This Dataset contains raindrop data: hyd_diameter (mm), hyd_fall_speed (m s-1), hyd_axis_ratio_3d, hyd_azimuth_angle (deg), hyd_zenith_angle (deg), rain_rate (mm h-1) , hyd_U_speed (m s-1) and turbulence_dissipation_rate (m2 s-3). The data is in Python numpy ('.npy') format and can be read with the following Python code:import numpy as nphyd_diameter_read = np.load(path_data_save + 'hyd_diameter.npy')

Autonomous vehicles use cameras as one of the primary sources of information about the environment. Adverse weather conditions such as raindrops, snow, mud, and others, can lead to various image artifacts. Such artifacts significantly degrade the quality and reliability of the obtained visual data and can lead to accidents if they are not detected in time.

We present an ongoing work on a new dataset for training and assessing vision algorithms' performance for different tasks of image raindrops detection on either camera lens or windshield. At the moment, it contains 8190 images, of which 3390 contain raindrops.

Images were labeled by outlining artifacts with polygons. Labeling results are stored in JSON format. Besides, binary masks were generated from this markup, which are also presented in the dataset for convenience. White color denotes an artifact area.

For a fast download please use zenodo-get. To install it use the following commands:

pip install zenodo-get
zenodo_get https://zenodo.org/record/4680442 --output-dir=RaindropsOnWindshield

This research prioritisation project contains underlying data and extended data and both available in a PDF Document.The copy of statements received as part of Phase I Survey is available to download via an excel format.

Surface observations include surface temperature, dew point temperature, wet-bulb temperature and weather phenomenon data from 2168 surface stations at 00:00, 06:00, 12:00, and 18:00 UTC for the period January 2000 to December 2019 when freezing rain occurred. Sounding profile data were collected from 89 sounding stations across China at 00:00 and 12:00 UTC for freezing rain events, and can be directly driven by a raindrop temperature model to calculate the temperature of raindrops as they fall from the cloud base. The borderline_precip include the sounding profiles of the rain and freezing rain events when the surface temperature near 0℃(-1~1℃).

Rain drop size distribution measurements from a tropical site, Pune, India (JJAS, 2013-2015).

Raindrop is a set of image pairs, where each pair contains exactly the same background scene, yet one is degraded by raindrops and the other one is free from raindrops. To obtain this, the images are captured through two pieces of exactly the same glass: one sprayed with water, and the other is left clean. The dataset consists of 1,119 pairs of images, with various background scenes and raindrops. They were captured with a Sony A6000 and a Canon EOS 60.

This dataset contains the mean raindrop volume diameter Dmv, the total raindrop concentration Nr, the rain water content RWC and the vertical wind speed w obtained by a retrieval technique combining the observations from two collocated and zenith pointing Ka and W-band radars at two sites in Finland (07/06/2014) and Oklahoma (12/06/2011). How to cite: Niquet, L., Tridon, F., & Planche, C. (2024). Evaluation of the representation of raindrops self-collection and breakup processes in 2-moment bulk models using multifrequency radar retrievals [Data set]. OPGC, LaMP. https://doi.org/10.25519/1GB0-1C84

Dataset Card for Dataset Name

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

  Dataset Description

NightDrop: the first large-scale nighttime raindrop dataset featuring diverse raindrop densities and a wide range of lightting conditions. \t \NightDrop is a Dataset (CC-BY-4.0) for raindrop removal in low-light and overexposed nighttime scenes, including well-lit, low-light, and overexposed… See the full description on the dataset page: https://huggingface.co/datasets/hugginganonys/NightDrop.

The authors are: Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka ZitnikThis PAM dataset is a subset of PAMAP2 dataset (public accessable). - Paper: Graph-Guided Network For Irregularly Sampled Multivariate Time Series, (Accepted by ICLR 2022) - Paper link: https://openreview.net/pdf?id=Kwm8I7dU-l5- Github repo: https://github.com/mims-harvard/Raindrop- Project website: https://zitniklab.hms.harvard.edu/projects/Raindrop/

The deposited data were collected as part of the research project entitled ‘Zjawisko rozbryzgu jako mechanizm transportu mikroorganizmów glebowych’, eng. ‘Splash phenomenon as a mechanism of transportation of soil microorganisms’, financed by the National Science Centre, Poland as part of the project under the OPUS 23 call (project no. 2022/45/B/NZ9/00605). The project is concerned with the quantitative and qualitative description of bacterial transport during the soil splash phenomenon induced by the impact of a raindrops. The accompanying data relate to the characterisation of aspects of falling drops that are the primary driver of splash process and that may affect microbial transport.The research was conducted from March 2024 to June 2024 at the Institute of Agrophysics, Polish Academy of Sciences in Lublin (Poland). The collection contains: 1) the drop characteristics (diameter, velocity) measured by two disdrometers, 2) the drop characteristics (diamater, velocity, shape descriptors) measured by high-speed cameras. The data were compiled on the basis of laboratory tests.The dataset consists of the following files:A) Drop characteristics from disdrometers.zip – data of diameter (A_1.xlsx) and velocity (A_2.xlsx) of falling drops differentiated by the size of the falling drops and the height of their fall. The data were obtained by the Thies Clima Laser Precipitation Monitor (Adolf Thies, Germany) and Parsivel2 (OTT, Germany) disdrometers. A detailed description can be found in the attached file (ReadmeA.txt).B) Drop characteristics from high-speed cameras.zip – data of diameter (B_1.xlsx), velocity (B_2.xlsx and B_5).xlsx) and shape descriptors (B_3.xlsx and B_4 xlsx) of falling drops differentiated by the size of the falling drops and the height of their fall, as well as simulated wind. The data were obtained by the single Phantom Miro M310 high-speed camera (Vision Research, USA) or the set of two Phantom Miro M310 high-speed cameras (Vision Research, USA) combined with particle tracking velocimetry module (PTV). A detailed description can be found in the attached file (ReadmeB.txt).

Dataset supporting publication in the Journal of Fluid Mechanics by Murphy et al (2015). This data set contains raw data and analysis of an experimental laboratory study examining splash behavior and oily marine aerosol production by raindrops impacting oil slicks. The raw data consist of .tif images from high speed visualizations (used to describe and classify splash processes) and high speed holography (used to measure airborne droplet sizes). Images (.tif) used for measurement of interfacial and surface tension of various oils via the pendant drop method are also included, as are Excel spreadsheets with analysis of the data.

This dataset is about books. It has 1 row and is filtered where the book is Can a raindrop be in pain? : a consideration of the location & pervasiveness of pain and other states of feeling. It features 7 columns including author, publication date, language, and book publisher.

This dataset is used to make figures for the paper entitled “Observational Evidence of the Environmental Impacts on Raindrop Size Distribution in East China” submitted to Geophysical Research Letters in June 2022. It contains the disdrometer and automatic weather station observations in minute, hourly, daily scales, and also the training and testing samples for machine learning.

A dataset of mentions, growth rate, and total volume of the keyphrase 'Virtual Raindrop' over time.

The experimental data were used to study effects of raindrop impact on the resistance characteristics of sheet flow. The flume was 6.0 m long, 0.25 m wide, and 0.3 m deep. The bed surface of the flume was covered by a smooth and uniform layer of mortar (sand to cement mixing ratio 2:1). The flume surface was then sheltered with a nylon gauze sheet, which was fixed at 0.4 m above the flume surface to reduce the raindrop impact. Flume tests with four rainfall intensities and eight slope angles were simulated for each scenario. The four simulated raindrop characteristics of with and without gauze screen are located in the folder. The experimental data mainly include mean flow velocity and depth of whole flume. The surface flow velocity was measured in each segment by using a dye tracing method with KMnO4. The whole flume was equally divided into three segments: downslope (0-2 m), middle slope (2-4 m) and upslope (4-6 m). The surface flow velocity and flow depth were measured in each segment. The surface velocity of the whole flume was mean surface velocity of the three segments. Flow depth was measured in each 1 m by using a water level measuring needle. There were six observation points for measuring flow depth, positioned at 0.5, 1.5, 2.5, 3.5, 4.5, 5.5 m along the flume center line. The mean flow depth of the whole flume was the average of all measured points.

This is the dataset for the publication [1]. This dataset contains:
1) Training dataset (train_data.pkl)
2) Independent validation dataset (test_data.pkl)

This dataset was also used for the publication [2]. The training and validation datasets were merged in [2].

References

[1] Shin, K., Kim, K., Song, J. J., & Lee, G. (2024). Polarimetric Retrieval of Raindrop Size Distribution: Double‐Moment Normalization Approach and Machine Learning Techniques. Geophysical Research Letters, 51(1), e2023GL106057. https://doi.org/10.1029/2023GL106057

[2] Tapiador, F. J., Shin, K., Leganés, L. J., Lim, K.-S., Juárez, G., Bang, W., et al. (2025). A Physically Consistent Particle Size Distribution Modelling of the Microphysics of Precipitation for Weather and Climate Models. Submitted.

This dataset provides information about the number of properties, residents, and average property values for Raindrop Drive cross streets in Boise, ID.

hail data detected by the Parsivel laser raindrop spectrometer where time is local time（UTC+8）, and CodeMETAR = ’GR’ and CodeNWS = ’A’, that the particle is hail or graupel.

The global raindrop spectrometer market is experiencing robust growth, driven by increasing demand for accurate precipitation measurements in weather forecasting, hydrological research, and agricultural applications. The market size in 2025 is estimated at $150 million, exhibiting a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033. This growth is fueled by advancements in sensor technology, leading to more precise and reliable data acquisition. Furthermore, the rising adoption of automated weather stations and the increasing need for real-time hydrological data are key market drivers. The market is segmented by type (optical, disdrometer), application (weather forecasting, agriculture, hydrology), and region (North America, Europe, Asia-Pacific, etc.). Key players like Hach, FRT, and several Chinese technology companies are actively contributing to market expansion through innovation and strategic partnerships. Challenges include the relatively high cost of advanced spectrometers, limiting broader adoption in resource-constrained regions. However, ongoing technological improvements are expected to decrease production costs over time, making the technology more accessible. Future growth will be significantly influenced by government investments in weather infrastructure and the expanding adoption of precision agriculture techniques, which rely heavily on accurate rainfall data for optimized irrigation and crop management. The increasing prevalence of extreme weather events globally further emphasizes the crucial role of accurate rainfall measurement, thereby bolstering market demand for reliable and efficient raindrop spectrometers.

This dataset provides information about the number of properties, residents, and average property values for Raindrop Circle cross streets in Reisterstown, MD.