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Subseasonal forecasting -- predicting temperature and precipitation 2 to 6 weeks ahead -- is critical for effective water allocation, wildfire management, and drought and flood mitigation. Recent international research efforts have advanced…
To be able to produce accurate and reliable predictions of visibility has crucial importance in aviation meteorology, as well as in water- and road transportation. Nowadays, several meteorological services provide ensemble forecasts of…
Atmospheric correction is a fundamental task in remote sensing because observations are taken either of the atmosphere or looking through the atmosphere. Atmospheric correction errors can significantly alter the spectral signature of the…
A crucial function for automated vehicle technologies is accurate localization. Lane-level accuracy is not readily available from low-cost Global Navigation Satellite System (GNSS) receivers because of factors such as multipath error and…
Accurate weather forecasts are critical for societal planning and disaster preparedness. Yet these forecasts remain challenging to produce and evaluate, especially in regions with sparse observational coverage. Current evaluation of…
We have constructed a Bayesian neural network able of retrieving tropospheric temperature profiles from rotational Raman-scatter measurements of nitrogen and oxygen and applied it to measurements taken by the RAman Lidar for Meteorological…
To explore the issue of performing a non-interactive numerical weather forecast with an operational global model in assist of astronomical observing, we use the Xu-Randall cloud scheme and the Trinquet-Vernin AXP seeing model with the…
A generative diffusion model is used to produce probabilistic ensembles of precipitation intensity maps at the 1-hour 5-km resolution. The generation is conditioned on infrared and microwave radiometric measurements from the GOES and DMSP…
In this study, the statistical downscaling model (SDSM) is employed for downscaling the precipitation (PREC), maximum temperature (T max ) and minimum temperature (T min ) over Krishna River Basin (KRB). The Canadian Earth System Model,…
After 30 years since the beginning of the Global Positioning System (GPS), or, more generally, Global Navigation Satellite System (GNSS) meteorology, this technique has proven to be a reliable method for retrieving atmospheric water vapor;…
In order to describe more accurately the time relationships between daily satellite imagery time series of precipitation and NDVI we propose an estimator which takes into account the sparsity naturally observed in precipitation. We…
LiDAR sensors are used in autonomous driving applications to accurately perceive the environment. However, they are affected by adverse weather conditions such as snow, fog, and rain. These everyday phenomena introduce unwanted noise into…
Precipitation remains one of the most challenging climate variables to observe and predict accurately. Existing datasets face intricate trade-offs: gauge observations are relatively trustworthy but sparse, satellites provide global coverage…
The NASA dual-frequency, dual-polarization, Doppler radar (D3R) is an important ground validation tool for the global precipitation measurement (GPM) mission dual-frequency precipitation radar (DPR). The D3R has undergone extensive field…
Single image rain removal is a typical inverse problem in computer vision. The deep learning technique has been verified to be effective for this task and achieved state-of-the-art performance. However, previous deep learning methods need…
Flight height is a fundamental parameter for correcting the gamma signal produced by terrestrial radionuclides measured during airborne surveys. The frontiers of radiometric measurements with UAV require light and accurate altimeters flying…
A Low Humidity and Temperature Profiling (LHATPRO) microwave radiometer, manufactured by Radiometer Physics GmbH (RPG), is used to monitor sky conditions over ESO's Paranal observatory in support of VLT science operations. The unit measures…
In this paper, the complexities in the relationship between rainfall and sea surface temperature (SST) anomalies during the winter monsoon (November-January) over India were evaluated statistically using scatter plot matrices and…
Roughness parameters that characterize contacting surfaces with regard to friction and wear are commonly stated without uncertainties, or with an uncertainty only taking into account a very limited amount of aspects such as repeatability of…
Soft Computing techniques have opened up new avenues to the forecasters of complex systems. Atmosphere is a complex system and all the atmospheric parameters carry different degrees of complexity within themselves. Endeavor of the present…