Surface
1. Canadian Land Data Assimilation System in the National Surface and River Prediction System (CaLDAS-NSRPS)
Description:
CaLDAS-NSRPS is a continuous offline land-surface assimilation system that provides analyses of the land surface every 3 hours over the domain of the High-Resolution Deterministic Prediction System (HRDPS) at a 2.5 km grid spacing. The system focuses on assimilating satellite-based remote sensing observations to optimize initial conditions for predictive components of the National Surface and River Prediction System (NSRPS). It is launched four times daily at 0000, 0600, 1200, and 1800 UTC.
Available Variables:
Air Temperature (1.5 m above ground): Temperature in Kelvin.
Soil Moisture: Volumetric water content in the soil.
Dew Point Temperature: Temperature at which air becomes saturated.
Surface Radiative Temperature: Temperature of the land surface as measured by radiative methods.
Snow Water Equivalent: Amount of water contained within the snowpack.
Surface Albedo: Reflectivity of the Earth's surface.
Latent and Sensible Heat Fluxes: Energy exchanges between the land surface and atmosphere.
Potential AI/ML Applications:
Improving weather and climate models by providing accurate land surface initial conditions.
Enhancing hydrological forecasting through better soil moisture and snowpack data.
Developing models for agricultural monitoring and drought assessment.
2. High Resolution Deterministic Land Surface Prediction System (HRDLPS)
Description:
The HRDLPS produces high-resolution medium-range forecasts of land surface, subsurface variables, and near-surface atmospheric variables. It is initialized with analysis and trial fields provided by CaLDAS-NSRPS. The system aims to provide detailed forecasts to support various applications, including weather prediction and hydrological modeling.
Available Variables:
1.5 m Air Temperature and Dew Point: Forecasted near-surface temperature and dew point.
10 m Wind Speed and Direction: Predicted wind conditions near the surface.
Soil Temperature and Moisture at Various Depths: Forecasted subsurface conditions.
Snow Depth and Snow Water Equivalent: Predicted snowpack characteristics.
Surface Fluxes (e.g., Latent and Sensible Heat): Energy exchanges between the land surface and atmosphere.
Potential AI/ML Applications:
Enhancing precision agriculture through detailed soil and atmospheric forecasts.
Improving flood forecasting and water resource management with accurate soil moisture and snow data.
Supporting renewable energy operations by providing detailed surface wind forecasts.
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