Abstract. Lidar scan techniques for wind profiling rely on the assumption of a horizontally homogeneous wind field and stationarity for the duration of the scan. As this condition is mostly violated in reality, detailed knowledge of the resulting measurement error is required. The objective of this study is to quantify and compare the expected error associated with Doppler-lidar wind profiling for different scan strategies and meteorological conditions by performing virtual measurements implemented in a large-eddy simulation (LES) model. Various factors influencing the lidar retrieval error are analyzed through comparison of the wind measured by the virtual lidar with the ‘true’ value generated by the LES. These factors include averaging interval length, zenith angle configuration, scan technique and instrument orientation. For the first time, ensemble simulations are used to determine the statistically expected uncertainty of the lidar error. The analysis reveals a root-mean-square deviation (RMSD) of less than 1 m s−1 for 10 min averages of wind speed measurements in a moderately convective boundary layer, while RMSD exceeds 2 m s−1 in strongly convective conditions. Unlike instrument orientation and scanning scheme, the zenith angle configuration proved to have significant effect on the retrieval error. Horizontal wind speed error is reduced when a larger zenith angle configuration is used, but is increased for measurements of vertical wind. Results suggest that the scan strategy has a relevant effect on the lidar retrieval error and that instrument configuration should be chosen depending on the quantity of interest and the flow conditions in which the measurement is performed.
Abstract. Doppler-lidar scan techniques for wind profiling rely on the assumption of a horizontally homogeneous wind field and stationarity for the duration of the scan. As this condition is mostly violated in reality, detailed knowledge of the resulting measurement error is required. The objective of this study is to quantify and compare the expected error associated with Doppler-lidar wind profiling for different scan strategies and meteorological conditions by performing virtual Doppler-lidar measurements implemented in a large-eddy simulation (LES) model. Various factors influencing the lidar retrieval error are analyzed through comparison of the wind measured by the virtual lidar with the “true” value generated by the LES. These factors include averaging interval length, zenith angle configuration, scan technique and instrument orientation (cardinal direction). For the first time, ensemble simulations are used to determine the statistically expected uncertainty of the lidar error. The analysis reveals a root-mean-square deviation (RMSD) of less than 1 m s−1 for 10 min averages of wind speed measurements in a moderately convective boundary layer, while RMSD exceeds 2 m s−1 in strongly convective conditions. Unlike instrument orientation with respect to the main flow and scanning scheme, the zenith angle configuration proved to have significant effect on the retrieval error. Horizontal wind speed error is reduced when a larger zenith angle configuration is used but is increased for measurements of vertical wind. Furthermore, we find that extending the averaging interval length of lidar measurements reduces the error. In addition, a longer duration of a full scan cycle and hence a smaller number of scans per averaging interval increases the error. Results suggest that the scan strategy has a measurable impact on the lidar retrieval error and that instrument configuration should be chosen depending on the quantity of interest and the flow conditions in which the measurement is performed.
<div> <p><span data-contrast="auto">As there is no evidence for the implementation of sufficiently ambitious global CO2 emission reductions, it is very unlikely that we will be able to keep the global mean warming at the end of the century below the 1.5 C limit set in the Paris Agreement. However, the development of CO2 removal techniques could potentially allow us to reach the 1.5 C target after a period of temperature overshoot, by offsetting past and current high levels of emissions with net-negative emissions in the future.&#160;To assess the effectiveness and the risks associated to such mitigation options, we need to better understand the impact of temperature overshoot scenarios on various components of the Earth System. </span><span data-ccp-props="{">&#160;</span></p> <p><span data-contrast="auto">Here, we focus on the Greenland Ice Sheet. We force an ice-sheet model (CISM2) with Surface Mass Balance (SMB) from an ensemble of 400 years-long idealized overshoot simulations, carried out with the Norwegian Earth System Model NorESM2. The SMB, which is calculated in NorESM2 using an energy balance scheme at multiple elevation classes, is downscaled during runtime to the ice-sheet model grid, thus allowing to account explicitly for the SMB-height feedback. In this presentation, we will assess the sea-level contribution of the Greenland Ice Sheet for overshoot pathways, compared to reference pathways without overshoot. Moreover, we will assess the impact of individual processes, such as the SMB-height feedback and the ocean-driven mass loss at marine-terminating margins, on the sea-level contribution of the Greenland Ice Sheet. </span><span data-ccp-props="{">&#160;</span></p> </div>
<p>The Greenland ice sheet is currently one of the main contributors to sea-level rise and mass loss from the ice sheet is expected to continue under increasing Arctic warming. Since sea-level rise is threatening coastal communities worldwide, reducing uncertainties in projections of future sea-level contribution from the Greenland ice sheet is of high importance. In this study we address the response of the ice sheet to future climate change. We determine rates of sea-level contribution that can be expected from the ice sheet until 2100 by performing an ensemble of standalone ice sheet simulations with the Community Ice Sheet Model (CISM). The ice sheet is initialized to resemble the presently observed geometry by inverting for basal friction. We examine a range of uncertainties, associated to stand alone ice sheet modeling by prescribing forcing from various global circulations models (GCMs) for different future forcing scenarios (shared socioeconomic pathways, SSPs). Atmospheric forcing is downscaled with the regional climate model MAR. The response of marine terminating outlet glaciers to ocean forcing is represented by a retreat parameterization and sampled by considering different sensitivities. Furthermore, we investigate how the initialization of the ice sheet with forcing from different global circulation models affects the projected rates of sea-level contribution. In addition, sensitivity of the results to the grid spacing of the ice sheet model is assessed. The observed historical mass loss is generally well reproduced by the ensemble. The projections yield a sea-level contribution in the range of 70 to 230 mm under the SSP5-8.5 scenario until 2100. Climate forcing constitutes the largest source of uncertainty for projected sea-level contribution, while differences due to the initial state of the ice sheet and grid resolution are minor.</p> <p>&#160;</p> <p>&#160;</p>
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