457 research outputs found
The complex interplay of atmosphere and sea ice in the Arctic (Das komplexe Wechselspiel von AtmosphÀre und Meereis in der Arktis)
Evaluation of 20CR reanalysis data and model results based on historical (1930â1940) observations from Franz Josef Land
Unique and independent historical observations, carried out in the central Arctic during the early twentieth century warming (ETCW) period, were used to evaluate the older (20CRv2) and newer (20CRv2c) versions of the 20th Century Reanalysis and the HIRHAM5 regional climate model. The latter can reduce several biases compared to its forcing data set (20CRv2) probably due to higher horizontal resolution and a more realistic cloud parameterization. However, low-level temperature and near-surface specific humidity agree best between 20CRv2c and the surface-based observations. This better performance results from more realistic lower boundary conditions for sea ice concentration and sea surface temperature, but it is limited mainly to polar night. Although sea level pressures are very similar, the vertical stratification and baroclinicity change in the transition from 20CRv2 to 20CRv2c. Compared to observed temperature profiles, the systematic cold bias above 400 hPa remains almost unchanged indicating an incorrect coupling between the planetary boundary layer and free troposphere. In addition to surface pressures, it is therefore recommended to assimilate available vertical profiles of temperature, humidity and wind speed. This might also reduce the large biases in 10 m wind speed, but the reliability of the sea ice data remains a great unknown
South Asian summermonsoon breaks: Process-based diagnostics in HIRHAM5
This study assesses the ability of a high-resolution downscaling simulation with the regional
climate model (RCM) HIRHAM5 in capturing the monsoon basic state and boreal summer intraseasonal
variability (BSISV) over South Asia with focus on moist and radiative processes during 1979â2012.
A process-based vertically integrated moist static energy (MSE) budget is performed to understand
the modelâs fidelity in representing leading processes that govern the monsoon breaks over continental
India. In the climatology (JuneâSeptember) HIRHAM5 simulates a dry bias over central India in association
with descent throughout the free troposphere. Sources of dry bias are interpreted as (i) near-equatorial
Rossby wave response forced by excess rainfall over the southern Bay of Bengal promotes anomalous
descent to its northwest and (ii) excessive rainfall over near-equatorial Arabian Sea and Bay of Bengal
anchor a âlocal Hadley-typeâ circulation with descent anomalies over continental India. Compared with
observations HIRHAM5 captures the leading processes that account for breaks, although with generally
reduced amplitudes over central India. In the model too, anomalous dry advection and net radiative cooling
are responsible for the initiation and maintenance of breaks, respectively. However, weaker contributions
of all adiabatic MSE budget terms, and an inconsistent relationship between negative rainfall anomalies
and radiative cooling reveals shortcomings in HIRHAM5âs moisture-radiation interaction. Our study directly
implies that process-based budget diagnostics are necessary, apart from just checking the northward
propagation feature to examine RCMâs fidelity to simulate BSISV
Simulation and evaluation of 2-m temperature over Antarctica in polar regional climate model
The European Centre for Medium-Range Weather Forecasts Reanalysis ERA40, National Centers for Environmental Prediction (NCEP) 20th-century reanalysis, and three station observations along an Antarctic traverse from Zhongshan to Dome-A stations are used to assess 2-m temperature simulation skill of a regional climate model. This model (HIRHAM) is from the Alfred Wegener Institute for Polar and Marine Research in Germany. Results show: (1) The simulated multiyear averaged 2-m temperature field pattern is close to that of ERA40 and NCEP; (2) the cold bias relative to ERA40 over all of Antarctic regions is 1.8°C, and that to NCEP reaches 5.1°C; (3) bias of HIRHAM relative to ERA40 has seasonal variation, with a cold bias mainly in the summer, as much as 3.4°C. There is a small inland warm bias in autumn of 0.3°C. Further analysis reveals that the reason for the cold bias of 2-m temperature is that physical conditions of the near-surface boundary layer simulated by HIRHAM are different from observations: (1) During the summer, observations show that near-surface atmospheric stability conditions have both inversions and non-inversions, which is due to the existence of both positive and negative sensible heat fluxes, but HIRHAM almost always simulates a situation of inversion and negative sensible heat flux; (2) during autumn and winter, observed near-surface stability is almost always that of inversions, consistent with HIRHAM simulations. This partially explains the small bias during autumn and winter
Analysis of atmospheric circulation from climate model big data -Current approaches and future challenges
A large part of low-frequency variability in the climate system on sub-seasonal to decadal timescales can be described in terms of preferred atmospheric circulation patterns, often called circulation regimes. Such recurring and persistent, large-scale patterns of pressure and circulation anomalies span vast geographical area and are closely related to atmospheric teleconnection patterns like the famous North-Atlantic Oscillation (NAO). Within the conceptual framework of circulation regimes, low-frequency variability can be observed as a result of transitions between the distinct atmospheric circulation regimes. Moreover, the frequency of occurrence of preferred atmospheric circulation regimes is influenced by the external forcing factors such as other components of the climate system and anthropogenic forcing. This determines, at least partly, the time-mean response of the atmospheric flow to the external forcing.
In this framework, one of our research foci is to advance the understanding of past, recent and future changes in the spatial/temporal structure of atmospheric circulation regimes and to assess the impact of internal climate dynamics versus external forcing. To tackle these questions, we exploit large global gridded data sets either from different reanalysis data sets or from model simulations with state of the art climate models mostly performed in the framework of CMIP (Coupled model intercomparison project) initiatives.
We introduce and apply a hypothesis-driven approach, in particular to study the impact of sea-ice changes on atmospheric circulation patterns. The hypothesis-driven approach consists in three (iterative) steps: (i) Application of statistical methods for pattern recognition on reanalysis and climate model data, (ii) development of a hypothesis about underlying dynamical mechanisms of the impact of sea-ice changes on atmospheric circulation patterns, (iii) testing of the new hypothesis by performing new well designed climate model experiments and new model data analysis. By applying this approach, we identified tropospheric and stratospheric dynamical pathways which explain, how Arctic climate changes, in particular sea-ice changes, influence the weather and climate in mid-latitudes
Structure and seasonal changes in atmospheric boundary layer on coast of the east Antarctic continent
The temperature, humidity, and vertical distribution of ozone in the Antarctic atmospheric boundary layer(ABL) and their seasonal changes are analyzed, by using the high-resolution profile data obtained during the International Polar Year 2008 to 2009 at Zhongshan Station, to further the understanding of the structure and processes of the ABL. The results show that the frequency of the convective boundary layer in the warm season accounts for 84% of its annual occurrence frequency. The frequency of the stable boundary layer in the cold season accounts for 71% of its annual occurrence frequency. A neutral boundary layer appears rarely. The average altitude of the convective boundary layer determined by the parcel method is 600 m; this is 200 to 300 m higher than that over inland Antarctica. The average altitude of the top of the boundary layer determined by the potential temperature gradient and humidity gradient is 1 200 m in the warm season and 1 500 m in the cold season. The vertical structures of ozone and specific humidity in the ABL exhibit obvious seasonal changes. The specific humidity is very high with greater vertical gradient in the warm season and very low with a lesser gradient in the cold season under 2 000 m. The atmospheric ozone in the ABL is consumed by photochemical processes in the warm season, which results in a slight difference in altitude. The sub-highest ozone center is located in the boundary layer, indicating that the ozone transferred from the stratosphere to the troposphere reaches the low boundary layer during October and November in Antarctica
Recent Greenland accumulation estimated from regional climate model simulations and ice core analysis
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. non-consideration 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
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