Abstract
This case study examined how well downscaling of Community Earth System Model (CESM) data can reproduce climatological conditions relevant for summer (JJA) air quality in Glacier Bay National Park. Climatology was determined from the meteorological results obtained by the Weather Research and Forecasting model inline coupled with chemistry (WRF-chem) when driven with CESM data of 2006-2012. The climatology of this experiment (EXP) was evaluated by climatology from gridded blended sea-wind speeds, CRU data, and 42 surface meteorology sites. The quality relative to known performance was assessed by comparison to climatology determined from WRF-chem control simulations driven with FNL analysis data (CON) in forecast mode. Compared to observations, the thermodynamic and dynamic performances of EXP showed similar shortcomings (dampened diurnal temperature range, overestimation of wind speed over land) as CON. Over water EXP wind-speed climatology JJA bias (simulated minus observed) was -0.7 m/s. With respect to the CRU data EXP biases in JJA 2m temperature, diurnal temperature range, relative humidity and accumulated precipitation were -1.1 K, -4.9 K, 13%, and 110 mm, respectively. The slightly warmer atmosphere in EXP compensated for deficiencies in the cloud schemes leading to better results for the number of wet days and accumulated precipitation than in CON. Downscaling captured known mesoscale responses important for regional climate in a similar way as CON. When using CESM forcing, lateral boundary effects expanded spatially farther into the domain than known for forcing by analysis data. Overall, climatologies obtained from downscaling for Southeast Alaska had similar skill than those derived from forecasts driven by analysis data.
Highlights
In Southeast Alaska and Glacier Bay National Park, in particular, many management decisions require assessment of the impacts on future visibility, degree of the air’s pristine quality, and ecosystems prior to their implementation [1]
Given the limitations set by the data situation, our study provides a first, locally and temporally resticted assessment of the capability and accuracy of downscaling Community Earth System Model (CESM) data by Weather Research and Forecast model (WRF)-chem to reproduce local/regional climatologies
And along the coasts, EXP outperformed control simulation (CON). These findings suggest that (1) the bias was rather due to the prescribed sea-surface temperatures (SST) than the lateral forcing data, (2) downscaling with WRF-chem produced better diurnal temperature range (DTR) inland than along the coasts in all summer months, and (3) EXP results were of similar quality than we know from forecasts with analysis data
Summary
In Southeast Alaska and Glacier Bay National Park, in particular, many management decisions (e.g. cruisespeed limits, restrictions on the number of vessels in protected areas, emission controls) require assessment of the impacts on future visibility, degree of the air’s pristine quality, and ecosystems prior to their implementation [1]. Southeast Alaska is part of the large Alexander Archipelago (Figure 1) representing a substantial number of large islands and islets, and mountainous forest. The Tongass National Forest, the largest forest in the US, encompasses about 27,359 km of shoreline and covers a substantial area of the region. At the northern end of the archipelago, Glacier Bay National Park encompasses one of the largest marine protected areas in the northern hemisphere with nearly 3 million acres of glacial fjord landscape and pristine wilderness. In 2008, 225 cruise ships entered the park, typically spending 9 - 10 hours per visit all of which include stops in the upper fjords in front of tidewater glaciers
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