CL2.3

Lamb Weather Types (LWT, 1972) are a classical method in synoptic climatology consisting in a subjective classification of atmospheric circulation based on an expert interpretation of sea-level pressure (SLP) fields centered on the British Isles. Jenkinson-Collison (1977) made a subsequent adaptation of the original LWT approach (JC-WT) to obtain an automated, objective method that is also applicable to other locations. In spite of its potential for an objective large-scale circulation typing in extratropical regions of the world, to date, JC-WT has been seldom used in the Southern Hemisphere, which requires a minor modification of its original formulation to this aim. This study sets the grounds for the adoption of the JC-WT classification worldwide by applying it centered in all cells of a 2.5º global grid (excluding a 10º wide equatorial band). We present an open, 6-hourly JC-WT catalogue on this grid for the period 1979-2005 built from five popular reanalysis products (https://doi.org/10.5281/zenodo.5761258). This catalogue is used to evaluate the observational uncertainty linked to the representation of atmospheric circulation in the different reanalyses.

Overall, we find empirical evidence of the suitability of the JC-WT classification for the regional assessment of atmospheric circulation outside the tropics, including the Southern Hemisphere. We also find important differences in the JC-WT representation by different reanalyses in some regions, such as the Tibetan Plateau, the Andes, Greenland and Antarctica, in light of the comparison of their respective occurrences and transition probabilities. These inconsistencies may compromise the robustness of circulation-based model assessments relying on a single reanalysis in these regions.

How to cite: Fernández-Granja, J. A., Brands, S., Bedia, J., Casanueva, A., and Fernández, J.: A worldwide assessment of the Jenkinson-Collison atmospheric circulation classification and observational uncertainty based on different reanalysis., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5784, https://doi.org/10.5194/egusphere-egu22-5784, 2022.

Automated classifications of atmospheric circulations are a well-known tool to characterize large-scale patterns that predominantly determine day-to-day weather variations. Through its potential influence on the relative frequency of circulation patterns, global warming can also enhance or mitigate the occurrence of extreme weather events.

Here, we use a subset of 22 CMIP6  global climate models (GCMs) to assess their ability to capture these recurrent circulation patterns and their implication for the European climate and its projected changes.

We investigate links between synoptic circulations and short-term meteorological drought events that span one month. We employ the automated Jenkinson-Collison classification to determine daily atmospheric features based on mean sea-level pressure. We compute the conditional probability of dry days related to each circulation type. Furthermore, we confirm the influence of these patterns on the occurrence of dry months by computing the monthly relative frequency anomalies of the synoptic circulations given months where the Standardized Precipitation Index (SPI) was below minus 1. We evaluate the ability of the historical runs of global climate models (GCMs) to reproduce the observed features from the ERA5 reanalyses over the 1961-1990 reference period. Links between the mean directional flow characteristics of the circulation types and the dry days and months are well represented by most GCMs. The most robust relationships were found for the anticyclonic, easterly, and low flow types. These circulations are generally associated with a lack of precipitation and therefore show higher than average occurrences during dry months. 

How to cite: Herrera Lormendez, P., John, A., Douville, H., and Matschullat, J.: A CMIP6 evaluation of summer synoptic circulations linked to short-term droughts over Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4665, https://doi.org/10.5194/egusphere-egu22-4665, 2022.

Based on a centenary meteorological observatory, the mean temperature and frequency of heat waves at the city of Barcelona is increasing due to global warming. The number of heat wave episodes by climatic periods of 30 years, with a specific percentile 95 (P95) of summer maximum temperature, has been increased from 23 (1951-1980) with a P95 of 31˚C to 59 days (1991-2020) with a P95 of 32.8˚C.  Therefore, it is necessary to analyse weather circulation to understand the reason and predict the possible future impacts. In this study, heat wave events for 1951-2020 have been analysed with ERA5 data, in order to classify the different synoptic patterns and each evolution. It is possible to get climate trends from past reanalysis data, but it is also interesting to predict future possibilities. Most of the previous research is focused on temperature and precipitation while the target of this study is the mesoscale and synoptic circulation. For this reason, Coordinated Regional Climate Downscaling Experiment (CORDEX) data at 0.11˚ grid mesh has been used to analyse the future scenarios compared to the historical simulations of the same source. More specifically, for this study, it was necessary to download mean sea level pressure (MSLP) and 500hPa geopotential height (GHP) data. Due to the big amount of information, it has been applied a statistical method called Principal Component Analysis (PCA) to simplify and reduce the dimensions of the sample. Afterwards, working on a cluster analysis has been necessary to classify the simplified data. The synoptic patterns remain relatively constant throughout the last climatic periods according to ERA5, being the synoptic type “Shallow Cyclone or Undetermined pressure gradient” the recurrent type to cause heat wave periods in summer. CORDEX data shows more dynamism in comparison to ERA5 reanalysis and expects to remain similar until 2100. Northwest and north advections are expected to increase by 7.3% and 6.6% respectively and lows or cyclones are expected to decrease by 8.3% according to RCP4.5 scenarios.

How to cite: Ventura, S., Villalba, G., Miró, J. R., and Peña, J. C.: Past and future climate trends focused on synoptic patterns in the northeast of the Iberian Peninsula, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8214, https://doi.org/10.5194/egusphere-egu22-8214, 2022.

Seasonal cycle including day-to-day fluctuations shows great variety from region to region even among the middle/higher latitudes. Thus to know such detailed seasonal cycle for each region is the common basis for deeper understanding of (1) seasonal backgrounds of extreme meteorological or climatological events and (2) that of cultural generation leading to the cultural understanding education through the “seasonal feeling”. For example, the “seasonal feeling” of the severe winter relating to the traditional event for driving the winter away (“Fasnacht”) around Germany might be greatly reflected by the intermittent appearance of the extremely low temperature events, although the winter mean temperature there is lower only by about 3~5℃than in the southern part of the Japan Islands area.

Hamaki et al.(2018, although written in Japanese) suggested, based on the case study for 2000/01 winter, that the appearance of such events with large intraseasonal variation are greatly controlled by that of the Icelandic low. Furthermore, a case study for the same winter by Miyake and Kato (EGU2020 Assembly) pointed out that the rapid seasonal increase in the appearance frequency of extremely low temperature events there as the intraseasonal variation around mid-December, although the seasonal mean the Icelandic low already appeared in mid-October.

However, the climatological appearance features of the extremely low temperature events for longer periods should be examined further. Thus we will describe the detailed synoptic climatological features for 1971/72 to 2010/11 winters, based on the NCEP/NCAR reanalysis data. In this study, the days with daily mean surface air temperature less than or equal to -7℃ are referred to as the "extremely low temperature days".

Amplitude of the intraseasonal variation of the surface air temperature around Germany increased seasonally in association with the beginning of the nearly minimum seasonal mean temperature period (around December to February), resulting in the seasonal increase in the appearance frequency of the extremely low temperature days from around December. Such features are clearly found for the 10 winters (referred to as the "typical years") of the total 40 winters.

In the typical years, amplitude of the intrasesaonal variation increased rapidly around December (although this timing is somewhat different among the typical winters) and the persistent extremely low temperature days for about a week appeared two or three cycles in a winter. According to the case study for a typical winter (e.g., 1984/85 winter), while the temperature around Germany was relatively higher at the eastward shift phase of the Icelandic low due to the strong warm air advection by the SW-ly wind, the temperature was extremely low there when the Icelandic low was weakened and retreated westward as pointed out for the case study for 2000/2001 by Hamaki et al. (2018). It is also noted that the low corresponding to a part of the equivalent barotropic wave train lined up zonally was located around Germany in the extremely low temperature phase in 1984/85 winter.

How to cite: Kato, K., Otani, K., Miyake, C., Nagayasu, K., and Kato, H.: Synoptic climatological analysis on the appearance features of extremely low temperature days around Germany for 1971/72 to 2010/11 winters, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2186, https://doi.org/10.5194/egusphere-egu22-2186, 2022.

The aridity of the Southern Hemisphere subtropical latitudes is frequently punctuated by near-planetary scale bands of cloud that diagonally link the tropics to the mid-latitudes. These cloud bands preferentially occur in the subtropical convergence zones situated in each of the three ocean basins. However, much of the research focused on these regions has considered seasonal averages, which are not suitable for fully capturing the synoptic-scale variability of these events. The MetBot, first developed to identify cloud bands over southern Africa and now successfully adapted to the South American area, overcomes this problem by identifying these tropical-extratropical cloud bands in daily data. In this study, we use the near-real-time version of the MetBot, currently implemented to monitor the progress of cloudband seasons over the Southern Hemisphere. Cloud bands are identified in the daily outgoing longwave radiation data from the High-Resolution Infrared Radiation Sounder (HIRS), developed by the National Oceanic and Atmospheric Administration (NOAA), with a spatial resolution of 1° and latency time of a couple of days (Lee, 2011). The results of the near-real-time monitoring area are available at <https://hart-ncg.github.io/real-time/about.html>. Here, we considered the cloud bands dataset with events identified across the Southern Hemisphere between 1979 and 2020 to evaluate their variability and recent changes. The climatological analysis highlights four hotspot regions: South Pacific and South America, which are the strongest; southern Africa, with events only forming through austral summer; and Australia, with summer (winter) events over the eastern (western) coast. The hemispheric scale of the results provides a unified view of the interannual and intraseasonal variability of the cloud bands, including the preferential location of the convective activity during different ENSO phases. By isolating the systems responsible for most of the rainy season precipitation over the subtropics, we also identify changes in the cloud band activity in recent years and their impact on the total precipitation. Future applications include the use in tandem with S2S forecast data, as currently being implemented over South America, as well as a tool to evaluate historical and future climate model simulations of various resolutions.  

Lee, Hai-Tien and NOAA CDR Program (2011): NOAA Climate Data Record (CDR) of Daily Outgoing Longwave Radiation (OLR), Version 1.2. NOAA National Climatic Data Center. doi:10.7289/V5SJ1HH2 

How to cite: Zilli, M. and Hart, N.: Variability and changes of tropical-extratropical cloudband events over the Southern Hemisphere using a synoptic climatology approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12800, https://doi.org/10.5194/egusphere-egu22-12800, 2022.

In the past, one widely used technique to diagnose Lagrangian aspects of the atmospheric circulation has been the computation of trajectories. Trajectories provide detailed information along the pathways of individual parcels, but one has to consider a vast amount of them in order to obtain continuous-in-time, volume-filling information. As a consequence, analysing trajectories can be a painstaking task. To overcome this problem, we developed an alternative method allowing one to continuously diagnose Lagrangian information about the atmospheric circulation on a Eulerian grid. The method is based on the advection of passive tracer fields and includes a relaxation term. One thus obtains accumulated Lagrangian information, such as the recent meridional or vertical parcel displacement or the recent parcel-based diabatic heating, for each grid point at any time step. This convenient output format allows one to analyse large data sets (such as reanalysis data) in a straightforward manner. We suggest our method to be particularly useful in the field of synoptic climatology. Here, we present the underlying idea of the method and motivate its utility on the basis of examples that make use of reanalysis data.

How to cite: Mayer, A. and Wirth, V.: Diagnosing Lagrangian aspects of the atmospheric circulation by Eulerian tracer advection with relaxation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1189, https://doi.org/10.5194/egusphere-egu22-1189, 2022.