The Canadian Airport Nowcasting System (CAN‐Now)

Abstract

ABSTRACT:The Canadian Airport Nowcasting Project (CAN-Now) has developed an advanced prototype all-season weather forecasting and nowcasting system that can be used at major airports. This system uses numerical model data, pilot reports, ground in situ sensor observations (precipitation, icing, ceiling, visibility, winds), on-site remote sensing (such as vertically pointing radar and microwave radiometer) and off-site remote sensing (satellite and radar) information to provide detailed nowcasts out to approximately 6 h. The nowcasts, or short term weather forecasts, should allow decision makers such as pilots, dispatchers, de-icing crews, ground personnel or air traffic controllers to make plans with increased margins of safety and improved efficiency. The system has been developed and tested at Toronto Pearson International Airport (CYYZ) and Vancouver International Airport (CYVR). A Situation Chart has been developed to allow users to have a high glance value product which identifies significant weather related problems at the airport. New products combining observations and numerical model output into nowcasts have been tested. Some statistical verifications of forecast products, with comparisons to persistence, covering both a winter (2009/2010) and summer (2010) period have been made. Problems with the prediction of relative humidity and wind direction are outlined. The ability to forecast categorical variables such as ceiling, visibility, as well as precipitation rate and type accurately are discussed. Overall, for most variables, the nowcast systems can outperform persistence after the first 1 or 2 h, and provide more accurate forecasts than individual Numerical Weather Prediction models out to 6 h.

Nowcasting the precipitation phase combining weather radar data, surface observations, and NWP model forecasts

“…In particular, reflectivity and radial wind velocity from the weather radar network (XRAD) and surface observation data (XEMA and METAR) were assimilated in a 3-hour cycle. The resulting WRF simulations at 3 km (namely WRF-3DVAR, hereafter WRF) provided 12-hour forecasts at an hourly resolution that were linearly interpolated to a 30-minute temporal resolution, following Isaac et al (2014) and Keis (2015), to render them consistent with AWS network observations.…”

“…Nowcasting is usually achieved by means of persistence or trends of observations, since their performance surpasses that of NWP models (Golding, 1998; Haiden et al ., 2011). Examples of surface precipitation type nowcasting include combined ground‐temperature trend observations and NWP vertical temperature profiles in Integrated Nowcasting through Comprehensive Analysis (INCA: Haiden et al ., 2011), a decision‐tree algorithm based on modelled vertical temperature profiles in CAN‐Now (Isaac et al ., 2014), surface temperature conditions to classify different types of snow in PNOWWA (Saltikoff et al ., 2018), and features of modelled vertical temperature profiles and trends of observations in WHITE (Keis, 2015). All the aforementioned nowcasting schemes implement a weather radar extrapolation technique for precipitation, since this tends to outperform NWP models for the first 1.5–2 hr (Simonin et al ., 2017).…”

Snowfall rate estimation using C‐band polarimetric radars

“…Pearson International Airport (CYYZ) in Toronto was selected as an observation site due to the availability of multiple sensors for precipitation measurements as part of the CAN‐Now project (Isaac et al ., ). Also, the site is within a reasonable distance from the radar.…”

“…Solid snowfall measurements ranged between 0.5 and 6.5 cm h −1 while SWE measurements ranged between 0.1 and 3.7 mm h −1 with no wet snowfall cases included. Pearson International Airport (CYYZ) in Toronto was selected as an observation site due to the availability of multiple sensors for precipitation measurements as part of the CAN-Now project (Isaac et al, 2014). Also, the site is within a reasonable distance from the radar.…”

Cloud height measurement by a network of all-sky-imagers

“…CBH is used to validate and improve climate models (Costa-Surós et al, 2013) and numeric weather prediction models (Hogan et al, 2009). In aviation, CBH is important to air traffic controllers (Khlopenkov et al, 2019;Reynolds et al, 2012;Isaac et al, 2014). As clouds are the major cause of variability of the solar resource, they are of special interest for solar power applications.…”