Heidrun Matthes

Cyclones and their possible changes in the Arctic by the end of the twenty first century from regional climate model simulations

Characteristics of cyclones (frequency, intensity and size) and their changes in the Arctic region in a warmer climate have been analyzed with the use of the HIRHAM regional climate model simulations with SRES-A1B anthropogenic scenario for the twenty first century. The focus was on cyclones for the warm (April–September) and cold (October–March) seasons. The present-day cyclonic characteristics from HIRHAM simulations are in general agreement with those from ERA–40 reanalysis data. Differences noted for the frequency of cyclones are related with different spatial resolution in the model simulations and reanalysis data. Potential future changes in cyclone characteristics at the end of the twenty first century have been analyzed. According to the model simulations, the frequency of cyclones is increasing in warm seasons and decreasing in cold seasons for a warmer climate in the twenty first century, but these changes are statistically insignificant. Noticeable changes were detected for the intensity and size of cyclones for the both seasons. Significant increase was found for the frequency of weak cyclones during cold season. Further, a general increase in the frequency of small cyclones was calculated in cold seasons, while its frequency decreases in warm seasons.

Recent changes in Arctic temperature extremes: warm and cold spells during winter and summer

In the Arctic, climate change manifests with the strongest warming trends on the globe, especially in the cold season. It is under debate if climate extremes change similarly strong. Our study provides detailed regional information about two selected temperature extreme indices in the Arctic, namely warm and cold spells in winter and summer. We analyze their temporal evolution and variability from 1979–2013, based on daily station data and ERA-Interim reanalysis. Calculated trends from both datasets suggest a widespread decrease of cold spells in winter and summer of up to −4 days/decade, with regional patches where trends are statistically significant throughout the Arctic. Winter trends are spatially heterogeneous, the reanalysis also shows small areas with statistically significant increases of cold spells throughout Siberia. Calculated changes in warm spells from both datasets are mostly small throughout the Arctic (less than ±1 day/decade) and statistically not significant. Remarkable exceptions are the Lena river basin in winter with a statistically significant decrease of up to −1.5 days/decade and areas in Scandinavia with statistically significant increases of up to 2.5 days/decade in winter and summer (again from both datasets). From the analysis of spell lengths, we find that there are no shifts from longer to shorter spells or vice versa with time, but long cold spells (events lasting for more than 15 days) disappear almost completely after the year 2000. There is a distinct inter-annual and decadal variability in the spells, which hinders the detection of significant trends for all spell categories in all regions.

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.

Variability of Extreme Temperature in the Arctic - Observation and RCM

This paper discusses results of a simulation with the regional climate model HIRHAM for 1958-2001, driven by the ECMWF reanalysis (ERA40) data over the Arctic domain. The aim is to analyze the ability of the model to capture certain features of climate extremes derived from daily mean, maximum and minimum temperatures. For this purpose, a range of climate indices (frost days, cold and warm spell days, growing degree days and growing season length) was calculated from the model output as well as from ERA40 data and region-specific station data for Eastern and Western Russian Arctic for comparison. It is demonstrated that the model captures the main features in the spatial distribution and temporal development of most indices well. Though systematic deviations in the seasonal means occur in various indices (frost days, growing degree days), variability and trends are well reproduced. Seasonal mean patterns in frost days are reproduced best, though the model persistently calculates too many frost days. Seasonal means of cold and warm spell days are reproduced without systematic biases, though deviations occur in summer for cold spells and in spring and summer for warm spells due to an early spring warming in the regional climate model and a low variability of the daily maximum temperature over sea ice.

Uncertainties in coupled regional Arctic climate simulations associated with the used land surface model

Permafrost is one of the most important components of Arctic land. Regional atmosphere-snowpermafrost interactions can be best studied with Regional Climate Models (RCMs) due to their higher horizontal resolution compared to global climate models. The development of Arctic RCMs with sophisticated land models is therefore very important. Comparing RCMs with different land surface model (LSM) components then allows the quantification of the uncertainties associated with the LSM. This study analyzes two simulations of coupled atmosphere-land RCMs over the Arctic, which differ only in their land component, while the atmospheric model component is the same. Specifically, we examine HIRHAM5-CLM4 (HIRHAM5 coupled with the sophisticated land model CLM4) and HIRHAM5 (HIRHAM5 coupled with the simpler land model of ECHAM5). We discuss the two models’ abilities to represent observations on permafrost-like permafrost extent, active layer thickness (ALT), and soil temperature profiles, as well as on the representation of the Arctic atmosphere, based on simulations over 1979–2014. In comparison to HIRHAM5, HIRHAM5-CLM4 significantly reduces the simulated bias in ALT and winter soil temperatures. We find that the simulation of soil temperature and subsequently ALT is sensitive to soil thermal and hydraulic parameter representation in the models. The simulation of permafrost extent is sensitive to the initial soil temperature state in the models. Both HIRHAM5 and HIRHAM5-CLM4 do similarly well in modeling the Arctic 2 m air temperature and atmospheric circulation. Changing the land model impacts the 2 m air temperature significantly over land and the atmospheric circulation predominantly over the Arctic Ocean, associated with changes in baroclinic cyclones.

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

The ability of state-of-the-art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic-CORDEX initiative. Some models employ large-scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA-Interim, National Centers for Environmental Prediction-Climate Forecast System Reanalysis, National Aeronautics and Space Administration-Modern-Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency-Japanese 55-year reanalysis) in winter and summer for 1981-2010 period. In addition, we compare cyclone statistics between ERA-Interim and the Arctic System Reanalysis reanalyses for 2000-2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large-scale spectral nudging show a better agreement with ERA-Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables. (Less)