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The greater the probability of cloud drop, the uncertainty of cloud drop is smaller.
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The information about optical and microphysical cloud properties derived from SEVIRI used as input data to Artificial neural networks MLP are given as follows: Information about "Cloud Water Path (CWP)" The effective droplet radius re and the optical thickness τ of clouds both represented by a single parameter referred to as CWP are directly related to rainfall probability of a cloud.
The CWP is related to the rainfall probability of a cloud and can therefore be used as a delimiter between the non-raining and raining cloud (e.g. Thies et al. 2008a, b; Nauss and Kokhanovsky 2006).
Some stochastic variables are used to estimate the probability of vapor cloud explosions: frequency of the release, the probability of not having an immediate ignition, the probability of delayed ignition and the probability of a vapor cloud explosion given a delayed ignition, as well as different possible meteorological conditions.
A two-dimensional Markov chain model is applied to only two dimensions to change, and the success arrive probability of the cloud is P1PxPy.
The 1D Markov chain model is applied to only one dimension to change, the success arrive probability of the cloud is P1Px.
Koch (2013) gives reasons for continued use of aerial photography, such as long traditions, high spatial resolution, greater probability of acquiring cloud free data within a specific time window as well as smaller areas and fragmented land use in European countries compared to, e.g., larger non-European countries such as the USA, Canada, or countries in South America.
With a return schedule of approximately 16 days, the probability of collecting one cloud-free Landsat image per month of the year is low.
With decreasing of cosmic ray (CR) intensity caused by increasing of solar activity (SA) or in some short periods of Forbush-decreases, the intensity of secondary CR relativistic electrons decreases and the probability of formation of thunderstorm clouds and discharges between clouds or between clouds and ground is also expected to decrease.
The numerical models in use today, the founder says, are pretty much incapable of predicting the formation of a single cloud and, instead focus on predicting the probability of conditions suitable for cloud formation in a given time (at least one hour) in a relatively large domain.
The authors use this model to investigate rejection probabilities and help dimensioning of cloud data centers.
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