Improving Snowfall Forecasting by Diagnosing Snow Density
نویسندگان
چکیده
منابع مشابه
Snowfall Measurement Using Lidar Ceilometers, Radars and Snow Gauges
1 School of Electrical and Computer Engineering, Kanazawa University Kakuma, Kanazawa 920-1192, Japan ( † Tel: +81-76-234-4890; † E-mail: [email protected]) 2 Toyama National College of Technology Hongo, Toyama 939-8630, Japan 3 Hydrospheric Atmospheric Research Center, Nagoya University Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan 4 Institute of Low Temperature Science, Hokkaido Univ...
متن کاملOn the evolution of the snow surface during snowfall
[1] The deposition and attachment mechanism of settling snow crystals during snowfall dictates the very initial structure of ice within a natural snowpack. In this letter we apply ballistic deposition as a simple model to study the structural evolution of the growing surface of a snowpack during its formation. The roughness of the snow surface is predicted from the behaviour of the time depende...
متن کاملImproving Stock Return Forecasting by Deep Learning Algorithm
Improving return forecasting is very important for both investors and researchers in financial markets. In this study we try to aim this object by two new methods. First, instead of using traditional variable, gold prices have been used as predictor and compare the results with Goyal's variables. Second, unlike previous researches new machine learning algorithm called Deep learning (DP) has bee...
متن کاملSnow in a Very Steep Rock Face: Accumulation and Redistribution During and After a Snowfall Event
Terrestrial laser scanning was used to measure snow thickness changes (perpendicular to the surface) in a rock face. The aim was to investigate the accumulation and redistribution of snow in extremely steep terrain (>60). The north-east face of the Chlein Schiahorn in the region of Davos in eastern Switzerland was scanned before and several times after a snowfall event. A summer scan without sn...
متن کاملForecasting Experiments Using the Regional Meteorological Model and the Numerical Snow Cover Model in the Snow Disaster Forecasting System
The Snow and Ice Research Center (SIRC) of the National Research Institute for Earth Science and Disaster Prevention (NIED) of Japan has been developing a snow disaster forecasting system. This system consists of an atmospheric mesoscale model NHM, the numerical snow cover model SNOWPACK, and three diagnostic models of snow disasters. In this paper, the performance of NHM and SNOWPACK is invest...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Weather and Forecasting
سال: 2003
ISSN: 0882-8156,1520-0434
DOI: 10.1175/1520-0434(2003)018<0264:isfbds>2.0.co;2