High-resolution (1 km) Polar WRF output for 79° N Glacier and the northeast of Greenland from 2014 to 2018

Abstract

Abstract. The northeast region of Greenland is of growing interest due to changes taking place on the large marine-terminating glaciers which drain the Northeast Greenland Ice Stream. Nioghalvfjerdsfjorden, or 79∘ N Glacier, is one of these that is currently experiencing accelerated thinning, retreat, and enhanced surface melt. Understanding both the influence of atmospheric processes on the glacier and feedbacks from changing surface conditions is crucial for our understanding of present stability and future change. However, relatively few studies have focused on the atmospheric processes in this region, and even fewer have used high-resolution modelling as a tool to address these research questions. Here we present a high-spatial-resolution (1 km) and high-temporal-resolution (up to hourly) atmospheric modelling dataset, NEGIS_WRF, for the 79∘ N and northeast Greenland region from 2014 to 2018 and an evaluation of the model's success at representing daily near-surface meteorology when compared with automatic weather station records. The dataset (Turton et al., 2019b: https://doi.org/10.17605/OSF.IO/53E6Z) is now available for a wide variety of applications in the atmospheric, hydrological, and oceanic sciences in the study region.

A Detailed, Multi‐Scale Assessment of an Atmospheric River Event and Its Impact on Extreme Glacier Melt in the Southern Alps of New Zealand

“…KROPAČ ET AL. The physics and dynamics settings used in this study are based on our experience using WRF in diverse latitudinal, topographic and climatic environments (e.g., Mölg & Kaser, 2011;Turton et al, 2020). We selected the best performing configuration (in terms of statistical performance metrics) out of a set of 45 sensitivity runs involving different combinations of physics und dynamics options as well as nudging techniques and time step settings.…”

“…For the high-resolution domain (D2), topographic effects on radiation, including both topographic shading and slope effects, were accounted for and a cumulus parameterization was neglected since model simulations using a grid spacing smaller than 4 km are considered to resolve most convective processes explicitly (Weisman et al, 1997). Cloud microphysics were represented by the Morrison 2-moment scheme, which we consider the most robust parametrization scheme for clouds and precipitation in high-mountain and/or glacierized environments based on our previous modeling studies in different climatic zones (e.g., Collier et al, 2018;Mölg et al, 2017;Temme et al, 2020;Turton et al, 2020). Specifically, in the Himalayas, the Morrison 2-moment scheme has been proven to produce the most accurate output (compared to other microphysics schemes) when evaluated against observational data and radar/lidar cloud products (Orr et al, 2017).…”

Convection‐permitting modeling with regional climate models: Latest developments and next steps

“…In many studies, the main interest lies in the evaluation of the simulated precipitation (Mölg & Kaser, 2011;Collier et al, 2013Collier et al, , 2018Collier et al, , 2019Collier & Immerzeel, 2015;Bonekamp et al, 2018Bonekamp et al, , 2019Schaefer et al, 2013) and precipitation extremes (Sauter, 2020) at high elevations, which contribute to the growth of glaciers. However, the atmospheric circulation (Bonekamp et al, 2018;Turton et al, 2019Turton et al, , 2020, and especially the recurrence of foehn events (Steinhoff et al, 2014;Bannister & King, 2015;Turton et al, 2017;Temme et al, 2020;Elvidge et al, 2020), are of large interest because such events directly affecting the melting of glaciers are improved at higher resolutions. Interestingly, Bannister and King (2015) were able to explain the recent asymmetrical retreat of South Georgia Island glaciers via enhanced leeside surface warming and drying.…”

“…In their evaluation of simulations at different resolutions over the Himalayas, Bonekamp et al (2018) highlighted that the highest resolution of 500 m provided the best match of precipitation, wind and 2-m temperature with the observations. CPRCM hindcast simulations of 1 year and above were analyzed over different glaciers such as the Kilimanjaro (Collier et al, 2018), Himalayas (Bonekamp et al, 2019), part of Greenland (Turton et al, 2020), Patagonia (Schaefer et al, 2013(Schaefer et al, , 2015Sauter, 2020), and South Georgia Island (Bannister & King, 2015). Amongst those studies, one focused on the impacts of TCs at high elevations of the Kilimanjaro (Collier et al, 2019) and another one took advantage of a long simulation to study the impacts of modes of climate variability on climate variables at different elevations (Collier et al, 2018).…”

Flow Regimes and Föhn Types Characterize the Local Climate of Southern Patagonia

“…In previous studies in mountainous regions, the wind speed errors in the WRF model were associated with problems in the initial and boundary conditions and the representation of the topography [59]. However, the results of the statistical performance are generally in a typical range for the model evaluations of WRF based on hourly data (e.g., [2,13,53,60,61]). The main föhn characteristics are reproduced by the model: With föhn onset (cessation), air temperature and wind speed increase (decrease) and relative humidity decreases (increases).…”