Extreme Precipitation and Climate Gradients in Patagonia Revealed by High-Resolution Regional Atmospheric Climate Modeling

Abstract

This study uses output of a high-resolution (5.5 km) regional atmospheric climate model to describe the present-day climate of Patagonia, with a particular focus on the surface mass balance (SMB) of the Patagonian ice fields. Through a comparison with available in situ observations, it is shown that the model is able to simulate the sharp climate gradients in western Patagonia. The southern Andes are an efficient barrier for the prevalent atmospheric flow, generating strong orographic uplift and precipitation throughout the entire year. The model suggests extreme orographic precipitation west of the Andes divide, with annual precipitation rates of .5 to 34 m w.e. (water equivalent), and a clear rain shadow east of the divide. These modeled precipitation rates are supported qualitatively by available precipitation stations and SMB estimates on the ice fields derived from firn cores. For the period 1979-2012, a slight atmospheric cooling at upper ice field elevations is found, leading to a small but insignificant increase in the ice field SMB.

Temperature and Wind Climate of the Antarctic Peninsula as Simulated by a High-Resolution Regional Atmospheric Climate Model

“…11, 12, 13, 14, and 15 show ERA-Interim climate maps next to the RACMO2.3 climate maps, all illustrating the added value of the high-resolution results over the ERAInterim fields. The high resolution has a significant impact on simulated winds in rough terrain, which has been previously discussed in Bromwich et al (2005) and Lenaerts et al (2012b), which focused on other regions in Antarctica. At 5.5 km, more detail and more pronounced temperature and wind speed gradients are simulated over the AP mountain range.…”

“…RACMO2.3 has been adapted for use over the large ice sheets of Greenland and Antarctica ; it includes a multilayer snow model to calculate melt, percolation, refreezing, and runoff of liquid water (Ettema et al 2010); a prognostic scheme for snow grain size to calculate surface albedo (Kuipers Munneke et al 2011); and a routine that simulates the interaction of drifting snow with the surface and the lower atmosphere (Lenaerts et al 2012a). ERA-Interim data with 6-hourly resolution from January 1979 to December 2013 (Dee et al 2011) are used to force the model at the lateral atmospheric boundaries as well as at the lower ocean boundaries by prescribing sea ice fraction and sea surface temperatures.…”

“…Dynamical downscaling using high-resolution regional atmospheric climate models (RCMs) has proven to be a good method to represent climate at 5-10-km resolution. Moreover, RCMs can be specifically adapted to simulate the climate and surface mass balance of glaciated regions, such as the Antarctic ice sheet (Lenaerts et al 2012c;Van Wessem et al 2014b), but also of smaller partly glaciated regions, such as Greenland (Fettweis 2007;Ettema et al 2010), Patagonia (Lenaerts et al 2014), and Svalbard (Claremar et al 2012;Lang et al 2015).…”

The modelled surface mass balance of the Antarctic Peninsula at 5.5 km horizontal resolution

“…At this resolution we assume the assumption of hydrostatic balance to hold, an assumption that is justified to some extent by ear- lier studies (Lenaerts et al, 2014;Van Wessem et al, 2015), although a non-hydrostatic model version will likely further improve the model output in terms of better resolved processes over sloping surfaces, such as foehn and katabatic winds that influence (drifting snow) sublimation and snowmelt fluxes (Cassano and Parish, 2000). The surface topography is based on a combination of the 100 m digital elevation model (DEM) from Cook et al (2012) and the 1 km DEM from Bamber et al (2009).…”

“…Higher resolution simulations have also been performed, but without a high-resolution snow-routine (Bromwich, 2004;King et al, 2015). Recently, the regional atmospheric climate model RACMO2.3 was used at a horizontal resolution of 5.5 km to simulate the SMB of Patagonia (Lenaerts et al, 2014). In this study we use the same model and resolution to simulate the SMB of the AP for 1979-2014, the period for which reliable forcing data are available, coupling it to a FDM to calculate processes in the firnpack and, eventually, runoff.…”