Large-scale atmospheric circulation dynamics are the major driver of near surface climatic and environmental variability. Synoptic climatology examines atmospheric circulation dynamics and their relationship with near surface environmental variables. Within synoptic climatological analyses, a wide variety of methods is utilized to characterize atmospheric circulation (e.g., circulation and weather type classification, regime analysis, teleconnection indices). Various linear and non-linear approaches (e.g., multiple regression, canonical correlation, neural networks) are applied to relate the circulation dynamics to diverse climatic and environmental elements (e.g., air temperature, air pollution, floods).
The session welcomes contributions from the whole field of synoptic climatology. This includes application studies for varying regions, time periods (past, present, future) and target variables and in particular contributions on the development and the comparison of methods (e.g., varying circulation type classifications) and conceptual approaches (e.g., circulation types versus circulation regimes).
vPICO presentations: Tue, 27 Apr
Global Climate Models (GCMs) generally exhibit significant biases in the representation of large-scale atmospheric circulation. Even after bias adjustment, these errors remain and are inherited to some extent by the derived downscaling products, impairing the credibility of future regional projections.
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, 1972). We undertake a comprehensive assessment based on several evaluation measures, such as Kullback-Leibler divergence (KL), Relative Bias and Transition Probability Matrix Score (TPMS), used to assess the ability of the GCMs in reproducing not only the frequencies of the different Lamb Weather Types (LWTs), but also the daily probabilities of transitions among them. We show that the novel TPMS score poses a stringent test on the GCM performance, allowing for a convenient model ranking based on each model’s transition probability matrix fingerprint. Deficiencies in the transition probabilities from one LWT to another might explain the misrepresentation of the synoptic conditions and their frequencies by the GCMs. Four different reanalysis products of varying characteristics are considered as pseudo-observational reference in order to assess observational uncertainty.
Our results unveil an overall improvement of salient atmospheric circulation features of CMIP6 with respect to CMIP5, demonstrating the ability of the new models to better capture key synoptic conditions. The improvement is consistent across observational references, although it is uneven across models and large frequency biases still remain for the dominant LWTs in many cases. In particular, some CMIP6 models attain similar or even worse results than their CMIP5 counterparts. 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.
How to cite: Fernandez-Granja, J. A., Casanueva, A., Bedia, J., and Fernández, J.: Transition probabilities between synoptic weather types as a fingerprint for climate model evaluation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7973, https://doi.org/10.5194/egusphere-egu21-7973, 2021.
Circulation classifications are a simple tool given their ability to portray aspects of day-to-day weather. As we start facing a dynamical response in general circulation patterns due to anthropogenic global warming, circulation changes can enhance or mitigate regional and local behaviour of extreme weather events.
An automatic weather type (WT) classification, developed by Jenkinson-Collison, is used to evaluate past and future changes in seasonal frequencies of synoptic weather patterns over central and western Europe. A set of three reanalyses and eight Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are used, based on daily Sea Level Pressure (SLP) data.
Discrepancies are found in some of the model outputs as some fall short of capturing interannual variabilities when compared to reanalyses. Cyclonic and westerly circulations tend to be overestimated, whereas anticyclonic are underestimated.
Based on the historical data and Shared Socioeconomic Pathway 5 (SSP5-8.5) scenario, the evaluated trends suggest more robust signals during the summer half-years given their lesser synoptic-scale variability. During this season, increasing frequencies are found for the WT characterized by weak pressure gradients, mostly at the expense of decreasing frequencies of the westerlies. Our findings indicate that the time of emergence of these signals only occurs towards the end of the 21st century, even in such a high-emission scenario.
How to cite: Herrera-Lormendez, P., Matschullat, J., and Douville, H.: Past and future trends in large-scale atmospheric circulations over Europe: Assessment of the Jenkinson-Collison classification with reanalyses and CMIP6, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3150, https://doi.org/10.5194/egusphere-egu21-3150, 2021.
Atmospheric circulation regimes can be used to study links between regional weather and other climate processes, like sudden stratospheric warmings. For these studies it is important to know whether there is any background non-stationarity in the regimes themselves. To identify regime non-stationarity model ensemble data is needed to have sufficient data. However, models are noisy in their representation of circulation regimes making obtaining the signal difficult. We propose a new method, in the form of a constraint on the ensemble-member similarity in the clustering method, to identify the signal of the non-stationary regime dynamics.
We use ECMWF SEAS5 hindcast data to identify six wintertime circulation regimes over the Euro-Atlantic sector (NAO+/-, Atlantic Ridge (AR) +/- and Scandinavian Blocking (SB) +/-), which has been found to be the optimal number of regimes in a previous study. Implementing the constraint leads to more robust regimes and the identification of a stronger inter-annual signal in the regime occurrence rates than without the constraint. The clearest signal on inter-annual timescales is found during strong El Niño years. During those years the NAO+ becomes less frequent, while the SB- occurs more often. The signal in the occurrence rate of the NAO- is weaker than for the NAO+. Without the implementation of the constraint this difference in the strength of the signal between the two phases of the NAO cannot be detected. Thus, the constraint on the ensemble-member similarity allows for identifying a non-stationary signal that otherwise is more difficult to obtain.
How to cite: Falkena, S., de Wiljes, J., Weisheimer, A., and Shepherd, T.: Non-Stationarity of Wintertime Atmospheric Circulation Regimes in the Euro-Atlantic Sector, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2087, https://doi.org/10.5194/egusphere-egu21-2087, 2021.
Coastal lows are prevalent along the coast of Chile. They are thermal lows that propagate poleward. The leading edge of the coastal low is associated with easterly winds, warm surface temperatures and clear skies. They are forced by the reversal of the typical meridional pressure gradient by the passage of synoptic scale high pressure systems embedded in the extratropical storm track. Coastal lows are an important feature of Southwestern South America, as they are involved in some of the major air pollution episodes in Central Chile, as well as are a factor in summertime bushfire events. Similar coastally trapped disturbances occur in Southeastern Australia, South Africa and the west coast of North America.
In this work, we characterize the climatology of coastal lows in Chile using surface pressure, wind and geopotential height at 500 hPa from the ERA5 reanalysis (1979 to 2018). These high resolution fields allow, for the first time, to characterize the behavior of coastal lows in the mesoscale, which were only coarsely represented in previous reanalyses. We identify the events using a method based on the drop of surface pressure and winds from the associated coastal low level jet. We found an average of 39 events per year, developing mostly during winter and spring. We found that the coastal low demise occurs typically at around 19:00 Local Time. We also characterize the propagation speed of the low along the coast finding a very striking change from about 40 m/s north of 30ºS to about 17 m/s south of 30ºS. We will discuss our findings in the light of dynamical theories proposed for the propagation of these disturbances.
How to cite: Gómez Contreras, Á., Carrera Ávila, N., Rapanague, M. J., and Rondanelli Rojas, R.: Coastal lows climatology along the Chilean coast using ERA5 reanalysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5656, https://doi.org/10.5194/egusphere-egu21-5656, 2021.
The Northwest Atlantic and the Northwest Pacific are regions of strong temperature gradients and hence favourable locations for wintertime cyclone intensification co‐located with the storm tracks. Although the Gulf Stream and the Kuroshio Extension are both western boundary currents with similar characteristics, the SST gradient is markedly stronger across the Gulf Stream. Further, upper-level flow is stronger and more zonal over the Kuroshio Extension. To estimate the relative contribution of the SST front to the evolution of cyclones and to identify the mechanisms for cyclone intensification in the two regions, we track individual cyclones and categorise them depending on their propagation relative to the SST front. We focus on cyclones staying either on the cold (C1) or warm (C2) side of the SST front, and on cyclones that cross the SST front from the warm to the cold side (C3). Comparing these categories, we find that low-level baroclinicity, particularly arising from the land–sea contrast, drives the higher intensification of cyclones in C1 and C3 in the Gulf Stream region, with the propagation of those cyclones near the left exit region of the North Atlantic jet contributing to the higher intensification and precipitation. In the Kuroshio region on the other hand, the land–sea contrast plays a less prominent role for the low‐level baroclinicity. Cyclones remaining on the warm side of the Kuroshio SST front (C2), as well as those crossing the SST front from the warm to the cold side (C3) are characterized by higher intensification, associated with a stronger upper-level jet in the Pacific. Comparing the different cyclone categories, there is no direct effect of the SST front on cyclone intensification in both regions. However, the SST front contributes to the climatological low‐level baroclinicity, providing a conducive environment for cyclone intensification for the cyclones crossing the SST front.
How to cite: Tsopouridis, L., Spensberger, C., and Spengler, T.: Different cyclone characteristics along the Gulf Stream and Kuroshio SST front regions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7703, https://doi.org/10.5194/egusphere-egu21-7703, 2021.
The studies of associations between solar inputs and climate are mostly designed for winter or cold period; whereas the knowledge about these associations during spring on a day-to-day time scale are very scarce. Therefore, the aim of this study is to detect the response of spring air temperature (T), relative humidity (RH), and atmospheric pressure (ATP) to variation in teleconnection indices and space weather variables on the day-to-day timescale during the period of 1998–2017 in six cities of Eastern part of the Baltic region. We created a multivariate linear regression model for weather variables including month, the linear and seasonal trend, different teleconnection patterns, El Niño–Southern Oscillation (ENSO), the Quasi-biennial Oscillation (QBO) phase, the presence of Sudden Stratospheric Warming (SSW), and space weather variables.
The multivariate models for the mean daily weather variables showed a positive association between T and the daily Arctic oscillation (AO), monthly Scandinavian pattern (SCA) indices, solar proton events (SPEs) with a lag of 1-9 days, and solar wind dynamic pressure (P) with a lag of 1-2 days and negative association between T and East Atlantic/West Russia (EA/WR) index. The linear and seasonal trends, the presence of SSW during March, and changes in AO, EA/WR, and SCA indices explained about 73% of the variation in mean daily T in the investigated region in spring. The presence of the daily mean proton flux of > 10 MeV and energy over 10 pfu with a lag of 1-9 days and higher P with a lag of 1-2 days were also related to higher mean T. The mean RH positively correlated with a long-term and short-term variation in galactic cosmic rays (GCR) and solar wind speed (SWS) with a lag of 0-6 days and negatively correlated with EAWR and NINO3.4 indices. The seasonal variation, the presence of SSW during March, the QBO phase, and the changes in the EA/WRI and ENSO explained over 38% of variation in the daily mean RH in spring.
The mean ATP was negatively associated with both long-term and short-term changes in GCR and positively associated with the North Atlantic oscillation (NAO), EA/WR, and SCA indices, By component of interplanetary magnetic field with a lag of 2 days, P, days of Stream Interaction Regions (SIRs), and SWS with a lag of 4-6 days. These space weather variables had stronger effect on spring ATP in the eastern part of the Baltic region as compared to stratospheric events and teleconnection patterns. Results of the present study show the significant short-term effects of SSW, SPEs, SIRs, and solar wind variables on spring weather pattern in the Eastern part of the Baltic region.
How to cite: Kacienė, G., Venclovienė, J., and Kiznys, D.: Statistical associations of teleconnection indices and space weather with spring weather pattern in the Eastern Baltic region, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16522, https://doi.org/10.5194/egusphere-egu21-16522, 2021.
The North Hemisphere winter stratosphere is frequently affected by large and rapid temperature increases, known as Sudden Stratospheric Warmings (SSWs). The strongest and most spectacular events, known as the Major Mid-Winter Warmings, cause a temporary reversal of climatological westerly zonal mean winds and, in some cases, even the breakup of the stratospheric polar vortex into several smaller vortices. The following downward propagation of stratospheric anomalies to the upper and middle troposphere has been associated with significant weather anomalies resembling a negative Northern Annular Mode (NAM) regime over Eurasia and North America. These events are often involved in winter weather extremes in Northern Hemisphere, therefore a better understanding of their occurrence and development could be helpful for the improvement of medium term forecast of extreme meteorological conditions.
In order to assess the impact of Sudden Stratospheric Warmings on surface weather conditions in central and eastern Europe, all major SSW events identified in the period 1979 – 2020 were classified in 5 major types using a k-means cluster analysis method. Then, in order to determine the changes in tropospheric circulation as an effect of each SSW, we identified the main weather circulation types in Europe by performing a cluster analysis of 500 hPa geopotential height and sea level pressure. After that, the changes in frequencies of these types, as well as the mean composite anomalies of the two aforementioned parameters were assessed. This has been done for three intervals: one month before and two months after a SSW event. The surface and lower troposphere impact was studied using the mean composite anomalies of several parameters: 2 m temperature, total precipitation amount, snowfall and snow depth, for the same intervals.
The results show a great deal of variability in the surface effects of SSW events. The general impact of SSW events consisted in a tendency towards a diminishing of the frequency of westerlies, and a subsequent increase in the frequency of both Mediterranean cyclones and high latitude blocking conditions, with their associated temperature and precipitation anomalies. Also, a second major output of the study indicates that in central and eastern Europe these SSW events lead to harsh winter conditions in 30% of cases, but also to abnormal warm winters intervals in other 25% of cases, depending on the type of the SSW. However, some events show a less marked impact on tropospheric weather, while other SSW do not propagate from the stratosphere to the upper and middle troposphere. Taking into account the type and characteristics of each SSW might significantly increase the predictability of their tropospheric effects.
How to cite: Hrițac, R., Sfîcă, L., and Ichim, P.: Tropospheric impact of Sudden Stratospheric Warmings in Central and Eastern Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2896, https://doi.org/10.5194/egusphere-egu21-2896, 2021.
The estimation of regional extreme events (heavy precipitation and droughts) in Central Europe under ongoing climate change especially includes an evaluation of the relationship between atmospheric circulation types and regional droughts taking place in the bilateral research project WETRAX+ (WEather Patterns, Cyclone TRAcks, and related precipitation EXtremes). The study area is located in the south of central Europe, including Austria, parts of Germany, Switzerland, and the Czech Republic.
For a precipitation-conditioned circulation type classification, atmospheric variable fields from gridded daily JRA55 reanalysis data (Japan Meteorological Agency 2018) and gridded daily precipitation data based on 1756 weather stations in the study area (Zentralanstalt für Meteorologie und Geodynamik 2018) were used for the observation period 1961 to 2017. Seven different regional climate model runs of the Euro-Cordex – Initiative and from ReKliEs-De (Regional Climate Projections Ensemble for Germany) as well as three runs of the global climate model ECHAM6 (greenhouse gas scenario RCP 8.5) were used to estimate future changes in two projection periods (2031-2060 and 2071-2100).
The large-scale atmospheric circulation types have been derived using a non-hierarchical cluster analysis provided in the COST733 Classiﬁcation Software. The drought-relevant circulation types are determined according to relative frequencies of circulation type days under a particular percentile of precipitation: If at least 20 percent of the circulation type days are below the 20th percentile of precipitation, the circulation type is defined as drought relevant. Drought-relevant circulation types are examined in terms of trends, persistence, changes in monthly occurrence frequencies, and within-type variability. When transferring the circulation types to the climate model data, each single day of the projection period is assigned to the circulation type to whose centroid fields the respective single fields have the smallest Euclidean distance.
During the observation period, the trend analyses show that the occurrence of drought-relevant circulation types is significantly more often associated with higher temperatures and lower relative humidity. First results of the analysis for the future climate show an increase of central high-pressure areas over Central and Eastern Europe for the months April to September. Anticyclonic weather conditions with a resulting southwesterly flow occur less frequently.
How to cite: Thanheiser, S.: Variability and changes of drought-relevant circulation types in southern central Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2642, https://doi.org/10.5194/egusphere-egu21-2642, 2021.
This work analyses the link between Western Europe large-scale circulation and precipitation variability in the Northern French Alps from 1950 to 2017. We consider simple descriptors characterizing the daily 500hPa geopotential height fields. They are the Maximum Pressure Difference - representing the range of geopotential heights over Western Europe -, and the singularity - representing the mean distance between a geopotential shape and its closest analogs, i.e. the way this geopotential shape is reproduced in the climatology. These descriptors are compared to the occurrence of different atmospheric influences - Atlantic, Mediterranean, Northeast, Anticyclonic - and to the leading mode of large-scale circulation variability over Europe - the North Atlantic Oscillation (NAO) - for explaining precipitation variability in the Isère River catchment from one day to 10 years. We show that the Maximum Pressure Difference and the singularity of geopotential shapes explain a significant part of precipitation variability in the Northern French Alps from 10 days to 10 years, especially in winter (correlation values of 0.7). These descriptors provide much better performance than NAO and the same performance as the occurrence of the Atlantic influence, which is the best performing atmospheric influence. This means that simple characteristics of large-scale circulation - that are easy to implement - provide as much information as weather pattern classification to explain precipitation variability in the Northern French Alps.
How to cite: Blanc, A., Blanchet, J., and Creutin, J.-D.: Linking Large-scale Circulation Descriptors to Precipitation Variability in the Northern French Alps, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12881, https://doi.org/10.5194/egusphere-egu21-12881, 2021.
The North Atlantic Oscillation (NAO) has been widely recognized as one of the main patterns of atmospheric variability over the northern hemisphere, helping to understand variations on the North Atlantic Jet (NAJ) position and its influence on storm-tracks, atmospheric blocking and Rossby Wave breaking. Among several relevant teleconnection patterns identified through different timescales, the most prominent ones are found for northern Europe during winter months, when positive (negative) phases of NAO are related to wetter (drier) conditions. Although it is not well defined yet, an opposite connection is observed for the Mediterranean region, where negative NAO values are often associated with high precipitation. Therefore, the main goal of this study is to identify which regions and periods of the year are the most susceptible to abundant NAO-related precipitation throughout the Italian Peninsula. For doing so, the last 42 years period (1979-2020) was analysed using the Fifth Generation ECMWF Atmospheric ReAnalysis of the Global Climate (ERA5). The NAO index was calculated using the Mean Sea Level Pressure (MSLP) extracted from the nearest gridpoints to Reykjavik, Ponta Delgada, Lisbon and Gibraltar, with a time resolution of one hour and horizontal spatial resolution of 0.25ºx0.25º. Both NAO index and MSLP time series were validated for different timescales (hourly, daily, monthly and seasonal) using the Automated Surface Observing System data and the Climatic Research Unit (CRU) high-resolution dataset (based on measured data). High correlations, ranging from 0.92 to 0.98, were found for all stations, timescales and evaluated parameters. To quantify the influence of NAO over the Mediterranean region, the monthly averaged ERA5 ‘total precipitation’ data over the Italian Peninsula [35-48º N; 5-20º E] were used. As expected, the results concerning NAO x Precipitation presented the best correlations when analysed monthly, confirming some of the already known NAO signatures over the Italian Peninsula: higher correlations during winter and over the Tyrrhenian coast, and lower correlations during summer and over the Apennines, the Adriatic Sea and the Ionian Sea. On the other hand, the precipitation over the Alps and the Tunisian coast presented a remarkable signature of positive NAO values that, despite a lower statistical significance (85-90%), is in agreement with recent findings of observational studies. In addition, significant negative correlations were identified for the spring and autumn months over the Tyrrhenian area. Among those, the high correlations found during May are particularly interesting, as they follow the behaviour described in recent studies performed using the same high-resolution dataset (ERA5), which have identified an increased number of cyclones over the Mediterranean during this month. This connection suggests that NAO could also be used to explore the potential penetration of the North Atlantic depressions into the Mediterranean Basin.
Keywords: NAO; Teleconnections; ERA5; ReAnalysis; Mediterranean; Climatology.
How to cite: Lorenzo Sánchez, P. and Aragão, L.: North Atlantic Oscillation-related impacts on precipitation over the Italian Peninsula during the 1979-2020 period, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9183, https://doi.org/10.5194/egusphere-egu21-9183, 2021.
Climate change is altering the Earth’s atmospheric circulation and the dynamic drivers of extreme events. Extreme weather events pose a great potential risk to infrastructure and human security. In Montréal (Québec, Canada) long-duration mixed precipitation events (freezing rain and/or ice pellets) are high-impact cold-season hazards and an understanding of how climate change alters their occurrence is of high societal interest.
Here, we introduce a two-staged deep learning approach that uses the synoptic-scale drivers of mixed precipitation to identify these extreme events in archived climate model data. The approach is destined for the application on regional climate model (RCM) data over the Montréal area. The dominant dynamic mechanism leading to mixed precipitation in Montréal is pressure-driven channeling of winds along the St. Lawrence river valley. The identification of the synoptic-scale pressure pattern related to pressure-driven channeling is a visual image classification task that is addressed with supervised machine learning. A convolutional neural network (CNN) is trained on the classification of the synoptic-scale pressure patterns by using a large training database derived from an ensemble of the Canadian Regional Climate Model version 5 (CRCM5). The CRCM5 is to our knowledge the only RCM available so far that employs the diagnostic method by Bourgouin to simulate mixed precipitation inline and thus delivers training examples and labels for this supervised classification task.
The CNN correctly identifies 90 % of the Bourgouin mixed precipitation cases in the test set. The weak point of the approach is a high type I error, which is enhanced in a second stage by applying a temperature condition. The evaluation on an CRCM5 run driven by ERA-Interim reanalysis reveals a still low precision of 21 % and thus a Matthews correlation coefficient of 0.39. The deep learning approach can be applied to ensembles of regional climate models on the North America grid of the Coordinated Regional Downscaling Experiment (CORDEX-NA).
How to cite: Mittermeier, M., Bresson, É., Paquin, D., and Ludwig, R.: A deep learning approach for the identification of the synoptic-scale drivers of long-duration mixed precipitation in Montréal (Canada), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4334, https://doi.org/10.5194/egusphere-egu21-4334, 2021.
Tropical Atlantic variability modes can influence atmospheric circulation impacting the precipitation regimes over South American and the intensity of the meteorological systems associated. The objective of this work was to analyse the centennial variability and trends of the zonal and meridional modes in the Tropical Atlantic Ocean and their influences in the precipitation, focusing on the North and Northeast of Brazil. The zonal mode was estimated using the ATL3 index, calculated by the monthly sea surface temperature anomaly (SSTa) within 3ºS-3º N and 20ºW-0. The AMM index represents the meridional mode and was obtained by the difference of the monthly SSTa between the North (5-20ºN and 60ºW-10ºE) and South (20ºS-5ºN and 60ºW-10ºE) Atlantic. The indices were calculated for three reanalyses, NOAA ERSST v4, ERA20C and ERA-Interim, and compared to the observational dataset OISSTV2 using correlation for the 1982-2010 period. The results showed a positive trend in both indices considering the period of 1900-2010 for the two centennial reanalyses (NOAA ERSST v4 and ERA20C). However, the trend is higher for the ATL3 index and lower for the AMM considering the NOAA reanalysis. The monthly precipitation was also used to analyse the relationship between the indices and precipitation pattern. The correlation between ATL3 and AMM and the precipitation field using the NOAA reanalysis showed that ATL3 positively influences rain over northeastern Brazil, throughout the Tropical South Atlantic, and northwestern Africa between 1900 and 2010. The opposite is observed relative to AMM, once anomalies of negative (positive) precipitation in the Southern (Northern) Hemisphere are related to a positive SSTa in the region. These results may be related to the most intense SSTa in the northern tropical Atlantic, which shifts the ITCZ, promoting more precipitation further north, and favors the hurricane season All reanalyses represented the indices in agreement with observations, however, the statistical parameters were better for with the ERA-Interim. A possible reason is that ERA-Interim is a newer reanalysis, with more observed assimilated data. Moreover, it has a finer resolution when compared to the other datasets, which contributes to a better representation of the precipitation patterns. In conclusion, ATL3 positively influences precipitation in the North and Northeast Brazilian regions, as the warmer SST drives the position of the ITCZ. Therefore, the observed increasing trend in the precipitation over this region over the past years was associated with the increase in SSTa over the Tropical Atlantic, which may favor precipitation in the north and northeast of Brazil.
How to cite: Cardoso, A. and Wainer, I.: Modes of variability in the Tropical Atlantic and its influences on the precipitation regime in Brazil, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15509, https://doi.org/10.5194/egusphere-egu21-15509, 2021.
During austral summer, persistent tropical-extratropical (TE) cloud bands, such as the South Atlantic Convergence Zone (SACZ) over South America, link tropical humid areas to the subtropics. Changes in circulation due to global warming is already impacting the location and duration of these TE cloud bands, affecting the hydrological regime of the subtropics. In this study, we present an automatic object-based identification of TE cloud bands which we utilize to obtain an event set of TE cloud bands over South America. This approach and our newly-identified sample base are ideal for understanding interactions between the variability and change in the regional mean state and synoptic-scale weather systems. TE cloud bands are responsible for almost 60% of the subtropical precipitation during the South America rainy season (November to March), mostly produced by SACZ events, a TE cloud band persisting for four or more days. Their location and persistence are modulated by the propagation of synoptic-scale extratropical disturbances interacting with intraseasonal variability in the basic state upper-level zonal wind. The persistent SACZ events (i.e., lasting four or more days) are supported by upper-level westerly anomalies over the subtropics caused by an anomalous trough in the subtropical jet which favours the propagation extratropical disturbances deeper into the tropics. Conversely, transient events occur when the Bolivian High is displaced/expanded southeastward, resulting in upper-level easterly winds occurring over subtropical latitudes and blocking the equatorward propagation of Rossby waves.
In recent decades, changes in circulation due to global warming has affected the basic-state circulation, resulting in different impacts in transient and persistent TE events throughout the rainy season. Over South America, the number of days with TE events has decreased during the rainy season peak but increased during onset and cessation months, resulting in the displacement of accumulated precipitation into early and late summer. These results are obtained by comparing two periods: 1979-1996 and 1997-2018, excluding ENSO years. These synoptic-scale changes are related to changes in the position of the subtropical jet and its trough, impacting on the propagation of RW towards South America. In the beginning (November) and end (February) of the rainy season, the westerlies have become stronger over subtropical South America, favouring the development of more persistent events and resulting in an increase in the total precipitation during TE events. During the peak of the rainy season (December and January), changes in upper-level circulation have reduced the conditions necessary to the development of TE events, affecting the total precipitation during these months. We show that anomalous subtropical convection from the cloud bands is a source of Rossby waves that interact with the basic flow, resulting in downwind enhancement or damping of the extratropical disturbances. Therefore, these contemporary changes over South America are likely to have implications for changes Rossby Wave spectra in the Southern Hemisphere, especially downstream from the SACZ.
How to cite: Zilli, M. and Hart, N.: Large-scale circulation changes over South America are impacting synoptic-scale tropical-extratropical interactions and altering rainfall seasonality, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10393, https://doi.org/10.5194/egusphere-egu21-10393, 2021.
The Tibetan Plateau (TP) is the “water tower” of Asia and is the origin of most major rivers that provide water resources supporting countries in Asia. Changes in precipitation over the plateau play an important role in the water management in those areas, but the spatiotemporal variations of the precipitation over the TP are not well understood mainly because of the sparsely distributed in-situ observation sites. This study takes advantage of the newly available high-resolution ERA5 reanalysis and the Global Precipitation Measurement satellite product IMERG together with in-situ observations to characterize the seasonality of precipitation over the TP using a self-organizing map algorithm fed with precipitation data from 2000 to 2019. Specifically, this study aims to (1) identify regions with distinct seasonality in precipitation, (2) determine the interannual variability in the classification and regional precipitation, and (3) explore the roles played by large-scale atmospheric circulations on the seasonality of regional precipitation. The classification reveals three major precipitation regimes in the TP centered at the western, southwestern, and eastern plateau. On a year-to-year basis, the western region is relatively robust, while the southwestern and eastern regions tend to shift mainly between the central and northern TP. A composite analysis shows that the western region experiences larger amounts of precipitation in winter and early spring when the westerly jet is anomalously strong to the north of the TP. Precipitation variations in the southwestern region are associated with intensity changes in the South Asian High and Indian summer monsoon. The precipitation in the eastern region is correlated with the Indian summer monsoon and anticyclonic circulation over the western North Pacific. Our findings provide a better understanding of the regional and interannual variations of precipitation regimes over the TP, and could help to interpret future changes in precipitation regimes due to climate change.
How to cite: Lai, H.-W., Chen, H. W., Kukulies, J., Ou, T., and Chen, D.: Regionalization of seasonal precipitation over the Tibetan Plateau, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13259, https://doi.org/10.5194/egusphere-egu21-13259, 2021.
The sensitivity of wind to the Earth’s energy budget and the changes it causes in the climate system has a significant impact on the wind energy sector. The scope of this work is to examine the association of atmospheric circulation with the wind speed distribution characteristics on different timescales over Greece. Emphasis is given to the effect of specific regimes on the wind speed distributions at different locations. The work is based on using synoptic climatology as a tool for providing information regarding wind variability. This approach allows a more detailed description of the effect of changes in large-scale atmospheric circulation on wind energy potential. The atmospheric classification methodology, upon the selection of relevant atmospheric variables and domains, includes a Principal Components Analysis for dimension reduction purposes and subsequently, the classification is performed using an artificial neural network and in particular self-organizing maps. In the resulting feature map, the neighboring nodes are inter-connected and each one is associated with the composites of the selected large-scale variables. Upon the assignment and the characterization of each day in one of the resulting patterns, a daily catalog is constructed and frequency analysis is performed. In the context of estimating wind energy potential variability for each atmospheric pattern, the fit of multiple probability functions to the surface wind speed frequency distributions is performed. The most suitable function is selected based on a set of difference and correlation statistical measures, along with the use of goodness-of-fit statistical tests. The study employs the ERA5 reanalysis dataset with a 0.25° spatial resolution from 1979/01/01 up to 2019/12/31 and the wind field data are extracted at the 10m and the 100m levels. The approach could be valuable to the wind energy industry and can provide the required scientific understanding for the optimal siting of Wind Energy Conversion Systems considering the atmospheric circulation and the electricity interconnection infrastructure in the region. Considering the emerging issue of energy safety, accurate wind energy production estimates can contribute towards the establishment of wind as the primary energy source and in meeting the increasing energy demand.
How to cite: Philippopoulos, K. and Tzanis, C. G.: The impact of atmospheric circulation on wind energy resource using self-organizing maps, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3339, https://doi.org/10.5194/egusphere-egu21-3339, 2021.
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