High Resolution Climatic Projections for the Ottawa City Commensurate with 2 and 3.5 Degrees of Global Warming

This presentation will describe the methodology, validation, and results generated by dynamically downscaling future climate projections made by the Canadian Earth System Model (CanESM2) within and around the Ottawa city of Canada. The limited-area Weather Research and Forecasting (WRF) model (coupled to the Noah land surface model; Chen and Dudhia, 2001) is used for dynamic downscaling after evaluating its performance in simulating key climatic variables around the city of Ottawa under present-day weather conditions. The validated WRF-Noah modeling system is then used to dynamically downscale the CanESM2 future climatic projections from an initial horizontal spatial resolution of ~2.8^o to 1 km by using multiple two-way nesting domain simulations. The developed high-resolution climate projections are commensurate with 2^oC and 3.5ºC rise in projected future global warming with reference to a baseline time-period of 1986 to 2016.

To validate the WRF-Noah modeling system, we conducted two high spatial resolution WRF model experiments which were verified against one rural and one urban weather station located within the OTTAWA region (at hourly frequency) for near-surface air temperature, wind speed, relative humidity, and accumulated precipitation, each station covering the same three-month summertime period from 1 June to 31 August in 2018. Both WRF-simulations shared the same numerical domain, composed of three two-way nested domains of 9, 3, and 1 km, respectively. The vertical dimension was split in 40 eta levels, with 14 within the lowest 1.5 km to better reproduce planetary boundary layer (PBL) processes. The PBL processes were characterized with the two-order closure Mellor-Yamada-Janjic (Janjic 1994) turbulent parameterization. The National Centers for Environmental Prediction North American Regional Reanalysis products (number ds608.0), which are available at time steps of 3 h and a spatial resolution of 32 km, were used to provide the large-scale meteorological forcing to conduct the WRF model simulations. The lower boundary conditions for the coupled atmospheric model (i.e., WRF) were provided by the Noah land surface model (LSM) for the non-urban grid cells and by an urban parameterization for the urban grid cells. To assess the relative importance of representing urban surfaces, one WRF-simulation was conducted with the bulk urban parameterization (Liu et al., 2006), that was included in the Noah LSM, and the other WRF-simulation with a multilayer building energy model (MBEM; Salamanca et al., 2011). The bulk urban parameterization represents zero-order effects of urban surfaces and assumes common values for the entire urban domain (i.e., constant values for surface albedo, roughness lengths, volumetric heat capacity, and thermal conductivity). On the other hand, the MBEM is a sophisticated urban parameterization model comprised of a building energy model (Salamanca et al., 2010) integrated into a multilayer urban canopy model (Martilli et al., 2002) that directly interacts with the atmospheric boundary layer from the ground surface to the highest building present in the urban grid cell.

Our numerical experiments demonstrated that the WRF-Noah modeling system was able to accurately reproduce the daily evolution of near-surface air temperature, wind speed, and relative humidity for both rural and urban areas. More specifically, for rural and urban locations, the WRF-modeled mean absolute errors (MAEs) for 2 m air temperature were, respectively, below 2.3 ^oC and 2.0 ^oC. On the other hand, WRF-modeled MAEs for near-surface wind speed were lower than 6.2 km h^-1 and 6.5 km h^-1 for rural and urban sites respectively. Finally, WRF-modeled MAEs for near-surface relative humidity were below 11.7 % and 10.5 %, respectively, for the rural and urban locations. However, the WRF model tends to overestimate rainfall as was evident from values obtained for the WRF-modeled monthly accumulated precipitation during the months of June and August which were significantly overestimated. For example, WRF-modeled values during June, July, and August were, respectively, 151 mm, 148 mm, and 129 mm against 70 mm, 171 mm, and 98 mm gathered at the rural site, and 178 mm, 170 mm, and 135 mm against 76 mm, 153 mm, and 69 mm gathered at the urban site when the bulk urban parameterization was used. Similar results were computed when the MBEM was instead used.

As a final point, we will perform two more WRF model experiments (using the same setup that has already been described and with the MBEM) to dynamically downscale future climate projections commensurate with 2 ^oC and 3.5 ^oC rise in projected future global warming and the results will be presented with a short discussion on the limitations and future work.

References

Chen F., and Dudhia J. (2001), Coupling and advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model implementation and sensitivity, Monthly Weather Review, 129(4), 569-585.

Janjic Z. I. (1994), The Step-Mountain Eta Coordinate Model: Further Developments of the Convection, Viscous Sublayer, and Turbulent Closure Schemes, Monthly Weather Review, 122, 927-945.

Liu Y., Chen F., Warner T., and Basara J. (2006), Verification of a mesoscale data-assimilation and forecasting system for the Oklahoma city area during the Joint Urban 2003 Field Project, Journal of Applied Meteorology, 45(7), 912-929.

Martilli A., Clappier A., and Rotach M. W. (2002), An urban surface exchange parameterization for mesoscale models, Boundary-Layer Meteorology, 104(2), 261-304.

Salamanca F., Krpo A., Martilli A., and Clappier A. (2010), A new building energy model coupled with an urban canopy parameterization for urban climate simulations-Part I. Formulation, verification, and sensitivity analysis of the model, Theor. Appl. Climatol., 99, 331-344.

Salamanca F., Martilli A., Tewari M., and Chen F. (2011), A study of the urban boundary layer using different urban parameterizations and high-resolution urban canopy parameters with WRF, Journal of Applied Meteorology and Climatology, 50(5), 1107-1128.