Abstract. Environment and Climate Change Canada has initiated the production of a 1980–2018, 10 km, North American precipitation and surface reanalysis. ERA-Interim is used to initialize the Global Deterministic Reforecast System (GDRS) at a 39 km resolution. Its output is then dynamically downscaled to 10 km by the Regional Deterministic Reforecast System (RDRS). Coupled with the RDRS, the Canadian Land Data Assimilation System (CaLDAS) and Precipitation Analysis (CaPA) are used to produce surface and precipitation analyses. All systems used are close to operational model versions and configurations. In this study, a 7-year sample of the reanalysis (2011–2017) is evaluated. Verification results show that the skill of the RDRS is stable over time and equivalent to that of the current operational system. The impact of the coupling between RDRS and CaLDAS is explored using an early version of the reanalysis system which was run at 15 km resolution for the period 2010–2014, with and without the use of CaLDAS. Significant improvements are observed with CaLDAS in the lower troposphere and surface layer, especially for the 850 hPa dew point and absolute temperatures in summer. Precipitation is further improved through an offline precipitation analysis which allows the assimilation of additional observations of 24 h precipitation totals. The final dataset should be of particular interest for hydrological applications focusing on transboundary and northern watersheds, where existing products often show discontinuities at the border and assimilate very few – if any – precipitation observations.

Aquatic plants (macrophytes) are known to affect flow dynamics, contributing to flow resistance. Most studies on flow‐vegetation interactions are performed in laboratory flumes and focus on the flow field around plants, with little research at the level of vegetation patches in large aquatic ecosystems. In most hydrodynamic models, increased drag due to plants is modelled by increasing the Manning's n roughness coefficient. The objectives of this study were to: (1) develop a three‐dimensional hydrodynamic model (Delft3D) applicable to large water bodies including a novel approach to represent macrophyte resistance (modified k‐ε turbulence closure model); and (2) compare the modelled flow with field measurements for different vegetation configurations and patch arrangements. Work was carried out in Lake Saint‐Pierre, a large fluvial lake of the St Lawrence River in Québec, Canada. Results showed a marked increase in residence time in the zone affected by macrophytes when using the modified k‐ε turbulence closure model compared to the Manning's n approach, particularly near the bed. An improved agreement with field measured depth‐averaged velocity is obtained with this novel approach (correlation coefficient of 0.80 compared to 0.46 with Manning's n only). In addition, a good fit was obtained between vertical velocity profiles modelled and measured in the macrophyte zone. Sensitivity analysis revealed that the additional drag due to plants was closely associated with plant height, but that plant density played only a minor role in retarding velocities. These findings indicate that it is possible to accurately quantify both the horizontal and vertical flow modulations resulting from submerged vegetation in large fluvial systems. Considering that the Delft3D model is capable of approximating measured velocity magnitude, preserving the logarithmic shape throughout the water column and reaching near‐zero velocities without increasing the roughness coefficient, we recommend this modelling approach for future research on the impact of macrophytes on flow at the scale of vegetation patches in large water bodies comparable to Lake Saint‐Pierre.

Abstract. Environment and Climate Change Canada has initiated the production of a 1980–2018, 10 km, North American precipitation and surface reanalysis. ERA-Interim is used to initialize the Global Deterministic Reforecast System (GDRS) at a 39 km resolution. Its output is then dynamically downscaled to 10 km by the Regional Deterministic Reforecast System (RDRS). Coupled with the RDRS, the Canadian Land Data Assimilation System (CaLDAS) and Precipitation Analysis (CaPA) are used to produce surface and precipitation analyses. All systems used are close to operational model versions and configurations. In this study, a 7-year sample of the reanalysis (2011–2017) is evaluated. Verification results show that the skill of the RDRS is stable over time, and equivalent to that of the current operational system. The impact of the coupling between RDRS and CaLDAS is explored using an early version of the reanalysis system which was run at 15 km resolution for the period 2010–2014, with and without the use of CaLDAS. Significant improvements are observed with CaLDAS in the lower troposphere and surface layer, especially for the 850 hPa dew point and absolute temperatures in summer. Precipitation is further improved through an offline precipitation analysis which allows the assimilation of additional observations of 24-h precipitation totals. The final dataset should be of particular interest for hydrological applications focusing on trans-boundary and northern watersheds, where existing products often show discontinuities at the border and assimilate very few – if any – precipitation observations.