A5054609090- Meteorological Phenomena and Simulations
- Climate variability and models
- Atmospheric and Environmental Gas Dynamics
- Precipitation Measurement and Analysis
- Energy Load and Power Forecasting
- Wind and Air Flow Studies
- Geophysics and Gravity Measurements
- Ocean Waves and Remote Sensing
- Environmental Impact and Sustainability
Environment and Climate Change Canada
2016-2020
Université du Québec à Montréal
2015-2017
École de Technologie Supérieure
2012
Nordic Life Science Pipeline (Canada)
2012
Abstract It is still common to neglect the spatial error correlations of assimilated observations in numerical weather prediction systems because no practical approach available account for them when number with correlated large or these are non‐uniformly distributed. Instead, it practice inflate observation variances avoid overfitting scales and spatially thin reduce between remaining observations, although both methods generally sacrifice small‐scale information. Inspired by previous work...
Abstract Two types of approaches are commonly used for estimating the impact arbitrary subsets observations on short-range forecast error. The first was developed variational data assimilation systems and requires adjoint model. Comparable were use with ensemble Kalman filter rely ensembles forecasts. In this study, a new approach computing observation is proposed ensemble–variational (EnVar). Like standard approaches, procedure implemented through iterative minimization modified cost...
Although many near‐surface wind observations are available, very few assimilated over land mainly due to sub‐grid scale topographic interactions with the flow. The main objectives of this study understand impact on analysis and point out aspects that need be improved make a better use these observations. A geo‐statistical observation operator has been developed correct for systematic representativeness errors. Assimilation experiments were performed in simplified context, assimilating only...
Abstract The exigencies of the global community toward Earth system science will increase in future as human population, economies, and footprint on planet continue to grow. This growth, combined with intensifying urbanization, inevitably exert increasing pressure all ecosystem services. A unified interdisciplinary approach is required that can address this challenge, integrate technical demands long-term visions, reconcile user scientific feasibility. Together research arms World...
ABSTRACT Developed for short‐term (0–48 h) wind power forecasting purposes, high‐resolution meteorological forecasts Eastern Canada are available from Environment Canada's Numerical Weather Prediction (NWP) model configured on a limited area (GEM‐LAM). This paper uses 3 years of forecast data this the region North Cape (Prince Edward Island, Canada). Although resolution is relatively high (2.5 km), statistical analysis and site inspection reveal that does not have sufficiently refined grid...
Abstract High-resolution flow-dependent background error covariances can allow for a better usage of dense observation networks in applications data assimilation numerical weather prediction. The generation high-resolution ensembles, however, be computationally cost prohibitive. In this study, practical and low-cost ensemble methods are presented compared against both global regional Kalman filters (G-EnKF R-EnKF, respectively). goal is to provide limited-area deterministic schemes with...
Abstract This study examines the assimilation of near-surface wind observations over land to improve nowcasting and short-term tropospheric forecasts. A new geostatistical operator based on geophysical model output statistics (GMOS) is compared with a bilinear interpolation scheme (Bilin). The multivariate impact forecasts temporal evolution analysis increments produced are examined as well influence background error covariances different components prediction system. Results show that Bilin...
Abstract This study introduces an experimental regional assimilation configuration for a 4D ensemble–variational (4D-EnVar) deterministic weather prediction system. A total of 16 experiments covering July 2014 are presented to assess both climatological background error covariances and updates in the treatment flow-dependent covariances. The estimated using statistical correlations between variables instead balance operators. These covariance estimates allow analyses fit more closely with...