Daily Mean Sea Level Pressure Research Articles

Evaluating Medium-Range Forecast Performance of Regional-Scale Circulation Patterns

Abstract Accurate subseasonal-to-seasonal (S2S) weather forecasts are crucial to making important decisions in many sectors. However, significant gaps exist between the needs of society and what forecasters can produce, especially at weekly and longer lead times. We hypothesize that by clustering atmospheric states into a number of predefined categories, the noise can be reduced and, consequently, medium-range forecasts can be improved. Self-organizing map (SOM)-based clustering was used on daily mean sea level pressure (MSLP) data from the North American Regional Reanalysis to categorize the synoptic-scale circulation for eastern North America from 1979 to 2016 into 28 discrete patterns. Then, using two goodness-of-fit metrics, the relative skill of four different forecasting methods over a 90-day lead time was studied: 1) a circulation pattern (CP) forecast, 2) raw forecast output from the Climate Forecast System (CFS) operated by the National Centers for Environmental Prediction (NCEP), 3) a simple climatology forecast, and 4) a simple persistence forecast. As expected, forecast skill of both the CP forecast and the raw CFS forecast generally decreased rapidly from the first day, coming to parity with the skill of climatology after 10–12 days when using correlation, and at 7–10 days when using the root-mean-square error (RMSE). Most importantly, this study found that the CP forecast was the most skillful forecast method over the 8–11-day lead time when using RMSE. On a spatial basis, the skill of the CP forecast and the raw CFS decreases latitudinally from north to south. This study thus demonstrates the potential utility of categorical or circulation pattern–based forecasting at 1–2-week lead times.

Circulation pattern controls of wet days and dry days in Free State, South Africa

Atmospheric circulation is a vital process in the transport of heat, moisture, and pollutants around the globe. The variability of rainfall depends to some extent on the atmospheric circulation. This paper investigates synoptic situations in southern Africa that can be associated with wet days and dry days in Free State, South Africa, in addition to the underlying dynamics. Principal component analysis was applied to the T-mode matrix (variable is time series and observation is grid points at which the field was observed) of daily mean sea level pressure field from 1979 to 2018 in classifying the circulation patterns in southern Africa. 18 circulation types (CTs) were classified in the study region. From the linkage of the CTs to the observed rainfall data, from 11 stations in Free State, it was found that dominant austral winter and late austral autumn CTs have a higher probability of being associated with dry days in Free State. Dominant austral summer and late austral spring CTs were found to have a higher probability of being associated with wet days in Free State. Cyclonic/anti-cyclonic activity over the southwest Indian Ocean, explained to a good extent, the inter-seasonal variability of rainfall in Free State. The synoptic state associated with a stronger anti-cyclonic circulation at the western branch of the South Indian Ocean high-pressure, during austral summer, leading to enhanced low-level moisture transport by southeast winds was found to have the highest probability of being associated with above-average rainfall in most regions in Free State. On the other hand, the synoptic state associated with enhanced transport of cold dry air, by the extratropical westerlies, was found to have the highest probability of being associated with (winter) dryness in Free State.

Improved atmospheric circulation over Europe by the new generation of CMIP6 earth system models

Global Climate Models (GCMs) generally exhibit significant biases in the representation of large-scale atmospheric circulation. Even after a sensible bias adjustment these errors remain and are inherited to some extent by the derived downscaling products, impairing the credibility of future regional projections. In this study we perform a process-based evaluation of state-of-the-art GCMs from CMIP5 and CMIP6, with a focus on the simulation of the synoptic climatological patterns having a most prominent effect on the European climate. To this aim, we use the Lamb Weather Type Classification (LWT, Lamb British isles weather types and a register of the daily sequence 736 of circulation patterns 1861-1971. METEOROL OFF, GEOPHYS MEM; 737 GB; DA 1972; NO 116; PP 1-85; BIBL 2P1/2, 1972), a subjective classification of circulation weather types constructed upon historical simulations of daily mean sea level pressure. Observational uncertainty has been taken into account by considering four different reanalysis products of varying characteristics. Our evaluation unveils an overall improvement of salient atmospheric circulation features consistent across observational references, although this is uneven across models and large frequency biases still remain for the main LWTs. Some CMIP6 models attain similar or even worse results than their CMIP5 counterparts, although in most cases consistent improvements have been found, demonstrating the ability of the new models to better capture key synoptic conditions. In light of the large differences found across models, we advocate for a careful selection of driving GCMs in downscaling experiments with a special focus on large-scale atmospheric circulation aspects.

Long‐term variability and trends of extended winter snowfall in Turkey and the role of teleconnection patterns

AbstractIn this study, a climatological analysis of daily new snow cover data from 93 meteorological stations (10–2,400 m above sea level) over Turkey during the winter (December–March) period of 1967–2006 is presented. Series of snow cover depth (SCD) (≥1 cm) and number of snowy days (SDs) were analysed to determine the variability and statistically significant trends in the snow climatology. The results showed an inverse relation between SDs and SCD over the central (CAR) and eastern (EAR) Anatolian regions. While positive trends in SDs were observed in the CAR (77% of all stations), the new SCD decreased in time. On the other hand, the intensity of the daily snowfall over the EAR increased due to decreasing (increasing) SD (SCD) trends in the region, especially between the 500 and 1,000 m layer. It was found that higher SCDs occur in the EAR during winter with positive patterns in the east Atlantic/western Russia. The daily mean sea level pressure composite maps of high SCD (>5 cm) show that strong northeasterly flows enable the penetration of cold polar air to the EAR due to the interaction between the Siberian high‐pressure centre over Europe and the low‐pressure centre over the Caspian Sea. These results help further understanding of the regional variation of the snowfall pattern in Turkey and its response to global climatic change.

The Role of Synoptic Cyclones for the Formation of Arctic Summer Circulation Patterns as Clustered by Self-Organizing Maps

Contribution of extra-tropical synoptic cyclones to the formation of mean summer atmospheric circulation patterns in the Arctic domain (≥60° N) was investigated by clustering dominant Arctic circulation patterns based on daily mean sea-level pressure using self-organizing maps (SOMs). Three SOM patterns were identified; one pattern had prevalent low-pressure anomalies in the Arctic Circle (SOM1), while two exhibited opposite dipoles with primary high-pressure anomalies covering the Arctic Ocean (SOM2 and SOM3). The time series of their occurrence frequencies demonstrated the largest inter-annual variation in SOM1, a slight decreasing trend in SOM2, and the abrupt upswing after 2007 in SOM3. Analyses of synoptic cyclone activity using the cyclone track data confirmed the vital contribution of synoptic cyclones to the formation of large-scale patterns. Arctic cyclone activity was enhanced in the SOM1, which was consistent with the meridional temperature gradient increases over the land–Arctic ocean boundaries co-located with major cyclone pathways. The composite daily synoptic evolution of each SOM revealed that all three SOMs persisted for less than five days on average. These evolutionary short-term weather patterns have substantial variability at inter-annual and longer timescales. Therefore, the synoptic-scale activity is central to forming the seasonal-mean climate of the Arctic.

Long-term trends in large-scale circulation behaviour and wind storms for North Atlantic islands: a multi-data analysis using ERA-20C and meteorological station data

This research examines the role that large-scale circulation plays in local storminess for the North Atlantic islands of Orkney and Shetland, using the ERA-20C (1900–2009) reanalysis dataset. Automatic Lamb weather type classification is applied to daily mean sea level pressure (MSLP) data at 0.125° × 0.125° resolution to typify large-scale circulation patterns and calculate measures of storminess (frequencies of severe gale days, very severe gale days, and gale days that are not severe), calibrated using available observations from meteorological stations on the islands, which were made available by the UK Met Office. Analysis of the reanalysis-based gale day record indicates that while the frequency of cyclonic (C) weather type days does not vary over the study period, this weather type is coinciding more often with gale days and especially very severe gale days, which may indicate an increase in the intensity of cyclonic weather types in the region.

Temporal Characteristics of Heat Waves and Cold Spells and Their Links to Atmospheric Circulation in EURO-CORDEX RCMs

We study summer heat waves and winter cold spells and their links to atmospheric circulation in an ensemble of EURO-CORDEX RCMs in Central Europe. Results of 19 simulations were compared against observations over 1980–2005. Atmospheric circulation was represented by circulation types and supertypes derived from daily gridded mean sea level pressure. We examined observed and simulated characteristics of hot and cold days (defined using percentiles of temperature anomalies from the mean annual cycle) and heat waves and cold spells (periods of at least three hot/cold days in summer/winter). Although the ensemble of RCMs reproduces on average the frequency and the mean length of heat waves and cold spells relatively well, individual simulations suffer from biases. Most model runs have an enhanced tendency to group hot/cold days into sequences, with several simulations leading to extremely long heat waves or cold spells (the maximum length overestimated by up to 2-3 times). All simulations also produce an extreme winter season with (often considerably) higher number of cold days than in any observed winter. The RCMs reproduce in general the observed circulation significantly conducive to heat waves and cold spells. Zonal flow reduces the probability of temperature extremes in both seasons, while advection of warm/cold air from the south-easterly/north-easterly quadrant plays a dominant role in developing heat waves/cold spells. Because of these links, the simulation of temperature extremes in RCMs is strongly affected by biases in atmospheric circulation. For almost all simulations and all circulation supertypes, the persistence of supertypes is significantly overestimated (even if the frequency of a given supertype is underestimated), which may contribute to development of too-long heat waves/cold spells. We did not identify any substantial improvement in the EURO-CORDEX RCMs in comparison to previous ENSEMBLES RCMs, but the patterns of the biases are generally less conclusive as to general RCMs’ drawbacks.

Atlantic multi-decadal oscillation influence on weather regimes over Europe and the Mediterranean in spring and summer

We analyze the influence of the Atlantic sea surface temperature multi-decadal variability on the day-by-day sequence of large-scale atmospheric circulation patterns (i.e. the “weather regimes”) over the Euro-Atlantic region. In particular, we examine of occurrence of weather regimes from 1871 to present. This analysis is conducted by applying a clustering technique on the daily mean sea level pressure field provided by the 20th Century Reanalysis project, which was successfully applied in other studies focused on the Atlantic Multi-decadal Oscillation (AMO). In spring and summer, results show significant changes in the frequencies of certain weather regimes associated with the phase shifts of the AMO. These changes are consistent with the seasonal surface pressure, precipitation, and temperature anomalies associated with the AMO shifts in Europe.

The main characteristics of atmospheric circulation over East-Central Europe from 1871 to 2010

The main objective of the paper concerns the determination of the annual and multi-annual variability of air flow over East-Central Europe in the period 1871–2010. Daily mean sea-level pressure and values of physical quantities provided the basis for distinguishing 27 circulation types, i.e., eight directional cyclonic, transitional, and anticyclonic types, and one non-directional cyclonic, anticyclonic, and an undefined type. Over the area of East-Central Europe, the highest frequency is recorded for air flow from the western sector, with a maximum in the period from December to January. In spring, a higher than average frequency of cyclonic and easterly circulation is observed, and in summer—anticyclonic and northerly. Increased zonal circulation was recorded in the years 1910–1930, and particularly after 1970, and eastern at the end of the nineteenth century and in the 1930s and 1940s. An increase in the frequency of days with non-directional anticyclonic type and westerly air flow, and a simultaneous decrease in frequency of days with south-easterly and easterly circulation were observed throughout the study period. Among the three classes of circulation types, the highest persistence (particularly in winter) was recorded for anticyclonic types, i.e., when the high pressure system occurred over the Scandinavian Peninsula or East Europe.

A flexible approach to defining weather patterns and their application in weather forecasting over Europe

ABSTRACTA method is presented for deriving weather patterns objectively over an area of interest, in this case the UK and surrounding European area. A set of 30 and eight patterns are derived through k‐means clustering of daily mean sea level pressure (MSLP) data (1850–2003). These patterns have been designed for the purpose of post‐processing forecast output from ensemble prediction systems and understanding how forecast models perform under different circulation types. The 30 weather patterns are designed for use in the medium‐range and the eight weather patterns are designed for use in the monthly and seasonal timescales, or when there is low forecast confidence in the medium‐range. Weather patterns are numbered according to their annual historic occurrences, with lower numbered patterns occurring most often. Lower numbered patterns occur more in summer (with weak MSLP anomalies) and higher numbered patterns occur more in winter (with strong MSLP anomalies). Weather patterns have been applied in a weather forecasting context, whereby ensemble members are assigned to the closest matching pattern definition. This provides a probabilistic insight into which patterns are most likely within the forecast range and summarises key aspects from the large volumes of data which ensembles provide. Verification of European Centre for Medium‐Range Weather Forecasts medium‐range ensemble forecasts for the set of eight weather patterns shows small forecast biases annually with some large variations seasonally. The most prominent seasonal variation shows the westerly (NAO+) pattern to over‐forecast in summer and under‐forecast in winter. Forecast skill was found to be better in winter than summer for most patterns.

Understanding climate change projections for precipitation over western Europe with a weather typing approach

AbstractPrecipitation over western Europe (WE) is projected to increase (decrease) roughly northward (equatorward) of 50°N during the 21st century. These changes are generally attributed to alterations in the regional large‐scale circulation, e.g., jet stream, cyclone activity, and blocking frequencies. A novel weather typing within the sector (30°W–10°E, 25–70°N) is used for a more comprehensive dynamical interpretation of precipitation changes. A k‐means clustering on daily mean sea level pressure was undertaken for ERA‐Interim reanalysis (1979–2014). Eight weather types are identified: S1, S2, S3 (summertime types), W1, W2, W3 (wintertime types), B1, and B2 (blocking‐like types). Their distinctive dynamical characteristics allow identifying the main large‐scale precipitation‐driving mechanisms. Simulations with 22 Coupled Model Intercomparison Project 5 models for recent climate conditions show biases in reproducing the observed seasonality of weather types. In particular, an overestimation of weather type frequencies associated with zonal airflow is identified. Considering projections following the (Representative Concentration Pathways) RCP8.5 scenario over 2071–2100, the frequencies of the three driest types (S1, B2, and W3) are projected to increase (mainly S1, +4%) in detriment of the rainiest types, particularly W1 (−3%). These changes explain most of the precipitation projections over WE. However, a weather type‐independent background signal is identified (increase/decrease in precipitation over northern/southern WE), suggesting modifications in precipitation‐generating processes and/or model inability to accurately simulate these processes. Despite these caveats in the precipitation scenarios for WE, which must be duly taken into account, our approach permits a better understanding of the projected trends for precipitation over WE.

Projected changes in synoptic weather patterns over New Zealand examined through self‐organizing maps

ABSTRACTNew insight is provided regarding 21st century projections of synoptic scale atmospheric circulation over the New Zealand region. Daily mean sea level pressure patterns from a number of general circulation models (GCMs) participating in the 5th Coupled Model Intercomparison Project (CMIP5) were analysed through a self‐organizing map (SOM) technique. In terms of simulating the synoptic climatology found in reanalyses, an initial model evaluation revealed quite substantial differences in model skill. Generally, those models with relatively high horizontal atmospheric resolution skilfully simulated the historical frequency and mean lifetime of large scale synoptic patterns over this region. Analysing future projections under this smaller subset of better‐performing models indicated robust and quite substantial increases in the annual frequency of widespread anticyclonic conditions over New Zealand, accompanied by a general decrease in widespread low pressure. These projected changes in frequency of synoptic occurrences become the most pronounced towards the end of the 21st century and for winter, whereas changes in the average synoptic pattern lifetime remain small. While not robust for all models in this subset, significant 21st century trends in the intensification of geostrophic westerly flow conditions within certain synoptic patterns were also found. Linking synoptic patterns to surface climate variables has also provided evidence that these circulation changes may collectively manifest as a significant non‐uniform climatic change across New Zealand. These findings should encourage further focused studies on circulation‐relevant applications and impacts in a climate change context.

The influence of atmospheric circulation types on regional patterns of precipitation in Marmara (NW Turkey)

In this study, regional patterns of precipitation in Marmara are described for the first time by means of Ward’s hierarchical cluster analysis. Daily values of winter precipitation data based on 19 meteorological stations were used for the period from 1960 to 2012. Five clusters of coherent zones were determined, namely Black Sea-Marmara, Black Sea, Marmara, Thrace, and Aegean sub-regions. To investigate the prevailing atmospheric circulation types (CTs) that cause precipitation occurrence and intensity in these five different rainfall sub-basins, objective Lamb weather type (LWT) methodology was applied to National Centers of Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis of daily mean sea level pressure (MSLP) data. Precipitation occurrence suggested that wet CTs (i.e. N, NE, NW, and C) offer a high chance of precipitation in all sub-regions. For the eastern (western) part of the region, the high probability of rainfall occurrence is shown under the influence of E (SE, S, SW) atmospheric CTs. In terms of precipitation intensity, N and C CTs had the highest positive gradients in all the sub-basins of the Marmara. In addition, although Marmara and Black Sea sub-regions have the highest daily rainfall potential during NE types, high daily rainfall totals are recorded in all sub-regions except the Black Sea during NW types.

Atmospheric circulation patterns in the Arab region and its relationships with Saudi Arabian surface climate: A preliminary assessment

This paper establishes and analyses the principal circulation patterns in and around Saudi Arabia (domain: 10°E–70°E; 5°N–40°N) based on the daily mean sea-level pressure (MSLP) 0.75°×0.75° gridded data derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) re-analysis ERA-Interim for the period 1979–2012. Association of the circulation patterns to the local climate is investigated using observed daily temperature and rainfall data at 27 locations over Saudi Arabia for the period 1979–2010. Using the widely-used mathematical technique principal component analysis (PCA) we determine with MSLP data the principal patterns. We only analyse data for the wet season (October–May). The automated typing procedure establishes 12 circulation types, which represent all the main synoptic features especially those that originate from the Mediterranean, the European and African continents, Siberia, and also the Red and Arabian seas. There is a strong link between the circulation types and surface climate that is synoptically and spatially interpretable. Particular circulation types are associated with specific climatic conditions across the country: rainfall is linked with Types 9, 10 and 11, whilst warm days (nights) with 1, 2, 3, 9, 10, 11 and 12 (1, 2, 3, 10, 11 and 12), and cold days (nights) with 2, 3, 4, 5, 6, 7, 11 and 12 (2, 4, 5, 6, 7 and 8). In terms of regional influences, the circulation types also exhibit specific links between certain types and climatic divisions across Saudi Arabia.

Recent summer Arctic atmospheric circulation anomalies in a historical perspective

Abstract. A significant increase in the summertime occurrence of a high pressure area over the Beaufort Sea, the Canadian Arctic Archipelago, and Greenland has been observed since the beginning of the 2000s, and particularly between 2007 and 2012. These circulation anomalies are likely partly responsible for the enhanced Greenland ice sheet melt as well as the Arctic sea ice loss observed since 2007. Therefore, it is interesting to analyse whether similar conditions might have happened since the late 19th century over the Arctic region. We have used an atmospheric circulation type classification based on daily mean sea level pressure and 500 hPa geopotential height data from five reanalysis data sets (ERA-Interim, ERA-40, NCEP/NCAR, ERA-20C, and 20CRv2) to put the recent circulation anomalies in perspective with the atmospheric circulation variability since 1871. We found that circulation conditions similar to 2007–2012 have occurred in the past, despite a higher uncertainty of the reconstructed circulation before 1940. For example, only ERA-20C shows circulation anomalies that could explain the 1920–1930 summertime Greenland warming, in contrast to 20CRv2. While the recent anomalies exceed by a factor of 2 the interannual variability of the atmospheric circulation of the Arctic region, their origin (natural variability or global warming) remains debatable.

Circulation weather types and spatial variability of daily precipitation in the Iberian Peninsula

The relationships between atmospheric circulation patterns and daily Iberian rainfall are here explored at high spatial resolution (0.2°) using the Jenkinson and Collison automated classification scheme with 26 Weather Types (WTs). The WTs were computed by means of the daily EMULATE Mean Sea Level Pressure dataset (EMSLP) while the high resolution precipitation database corresponds to the recent Iberia02 daily gridded precipitation dataset over the 1950-2003 period. Six monthly indexes relating the WTs and precipitation were analyzed: their Frequency, the Mean Precipitation, the Percentage Contribution, the Area of Influence, the Precipitation Intensity and Efficiency. Except for the Frequency of the WTs, all other indexes were evaluated studying their spatial distribution over the Iberian Peninsula, focusing on a WT and a month at time. A small number of WTs (7) was found to capture a high percentage (~70%) of monthly Iberian precipitation. The Westerly WT is the most influent one, followed by the Cyclonic, the Northwesterly and the Southwesterly WTs. Westerly flows, however, do not affect the Mediterranean fringe or the Cantabrian coast, which are dominated by the Easterly and Northerly WTs, respectively. Rainfall along the Mediterranean coastline and the Ebro basin depends on a variety of WTs, but their effects are confined to narrow areas and short temporal intervals, suggesting that local factors such as convective processes, orography and the proximity to a warm water body could play a major role in precipitation processes. We show that the use of daily gridded precipitation dataset holds the advantage of measuring the daily rainfall amount due to each WT directly instead to relying on the predicted values of the regression model as done in previous works.

Statistical–dynamical downscaling for wind energy potentials: evaluation and applications to decadal hindcasts and climate change projections

ABSTRACTA statistical–dynamical downscaling (SDD) approach for the regionalization of wind energy output (Eout) over Europe with special focus on Germany is proposed. SDD uses an extended circulation weather type (CWT) analysis on global daily mean sea level pressure fields with the central point being located over Germany. Seventy‐seven weather classes based on the associated CWT and the intensity of the geostrophic flow are identified. Representatives of these classes are dynamically downscaled with the regional climate model COSMO‐CLM. By using weather class frequencies of different data sets, the simulated representatives are recombined to probability density functions (PDFs) of near‐surface wind speed and finally to Eout of a sample wind turbine for present and future climate. This is performed for reanalysis, decadal hindcasts and long‐term future projections. For evaluation purposes, results of SDD are compared to wind observations and to simulated Eout of purely dynamical downscaling (DD) methods.For the present climate, SDD is able to simulate realistic PDFs of 10‐m wind speed for most stations in Germany. The resulting spatial Eout patterns are similar to DD‐simulated Eout. In terms of decadal hindcasts, results of SDD are similar to DD‐simulated Eout over Germany, Poland, Czech Republic, and Benelux, for which high correlations between annual Eout time series of SDD and DD are detected for selected hindcasts. Lower correlation is found for other European countries. It is demonstrated that SDD can be used to downscale the full ensemble of the Earth System Model of the Max Planck Institute (MPI‐ESM) decadal prediction system.Long‐term climate change projections in Special Report on Emission Scenarios of ECHAM5/MPI‐OM as obtained by SDD agree well to the results of other studies using DD methods, with increasing Eout over northern Europe and a negative trend over southern Europe. Despite some biases, it is concluded that SDD is an adequate tool to assess regional wind energy changes in large model ensembles.

Indirect downscaling of hourly precipitation based on atmospheric circulation and temperature

Abstract. The main source of information on future climate conditions are global circulation models (GCMs). While the various GCMs agree on an increase of surface temperature, the predictions for precipitation exhibit high spread among the models, especially in shorter-than-daily temporal resolution. This paper presents a method to predict regional distributions of the hourly rainfall depth based on daily mean sea level pressure and temperature data. It is an indirect downscaling method avoiding uncertain precipitation data from the GCM. It is based on a fuzzy logic classification of atmospheric circulation patterns (CPs) that is further subdivided by means of the average daily temperature. The observed empirical distributions at 30 rain gauges to each CP-temperature class are assumed as constant and used for projections of the hourly precipitation sums in the future. The method was applied to the CP-temperature sequence derived from the 20th-century run and the scenario A1B run of ECHAM5. For the study region in southwestern Germany ECHAM5 predicts that the summers will become progressively drier. Nevertheless, the frequency of the highest hourly precipitation sums will increase. According to the predictions, estival water stress and the risk of extreme hourly precipitation will both increase simultaneously during the next decades. However, the results are yet to be confirmed by further \\mbox{investigation} based on other GCMs.

Implementation of Polar WRF for short range prediction of weather over Maitri region in Antarctica

India Meteorological Department has implemented Polar WRF model for the Maitri (lat. 70°45′S, long. 11°44′E) region at the horizontal resolution of 15 km using initial and boundary conditions of the Global Forecast System (GFS T-382) operational at the India Meteorological Department (IMD). Main objective of this paper is to examine the performance skill of the model in the short-range time scale over the Maitri region. An inter-comparison of the time series of daily mean sea level pressure and surface winds of Maitri for the 24 hours and 48 hours forecast against the corresponding observed fields has been made using 90 days data for the period from 1 December 2010 to 28 February 2011. The result reveals that the performance of the Polar WRF is reasonable, good and superior to that of IMD GFS forecasts. GFS shows an underestimation of mean sea level pressure of the order of 16–17 hPa with root mean square errors (RMSE) of order 21 hPa, whereas Polar WRF shows an overestimation of the order of 3–4 hPa with RMSE of 4 hPa. For the surface wind, GFS shows an overestimation of 1.9 knots at 24 hours forecast and an underestimation of 3.7 knots at 48 hours forecast with RMSE ranging between 8 and 11 knots. Whereas Polar WRF shows underestimation of 1.4 knots and 1.2 knots at 24 hours and 48 hours forecast with RMSE of 5 knots. The results of a case study illustrated in this paper, reveal that the model is capable of capturing synoptic weather features of Antarctic region. The performance of the model is found to be comparable with that of Antarctic Meso-scale Prediction System (AMPS) products.

Simulated winter circulation types in the North Atlantic and European region for preindustrial and glacial conditions

Winter circulation types under preindustrial and glacial conditions are investigated and used to quantify their impact on precipitation. The analysis is based on daily mean sea level pressure fields of a highly resolved atmospheric general circulation model and focuses on the North Atlantic and European region. We find that glacial circulation types are dominated by patterns with an east‐west pressure gradient, which clearly differs from the predominantly zonal patterns for the recent past. This is also evident in the frequency of occurrence of circulation types when projecting preindustrial circulation types onto the glacial simulations. The elevation of the Laurentide ice sheet is identified as a major cause for these differences. In areas of strong precipitation signals in glacial times, the changes in the frequencies of occurrence of the circulation types explain up to 60% of the total difference between preindustrial and glacial simulations.