosres.2026.109074
168. Research on Radar Echo Extrapolation Method by Fusing Environment Grid Point Field Information Y. Wen et al. https://doi.org/10.3390/atmos14060980
169. Visualization of radar-observed rainfall for hydrological risk assessment J. Olsson et al. https://doi.org/10.5194/asr-18-59-2021
170. Physics-Guided Latent Diffusion Model for Intensity- and Extremity-Aware VIL Nowcasting C. Gao et al. https://doi.org/10.1109/JSTARS.2026.3694114
171. Toward the Predictability of a Radar-Based Nowcasting System for Different Precipitation Systems L. Han et al. https://doi.org/10.1109/LGRS.2022.3185031
172. The GRAPES evaluation tools based on Python (GetPy) B. Zhao et al. https://doi.org/10.1007/s42514-022-00127-7
173. Operational Assessment of High Resolution Weather Radar Based Precipitation Nowcasting System B. Raj et al. https://doi.org/10.3390/atmos15020154
174. Enhancing consistency of microphysical properties of precipitation across the melting layer in dual-frequency precipitation radar data K. Mroz et al. https://doi.org/10.5194/amt-17-1577-2024
175. Key factors for quantitative precipitation nowcasting using ground weather radar data based on deep learning D. Han et al. https://doi.org/10.5194/gmd-16-5895-2023
176. Precipitation nowcasting using transformer-based generative models and transfer learning for improved disaster preparedness M. Piran et al. https://doi.org/10.1016/j.jag.2024.103962
177. Effective training strategies for deep-learning-based precipitation nowcasting and estimation J. Ko et al. https://doi.org/10.1016/j.cageo.2022.105072
178. Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall J. Ritvanen et al. https://doi.org/10.5194/gmd-18-1851-2025
179. Application of Radar-Based Precipitation Data Improves the Effectiveness of Urban Inundation Forecasting D. Tri et al. https://doi.org/10.3390/su16093736
180. MS-EdgeCast: A Dual-Stage Framework With a Multiscale Convolutional Recurrent Network and Edge-Guided Diffusion for Convective Storm Nowcasting W. Zhang et al. https://doi.org/10.1109/TGRS.2026.3655487
181. Reliability of Ensemble Climatological Forecasts Z. Huang et al. https://doi.org/10.1029/2023WR034942
182. Multiscale Representation of Radar Echo Data Retrieved through Deep Learning from Numerical Model Simulations and Satellite Images M. Zhu et al. https://doi.org/10.3390/rs15143466
183. Assessment of deterministic and probabilistic precipitation nowcasting techniques over New York metropolitan area A. Tounsi et al. https://doi.org/10.1016/j.envsoft.2023.105803
184. Two-Stage UA-GAN for Precipitation Nowcasting L. Xu et al. https://doi.org/10.3390/rs14235948
185. Lagrangian Integro-Difference Equation Model for Precipitation Nowcasting S. Pulkkinen et al. https://doi.org/10.1175/JTECH-D-21-0013.1
186. Shallow- and deep-convection characteristics in the greater Houston, Texas, area using cell tracking methodology K. Tuftedal et al. https://doi.org/10.5194/acp-24-5637-2024
187. Have you ever seen the rain? Observing a record convective rainfall with national and local monitoring networks and opportunistic sensors L. Petersson Wårdh et al. https://doi.org/10.5194/amt-19-461-2026
188. Precipitation nowcasting of satellite data using physically aligned neural networks A. Catão et al. https://doi.org/10.1017/eds.2026.10041
189. Clustering enhancement in multidimensional space via restricted dissimilarity functions on $$L^n$$ for rainstorm radar images I. Pérez-del-Notario et al. https://doi.org/10.1007/s40314-026-03712-6
190. Hybrid physics-AI outperforms numerical weather prediction for extreme precipitation nowcasting P. Das et al. https://doi.org/10.1038/s41612-024-00834-8
191. Mitigating blade erosion damage through nowcast-driven erosion-safe mode control N. Barfknecht et al. https://doi.org/10.1088/1742-6596/2767/3/032001
192. Comparative study of cloud evolution for rainfall nowcasting using AI-based deep learning algorithms X. Jiang et al. https://doi.org/10.1016/j.jhydrol.2024.131593
193. Cross-Regional Transfer Learning for Radar Echo Extrapolation in Northwestern Xinjiang, Western China K. Zeng et al. https://doi.org/10.3390/rs18183209
194. NLED: Nonlocal Echo Dynamics Network for Radar Echo Extrapolation T. Chen et al. https://doi.org/10.1109/TGRS.2022.3197833
195. GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement K. Zheng et al. https://doi.org/10.5194/gmd-17-399-2024