Wolfgang Dorn

Recent Greenland Accumulation Estimated from Regional Climate Model Simulations and Ice Core Analysis

Abstract The accumulation defined as “precipitation minus evaporation” over Greenland has been simulated with the high-resolution limited-area regional climate model HIRHAM4 applied over an Arctic integration domain. This simulation is compared with a revised estimate of annual accumulation rate distribution over Greenland taking into account information from a new set of ice core analyses, based on surface sample collections from the North Greenland Traverse. The region with accumulation rates below 150 mm yr−1 in central-northwest Greenland is much larger than previously assumed and extends about 500 km farther to the south. It is demonstrated that good agreement between modeled and observed regional precipitation and accumulation patterns exists, particularly concerning the location and the values of very low accumulation in the middle of Greenland. The accumulation rates in the northern part of Greenland are reduced in comparison to previous estimates. These minima are connected with a prevailing bloc...

A dynamical link between the Arctic and the global climate system

Received 16 November 2005; revised 12 December 2005; accepted 15 December 2005; published 1 February 2006. [1] By means of simulations with a global coupled AOGCM it is shown that changes in the polar energy sink region can exert a strong influence on the mid- and high-latitude climate by modulating the strength of the mid-latitude westerlies and storm tracks. It is found, that a more realistic sea-ice and snow albedo treatment changes the ice-albedo feedback and the radiative exchange between the atmosphere and the ocean-sea-ice system. The planetary wave energy fluxes in the middle troposphere of mid-latitudes between 30 and 50 Na re redistributed, which induces perturbations in the zonal and meridional planetary wave trains from the tropics over the mid-latitudes into the Arctic. It is shown, that the improved parameterization of Arctic sea-ice and snow albedo can trigger changes in the Arctic and North Atlantic Oscillation pattern with strong implications for the European climate. Citation: Dethloff, K., et al. (2006), A dynamical link between the Arctic and the global climate system, Geophys. Res. Lett., 33, L03703, doi:10.1029/2005GL025245.

A comparison of the two Arctic atmospheric winter states observed during N‐ICE2015 and SHEBA

Winter time atmospheric observations from the 2015 Norwegian young sea-ICE campaign (N-ICE2015) are compared with data from the 1997-1998 Surface Heat Budget of the Arctic (SHEBA) campaign. Both datasets have a bimodal distribution of the net longwave radiative flux for January-February, with modal values of -40 W m-2 and 0 W m-2. These values correspond to the radiatively clear and opaquely cloudy states, respectively, and are likely to be representative of the wider Arctic. The new N-ICE2015 observations demonstrate that the two winter states operate in the Atlantic sector of the Arctic and regions of thin sea ice. We compare the N-ICE2015 and SHEBA data with ERA-Interim and output from the coupled Arctic regional climate model HIRHAM-NAOSIM. ERA-Interim simulates two Arctic winter states well and captures the timing of transitions from one state to the other, despite underestimating the cloud liquid water path. HIRHAM-NAOSIM has more cloud liquid water compared with ERA-Interim, but simulates the two states poorly. Our results demonstrate that models must simulate realistic synoptic forcing and temperature profiles to accurately capture the two Arctic winter states, and not only the presence of mixed-phase clouds. Using ERA-Interim, we find a positive trend in the number of opaquely cloudy days in the western Atlantic sector of the Arctic, and a strong correlation with the mean winter temperature over much of the Arctic Basin. Hence, the two Arctic winter states are important for understanding inter-annual variability in the Arctic. The N-ICE2015 dataset will help improve our understanding of these relationships.

The impact of Greenland's deglaciation on the Arctic circulation

[2] The Greenland ice sheet is the largest orographic feature of the Arctic. Mountains of such a scale together with surface heating or cooling anomalies exert a strong influence on the atmospheric circulation of the Northern Hemisphere. The impact of Greenland’s ice sheet on the atmospheric circulation is of importance due to its position in vicinity to the North Atlantic storm tracks. The impact of Greenland’s deglaciation on cyclone tracks has been investigated in a regional numerical weather prediction model

New insight of Arctic cloud parameterization from regional climate model simulations, satellite‐based and drifting station data

Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (< 700m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

Evaluation of Arctic land snow cover characteristics, surface albedo and temperature during the transition seasons from regional climate model simulations and satellite data

This paper evaluates the simulated Arctic land snow cover duration, snow water equivalent, snow cover fraction, surface albedo, and land surface temperature in the regional climate model HIRHAM5 during 2008–2010, compared with various satellite and reanalysis data and one further regional climate model (COSMO-CLM). HIRHAM5 shows a general agreement in the spatial patterns and annual course of these variables, although distinct biases for specific regions and months are obvious. The most prominent biases occur for east Siberian deciduous forest albedo, which is overestimated in the simulation for snow covered conditions in spring. This may be caused by the simplified albedo parameterization (e.g., nonconsideration of different forest types and neglecting the effect of fallen leaves and branches on snow for deciduous tree forest). The land surface temperature biases mirror the albedo biases in their spatial and temporal structures. The snow cover fraction and albedo biases can explain the simulated land surface temperature bias of ca. −3°C over the Siberian forest area in spring.

The recent decline of the Arctic summer sea-ice cover in the context of internal climate variability

By means of a 21-year simulation of a coupled regional pan-Arctic atmosphere-ocean-ice model for the 1980s and 1990s and comparison of the model results with SSM/I satellite-derived sea-ice concentrations, the patterns of maxi- mum amplitude of interannual variability of the Arctic summer sea-ice cover are revealed. They are shown to concentrate beyond an area enclosed by an isopleth of barotropic planetary potential vorticity that marks the edge of the cyclonic rim current around the deep inner Arctic basin. It is argued that the propagation of the interannual variability signal farther into the inner Arctic basin is hindered by the dynamic isolation of upper Arctic Ocean and the high summer cloudiness usually appearing in the central Arctic. The thinning of the Arctic sea-ice cover in recent years is likely to be jointly re- sponsible for its exceptionally strong decrease in summer 2007 when sea-ice decline was favored by anomalously high atmospheric pressure over the western Arctic Ocean, which can be regarded as a typical feature for years with low sea-ice extent. In addition, unusually low cloud cover appeared in summer 2007, which led to substantial warming of the upper ocean. It is hypothesized that the coincidence of several favorable factors for low sea-ice extent is responsible for this ex- treme event. Owing to the important role of internal climate variability in the recent decline of sea ice, a temporal return to previous conditions or stabilization at the current level can not be excluded just as further decline.

Distinct circulation states of the Arctic atmosphere induced by natural climate variability

The high-resolution regional climate model HIRHAM4 with a horizontal resolution of 0.5°×0.5° was used to determine the influence of natural climate variations in the Arctic. The large-scale lateral forcing and the lower boundary forcing for the HIRHAM4 were delivered from a long-term run of the coupled circulation model ECHO-G at T30 resolution. This run was carried out with prescribed constant external forcing for present-day climate conditions. 600 years of this ECHO-G simulation were analyzed to find periods persisting over several years either with mainly warm or mainly cold conditions during the Arctic winter. Two warm and two cold periods, each of 6 years duration, were selected for the regionalization of the Arctic climate in January. The performed model simulations show that a warm or cold Arctic winter climate is connected with two distinct circulation states of the Arctic atmosphere. These states are characterized by a different location and extension of the tropospheric vortex with a vortex center over the western Arctic in warm Januaries or over the eastern Arctic in cold Januaries, respectively. Moreover, there are indications that these different locations of the vortex are linked to a different synoptic activity in Alaska and the eastern part of the Arctic which is, in turn, related to a different meridional transport of heat and moisture into these regions. The resultant climate conditions in these regions differ from each other with statistical significance and are, finally, decisive for the warm or cold Arctic climate state.

Arctic Regional Climate Models

In this chapter, we provide an overview of current applications of regional climate models (RCMs) to the Arctic. There are increased applications of RCMs to present-day climate simulations and process parameterisations. Any advances in regional climate modelling must be based on analysis of physical processes in comparison with observations. In data-poor regions like the Arctic, this approach may be completed by a collaborative analysis of several research groups. Within the ARCMIP (Arctic Regional Climate Model Intercomparison Project), simulations for the SHEBA year 1997–1998 have been performed by several Arctic RCMs. The use of high resolution RCMs can contribute to a better description of important regional physical processes in the ocean, cryosphere, atmosphere, land and biosphere including their interactions in coupled regional model systems. This is based on identifying and modelling of the key processes and on an assessment of the improved understanding in the light of analysis of instrumental as well as paleoclimatic and paleoenvironmental records. The main goal is to address the deficiencies in understanding the Arctic by developing improved physical descriptions of Arctic climate feedbacks in atmospheric and coupled regional climate models and to implement the improved parameterisations into global climate system models to determine their global influences and consequences for decadal-scale climate variations. A further aim is to model the main feedbacks correctly to arrive at a more reliable estimate of future changes due to the coupling between natural and anthropogenic effects.

Global impacts of Arctic climate processes

The polar regions are experiencing major climate and environmental changes due to the combined effects of natural variability and global warming. To address regional Arctic climate processes and their global feedbacks, 53 experts from the United States, Canada, Europe, and Russia gathered for a recent workshop at the Alfred Wegener Institute for Polar and Marine Research, in Potsdam, Germany. The workshop, which was organized by Klaus Dethloff and Annette Rinke, focused on the use of regional models of the Arctic, global coupled climate models, and Arctic impact studies. This article summarizes the main advances and outstanding issues in Arctic modeling that were presented and discussed during the workshop.