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 1979–2012. A process-based vertically integrated moist static energy (MSE) budget is performed to understand the model’s fidelity in representing leading processes that govern the monsoon breaks over continental India. In the climatology (June–September) 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 “local Hadley-type” 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 HIRHAM5’s moisture-radiation interaction. Our study directly implies that process-based budget diagnostics are necessary, apart from just checking the northward propagation feature to examine RCM’s 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

New Insights Into Cyclone Impacts on Sea Ice in the Atlantic Sector of the Arctic Ocean in Winter

Peer reviewe

Evaluation of 20CR reanalysis data and model results based on historical (1930–1940) 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

Arctic sea ice thickness variability and change

Arctic sea ice thickness variability and change and their dependence on the atmospheric and oceanic forcing are at the core of research in Subtopic 2.1, Theme: Ongoing and Future Arctic and Antarctic Climate Change. Our research is particularly focused on a better process understanding and representation in models, and observations during MOSAiC play a strong role. The poster gives examples of such process studies focused on Arctic sea ice thickness variability and change. We outline observations of the long-term and regional variability and change of sea ice thickness using satellite remote sensing, airborne surveying, and ice mass balance buoys. Thermodynamic growth and its interaction with the atmosphere over leads and level ice serves as an example for our joint research interests. The poster also gives examples of causes of sea ice thinning, like increased ocean heat flux to the ice due to Atlantification, and consequences, e.g., for reduced sea ice volume transport through Fram Strait

Arctic Storm Activities in Ensemble Simulations by the HIRHAM-NAOISM Regional Coupled Climate Model

Arctic storm activities have shown intensification during recent decades, which may have contributed to or caused extreme climate events. We examined Arctic storm activities in 10 ensemble simulations by using the Arctic regional coupled climate model HIRHAM-NAOSIM. Storm identification and tracking algorithm (Zhanget al., 2004) were employed to derive intensity, location and duration of each storm. Arctic regional storm climatology and variability were constructed and compared with the same statistics derived from the ERA-interim reanalysis data