Synoptic-scale Circulation Patterns Research Articles

Drivers controlling black carbon temporal variability in the lower troposphere of the European Arctic

Abstract. Black carbon (BC) is a short-lived climate forcer affecting the Arctic climate through multiple mechanisms, which vary substantially from winter to summer. Several models still fail in reproducing BC seasonal variability, limiting the ability to fully describe BC climate implications. This study aims at gaining insights into the mechanisms controlling BC transport from lower latitudes to the Arctic lower troposphere. Here we investigate the drivers controlling black carbon daily and seasonal variability in the Arctic using generalized additive models (GAMs). We analysed equivalent black carbon (eBC) concentrations measured at the Gruvebadet Atmospheric Laboratory (GAL – Svalbard archipelago) from March 2018 to December 2021. The eBC showed a marked seasonality with higher values in winter and early spring. The eBC concentration averaged 22 ± 20 ng m−3 in the cold season (November–April) and 11 ± 11 ng m−3 in the warm season (May–October). The seasonal and interannual variability was mainly modulated by the efficiency of wet scavenging removal during transport towards higher latitudes. Conversely, the short-term variability was controlled by boundary layer dynamics as well as local-scale and synoptic-scale circulation patterns. During both the cold and warm seasons, the transport of air masses from Europe and northern Russia was an effective pathway for the transport of pollution to the European Arctic. Finally, in the warm season we observed a link between the intrusion of warm air from lower latitudes and the increase in eBC concentration. Changes in the synoptic-scale circulation system and precipitation rate in the Northern Hemisphere, linked to climate change, are expected to modify the BC burden in the Arctic.

Influence of convective processes on weather research and forecasting model precipitation biases over East Asia

AbstractDynamical downscaling with a 20 km horizontal resolution was undertaken over East Asia for the period May–August in 1991–2015 using the Weather Research and Forecasting (WRF) model with Grell-3D ensemble cumulus parameterization as a product of the Impact of Initialized Land Temperature and Snowpack on Sub-Seasonal to Seasonal Prediction (LS4P) program. Simulated climatological precipitation biases were investigated over land during June when heavy precipitation occurred. Simulations underestimated precipitation along the Meiyu/Baiu rainband, while overestimating it farther north. Dry and wet biases expanded to south and north of the Yangtze River in China, respectively, marking years with poor precipitation simulations. Model biases in synoptic-scale circulation patterns indicate a weakened clockwise circulation over the western North Pacific in the model due to active convection there, and suppressed northward moisture transport to the Meiyu/Baiu rainband. Moisture convergence was slightly enhanced over central China due to an apparent anticyclonic circulation bias over northern China. In years with large biases, positive feedback between reduced moisture inflow and inactive convection occurred over southern China, while moisture transport to central China intensified on regional scales, with amplification of dry and wet biases over China. The Kain–Fritch scheme was used to test the influence of cumulus parameterization, improving the dry bias over southern China due to the modification of synoptic-scale circulation patterns in the lower troposphere. However, precipitation was further overestimated over central China, with the accuracy of precipitation distribution deteriorating.

Cloud-Resolving-Model Simulations of Nocturnal Precipitation over the Himalayan Slopes and Foothills

Abstract A numerical experiment with a 2-km resolution was conducted using the Weather Research and Forecasting (WRF) Model to investigate physical processes driving nocturnal precipitation over the Himalayas during the mature monsoon seasons between 2003 and 2010. The WRF Model simulations of increases in precipitation twice a day, one in the afternoon and another around midnight, over the Himalayan slopes, and of the single nocturnal peak over the Himalayan foothills were reasonably accurate. To understand the synoptic-scale moisture transport and its local-scale convergence generating the nocturnal precipitation, composite analyses were conducted using the reanalysis dataset and model outputs. In the synoptic scale, moisture transport associated with the westward propagation of low pressure systems was found when nocturnal precipitation dominated over the Himalayan slopes. In contrast, moisture was directly provided from the synoptic-scale monsoon westerlies for nocturnal precipitation over the foothills. The model outputs suggested that precipitation occurred on the mountain ridges in the Himalayas during the afternoon and expanded horizontally toward lower-elevation areas through the night. During the nighttime, the downslope wind was caused by radiative cooling at the surface and was intensified by evaporative cooling by hydrometeors in the near-surface layer. As a result, convergence between the downslope wind and the synoptic-scale flow promoted nocturnal precipitation over the Himalayas and to the south, as well as the moisture convergence by orography and/or synoptic-scale circulation patterns. The nocturnal precipitation over the Himalayas was not simulated well when we used the coarse topographic resolution and the smaller number of vertical layers.

Linking large-scale circulation patterns to low-cloud properties

Abstract. The North Pacific High (NPH) is a fundamental meteorological feature present during the boreal warm season. Marine boundary layer (MBL) clouds, which are persistent in this oceanic region, are influenced directly by the NPH. In this study, we combine 11 years of reanalysis and an unsupervised machine learning technique to examine the gamut of 850 hPa synoptic-scale circulation patterns. This approach reveals two distinguishable regimes – a dominant NPH setup and a land-falling cyclone – and in between a spectrum of large-scale patterns. We then use satellite retrievals to elucidate for the first time the explicit dependence of MBL cloud properties (namely cloud droplet number concentration, liquid water path, and shortwave cloud radiative effect – CRESW) on 850 hPa circulation patterns over the northeast Pacific Ocean. We find that CRESW spans from −146.8 to −115.5 W m−2, indicating that the range of observed MBL cloud properties must be accounted for in global and regional climate models. Our results demonstrate the value of combining reanalysis and satellite retrievals to help clarify the relationship between synoptic-scale dynamics and cloud physics.

Reconstructing summer upper-level flow in the northern Rocky Mountains using an alpine larch tree-ring chronology

Mid-latitude mesoscale weather during the climatological summer is strongly influenced by fluctuations in synoptic-scale circulation patterns. Previous research has linked Arctic amplification to alterations in summer synoptic climatology, leading to more extreme weather events in the mid-latitudes. In this study, seasonal (JJA) upper-level (500 hPa) atmospheric flow is reconstructed in the mid-latitudes using an alpine larch Larix lyallii Parl. tree-ring chronology sampled from western Montana. Significant relationships were found between alpine larch radial growth and upper-level flow patterns derived from the North American Regional Reanalysis dataset (1979-2015). Meridional and zonal flows that manifest in ridging are associated with enhanced radial growth of alpine larch (i.e. meridional flow west [r = 0.504, p = 0.001] and zonal flow north [r = 0.642, p < 0.001] of the study site). Meridional and zonal flows associated with troughing result in decreased radial growth (i.e. meridional flow east [r = -0.497, p = 0.001] and zonal flow south [r = -0.584, p < 0.001] of the study site). Using the leave-one-out method, a linear regression model was calibrated and verified between a principal component analysis score derived from measurements of upper-level flow in western North America and alpine larch tree growth. The 444 yr climate reconstruction of summer 500 hPa flow suggests that ridging is becoming more intense over the western United States and Canada since the 1980s.

Overview of modern atmospheric patterns controlling rainfall and floods into the Dead Sea: Implications for the lake's sedimentology and paleohydrology

The Dead Sea sedimentary fill is the basis for interpreting limnological conditions and regional paleohydrology. Such interpretations require an understanding of present-day hydroclimatology to reveal the relative impact of different atmospheric circulation patterns on water and sediment delivery to the Dead Sea. Here we address the most important meteorological conditions governing regional and local rainstorm occurrences, with different discharge characteristics. These meteorological controls over the Dead Sea watershed offer insights into past hydrometeorological processes that could have governed the Dead Sea water budget, seasonal and annual flows, floods, and the resultant sedimentology. Rainfall is typically associated with synoptic-scale circulation patterns forced by an upper-level trough that include Mediterranean cyclones (MCs), active Red Sea troughs (ARSTs), and active subtropical jets (STJs), although other rainstorms and sub-synoptic processes also affect the region. We point to their relative importance in inflow volume, peak discharges, and delivery of sediments from the various environments of the basin. MCs control the annual water amount discharging into the Dead Sea. A change in their frequency, intensity, or latitude can substantially alter the lake water balance. A change in frequency or intensity of ARSTs and STJs affects extreme flood and sediment discharge. Floods reach the lake through (a) the Mediterranean-climate-controlled Lower Jordan River, (b) desert-climate-controlled Nahal HaArava, and (c) the arid wadies draining directly into the Dead Sea, some with wetter headwaters. Floods in the wetter parts of the watershed are mainly controlled by MCs, and characterized by larger frequency, volume, and duration, but lower peak discharges and possibly sediment delivery, than floods in the desert parts, which can be produced by the three synoptic types. ARSTs contribute to heavy rainfall, typically of a spotty nature, in the desert parts of the watershed. STJs are currently rare, but their rainfall accumulation may be greater than the annual mean over a broad area in the southern dry Dead Sea watershed. This article presents a review of recent studies, which is extended with new analyses of meteorological, rainfall and flood data, underlining the importance of the Lower Jordan River in supplying water volume to the Dead Sea, as compared to the high-discharge, low-volume floods of the arid part of the watershed. Our analyses will help interpret paleoenvironmental conditions in the Dead Sea sedimentary record, and cope with the region's changing climate.

A synoptic assessment of the summer extreme rainfall over the middle reaches of Yangtze River in CMIP5 models

The summer mean and extreme rainfall over the middle reaches of Yangtze River (MRYR) are underestimated in many models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Our earlier work has identified three synoptic-scale circulation patterns associated with extreme rainfall events over the MRYR during early summer. It is verified here that the presence of these patterns indeed increases the likelihood of the occurrence of extreme rainfall over the MRYR. This relationship between the synoptic-scale circulation pattern and extreme rainfall is reproduced by only a subset of CMIP5 models, where the underestimated frequency of the corresponding synoptic-scale circulation patterns partly explains the underestimated frequency of extreme rainfall thus the summer total over the MRYR. Our analysis also reveals that a few models could “accidentally” simulate a realistic rainfall total and probability distribution of daily rain rate over the MRYR region during summer by generating their own model-dependent synoptic-scale circulation patterns that are not typically seen in observations. These findings suggest that a projection of future changes in extreme rainfall over the MRYR will be better constrained dynamically if we use a subset of models that can reproduce the “rainfall-circulation” relationship, given the diverse response of different circulation patterns to radiative forcing changes in the atmosphere. The results presented here also demonstrate the importance of tracking biases of synoptic-scale circulations in understanding model deficiencies in precipitation simulation, in addition to investigating problems in model physics such as cumulus schemes and microphysics parameterization. Nevertheless, these results are based on the analyses of extreme rainfall in one region and one season, further research covering other regions/seasons is needed.

A classification algorithm for selective dynamical downscaling of precipitation extremes

Abstract. High-resolution climate data O(1 km) at the catchment scale can be of great value to both hydrological modellers and end users, in particular for the study of extreme precipitation. While dynamical downscaling with convection-permitting models is a valuable approach for producing quality high-resolution O(1 km) data, its added value can often not be realized due to the prohibitive computational expense. Here we present a novel and flexible classification algorithm for discriminating between days with an elevated potential for extreme precipitation over a catchment and days without, so that dynamical downscaling to convection-permitting resolution can be selectively performed on high-risk days only, drastically reducing total computational expense compared to continuous simulations; the classification method can be applied to climate model data or reanalyses. Using observed precipitation and the corresponding synoptic-scale circulation patterns from reanalysis, characteristic extremal circulation patterns are identified for the catchment via a clustering algorithm. These extremal patterns serve as references against which days can be classified as potentially extreme, subject to additional tests of relevant meteorological predictors in the vicinity of the catchment. Applying the classification algorithm to reanalysis, the set of potential extreme days (PEDs) contains well below 10 % of all days, though it includes essentially all extreme days; applying the algorithm to reanalysis-driven regional climate simulations over Europe (12 km resolution) shows similar performance, and the subsequently dynamically downscaled simulations (2 km resolution) well reproduce the observed precipitation statistics of the PEDs from the training period. Additional tests on continuous 12 km resolution historical and future (RCP8.5) climate simulations, downscaled in 2 km resolution time slices, show the algorithm again reducing the number of days to simulate by over 90 % and performing consistently across climate regimes. The downscaling framework we propose represents a computationally inexpensive means of producing high-resolution climate data, focused on extreme precipitation, at the catchment scale, while still retaining the advantages of convection-permitting dynamical downscaling.

Synoptic-Scale Control over Modern Rainfall and Flood Patterns in the Levant Drylands with Implications for Past Climates

Abstract Rainfall in the Levant drylands is scarce but can potentially generate high-magnitude flash floods. Rainstorms are caused by distinct synoptic-scale circulation patterns: Mediterranean cyclone (MC), active Red Sea trough (ARST), and subtropical jet stream (STJ) disturbances, also termed tropical plumes (TPs). The unique spatiotemporal characteristics of rainstorms and floods for each circulation pattern were identified. Meteorological reanalyses, quantitative precipitation estimates from weather radars, hydrological data, and indicators of geomorphic changes from remote sensing imagery were used to characterize the chain of hydrometeorological processes leading to distinct flood patterns in the region. Significant differences in the hydrometeorology of these three flood-producing synoptic systems were identified: MC storms draw moisture from the Mediterranean and generate moderate rainfall in the northern part of the region. ARST and TP storms transfer large amounts of moisture from the south, which is converted to rainfall in the hyperarid southernmost parts of the Levant. ARST rainfall is local and intense, whereas TP rainfall is widespread and prolonged due to high precipitation efficiency and large-scale forcing. Thus, TP rainfall generates high-magnitude floods in the largest catchments; integration of numerous basins leads to sediment feeding from the south into the Dead Sea, exhibited in large sediment plumes. Anecdotal observations of the channel with the largest catchment in the region (Nahal HaArava) indicate that TP floods account for noticeable geomorphic changes in the channel. It provides insights into past intervals of increased flash flood frequency characterized by episodes of marked hydrogeomorphic work; such an increase is especially expected during intervals of southerly situated and southwesterly oriented STJs.

A 1286‐year hydro‐climate reconstruction for the Balkan Peninsula

We present a June–July drought reconstruction based on the standardized precipitation index (SPI) for the Balkan Peninsula over the period 730–2015 CE. The reconstruction is developed using a composite Pinus heldreichii tree‐ring width chronology, from a high‐elevation network of eight sites in the Pindus Mountains in northwest Greece, composed of living trees and relict wood. The dataset includes the ring width series of Europe's currently oldest known living tree, dendrochronologically dated to be more than 1075 years old. The spatial coverage of the reconstruction is improved by using an averaged gridded SPI data target derived from a response field that is located north of the study region. Justification for this approach includes the remoteness of instrumental data, the spatial variability of precipitation and synoptic scale circulation patterns. Over the past 1286 years, there have been 51 dry and 43 pluvial events. The driest year during the 1286‐year‐long period was 1660 and the wettest year was 1482. Comparison with shorter reconstructions and documentary evidence validates the new reconstruction, and provides additional insight into socioeconomic impacts and spatial patterns of extreme events. Fifty‐nine of 72 previously undescribed extremes occurred prior to the 17th century. The new reconstruction reveals long‐term changes in the number of extremes, including substantially fewer drought and pluvial events in the 20th century. Additional tests on the long‐term effects of age structure, replication and covariance changes support the heteroscedastic nature of the reconstructed hydro‐climatic extremes.

Evaluation of Tree Growth Relevant Atmospheric Circulation Patterns for Geopotential Height Field Reconstructions for Asia

Atmospheric circulations influence local and regional weather conditions and, thus, tree growth. To identify summer weather types relevant for tree growth, and their associated synoptic-scale circulation patterns, an atmospheric circulation tree ring index (ACTI) dataset, derived from 414 tree-ring sites across Asia spanning the period 1871–2010, was created. Modes of common variability in the ACTI dataset were compared with leading modes of observed summertime 500-hPa geopotential height. The first four ACTI modes (explaining 88% of the total variance) were associated with pressure centers over Eurasia, the tropics, and the Pacific Ocean. The high spatiotemporal resemblance between the leading circulation modes, derived from both tree rings and 500-hPa geopotential height fields, indicates a strong potential for reconstructing large-scale circulation patterns from tree rings in Asia. This would allow investigations of natural atmospheric circulation variability prior to anthropogenic climate change and provide a means to validate model simulations of climate predictions.

Hydro-climatic variability and extremes over the Athabasca River basin: Historical trends and projected future occurrence

Since humans and ecosystems require adequate, reliable water supplies, hydro-climatic variability and extremes pose serious threats to society and the environment. Western Canada, including the Athabasca River Basin (ARB), is prone to considerable hydro-climatic variability including periodic extreme droughts and excessive moisture conditions. The main causes of these extremes are persistent, mid-tropospheric circulation patterns that disrupt expected precipitation and temperature. However, no investigation has specifically focused on the occurrence and causes of both past and future hydro-climatologic variability within the ARB. Assessment of the Standardized Precipitation Evapotranspiration Index (SPEI) reveals substantial inter-annual and decadal-scale variability over the entire ARB and its individual reaches, with no discernible trends during the last ~100 years. Evaluation of the 500-hPa circulation patterns associated with identified hydro-climatic extremes shows that major droughts are related to higher frequencies of distinctive ridging patterns over the ARB and fewer incidences of troughing. Excessive moisture conditions tend to have opposite patterns. Projections from several regional climate models reveal an average change toward more drought-like summer and slightly wetter annual conditions over the ARB, but there is a substantial range for individual models ranging from a considerable increase in drought with a higher degree of inter-annual variability, to relatively little change from current conditions. Simulated changes to key atmospheric circulations are consistent with these SPEI projections and indicate that those patterns associated with hydro-climatic extremes will continue in the future and in some cases, increase in frequency. Results from this analysis have quantified historical hydro-climatic variability in the ARB and have provided insight into potential future conditions as driven by changes to surface climate and synoptic-scale atmospheric circulation patterns.

Synoptic-scale circulation patterns during summer derived from tree rings in mid-latitude Asia

Understanding past and recent climate and atmospheric circulation variability is vital for regions that are affected by climate extremes. In mid-latitude Asia, however, the synoptic climatology is complex and not yet fully understood. The aim of this study was to investigate dominant synoptic-scale circulation patterns during the summer season using a multi-species tree-ring width (TRW) network comprising 78 sites from mid-latitude Asia. For each TRW chronology, we calculated an atmospheric circulation tree-ring index (ACTI), based on 1000 hPa geopotential height data, to directly link tree growth to 13 summertime weather types and their associated local climate conditions for the period 1871–1993. Using the ACTI, three groups of similarly responding tree-ring sites can be associated with distinct large-scale atmospheric circulation patterns: 1. growth of drought sensitive trees is positively affected by a cyclone over northern Russia; 2. temperature sensitive trees show positive associations to a cyclone over northwestern Russia and an anticyclone over Mongolia; 3. trees at two high elevation sites show positive relations to a zonal cyclone extending from mid-latitude Eurasia to the West Pacific. The identified synoptic-scale circulation patterns showed spatiotemporal variability in their intensity and position, causing temporally varying climate conditions in mid-latitude Asia. Our results highlight that for regions with less pronounced atmospheric action centers during summer such as the occurrence of large-scale cyclones and anticyclones, synoptic-scale circulation patterns can be extracted and linked to the Northern Hemisphere circulation system. Thus, we provide a new and solid envelope for climate studies covering the past to the future.

The development of a non-linear autoregressive model with exogenous input (NARX) to model climate-water clarity relationships: reconstructing a historical water clarity index for the coastal waters of the southeastern USA

The coastal waters of the southeastern USA contain important protected habitats and natural resources that are vulnerable to climate variability and singular weather events. Water clarity, strongly affected by atmospheric events, is linked to substantial environmental impacts throughout the region. To assess this relationship over the long-term, this study uses an artificial neural network-based time series modeling technique known as non-linear autoregressive models with exogenous input (NARX models) to explore the relationship between climate and a water clarity index (KDI) in this area and to reconstruct this index over a 66-year period. Results show that synoptic-scale circulation patterns, weather types, and precipitation all play roles in impacting water clarity to varying degrees in each region of the larger domain. In particular, turbid water is associated with transitional weather and cyclonic circulation in much of the study region. Overall, NARX model performance also varies—regionally, seasonally and interannually—with wintertime estimates of KDI along the West Florida Shelf correlating to the actual KDI at r > 0.70. Periods of extreme (high) KDI in this area coincide with notable El Nino events. An upward trend in extreme KDI events from 1948 to 2013 is also present across much of the Florida Gulf coast.

Atmospheric circulation patterns, cloud-to-ground lightning, and locally intense convective rainfall associated with debris flow initiation in the Dolomite Alps of northeastern Italy

Abstract. The Dolomite Alps of northeastern Italy experience debris flows with great frequency during the summer months. An ample supply of unconsolidated material on steep slopes and a summer season climate regime characterized by recurrent thunderstorms combine to produce an abundance of these destructive hydro-geologic events. In the past, debris flow events have been studied primarily in the context of their geologic and geomorphic characteristics. The atmospheric contribution to these mass-wasting events has been limited to recording rainfall and developing intensity thresholds for debris mobilization. This study aims to expand the examination of atmospheric processes that preceded both locally intense convective rainfall (LICR) and debris flows in the Dolomite region. 500 hPa pressure level plots of geopotential heights were constructed for a period of 3 days prior to debris flow events to gain insight into the synoptic-scale processes which provide an environment conducive to LICR in the Dolomites. Cloud-to-ground (CG) lightning flash data recorded at the meso-scale were incorporated to assess the convective environment proximal to debris flow source regions. Twelve events were analyzed and from this analysis three common synoptic-scale circulation patterns were identified. Evaluation of CG flashes at smaller spatial and temporal scales illustrated that convective processes vary in their production of CF flashes (total number) and the spatial distribution of flashes can also be quite different between events over longer periods. During the 60 min interval immediately preceding debris flow a majority of cases exhibited spatial and temporal colocation of LICR and CG flashes. Also a number of CG flash parameters were found to be significantly correlated to rainfall intensity prior to debris flow initiation.

Satellite Derived Aerosol Optical Depth Climatology over Tropical Coastal Station Machilipatnam, India

Climatological aerosol optical depths (AOD) over Tropical coastal city Machilipatnam, India have been examined to bring out the temporal heterogeneity in columnar aerosol characteristics. AOD values at 388 nm derived from the Ozone Monitoring Instrument (OMI) sensor EOS-AURA satellite, for the period of 2005–2013 have been analyzed for the purpose. AOD trends exhibited seasonal annual mean variations. Frequency distributions of the AOD values are examined to infer the monthly mean values. Monthly and seasonal variations of AOD are investigated in the light of regional synoptic meteorology. AODs>0.6 showed maximum occurrence in monsoon months. The mean AOD values increased towards summer reaching ~0.69 ± 0.34 and attained peak in monsoon season with a value of ~0.74 ± 0.33 and decreased during post-monsoon reaching as low as ~0.73 ± 0.3. Positive slope ~0.016 observed for inter annual distribution trend line. Factors like synoptic scale circulation patterns which are causing modulations of AOD apart from local sources were discussed.

Satellite Derived Aerosol Optical Depth Climatology over Tropical Coastal Station Machilipatnam, India

Climatological aerosol optical depths (AOD) over Tropical coastal city Machilipatnam, India have been examined to bring out the temporal heterogeneity in columnar aerosol characteristics. AOD values at 388 nm derived from the Ozone Monitoring Instrument (OMI) sensor EOS-AURA satellite, for the period of 2005–2013 have been analyzed for the purpose. AOD trends exhibited seasonal annual mean variations. Frequency distributions of the AOD values are examined to infer the monthly mean values. Monthly and seasonal variations of AOD are investigated in the light of regional synoptic meteorology. AODs>0.6 showed maximum occurrence in monsoon months. The mean AOD values increased towards summer reaching ~0.69 ± 0.34 and attained peak in monsoon season with a value of ~0.74 ± 0.33 and decreased during post-monsoon reaching as low as ~0.73 ± 0.3. Positive slope ~0.016 observed for inter annual distribution trend line. Factors like synoptic scale circulation patterns which are causing modulations of AOD apart from local sources were discussed.

Neural network forecast of daily pollution concentration using optimal meteorological data at synoptic and local scales

We present a simple neural network and data pre–selection framework, discriminating the most essential input data for accurately forecasting the concentrations of PM10, based on observations for the years between 2002 and 2006 in the metropolitan region of Lisbon, Portugal. Starting from a broad panoply of different data sets collected at several air quality and meteorological stations, a forward stepwise regression procedure is applied enabling to automatically identify the most important variables for predicting the pollutant and also to rank them in order of importance. The importance of this variable ranking is discussed, showing that it is very sensitive to the urban location where measurements are obtained. Additionally, the importance of Circulation Weather Types is highlighted, characterizing synoptic scale circulation patterns and the concentration of pollutants. We then quantify the performance of linear and non–linear neural network models when applied to PM10 concentrations. In the light of contradictory results of previous studies, our results show no clear superiority for the case studied of non–linear models over linear models. While all models show similar predictive performances, we find important differences in false alarm rates and demonstrate the importance of removing weekly cycles from input variables.

Study of carbonaceous species, morphology and sources of fine (PM2.5) and coarse (PM10) particles along with their climatic nature in India

The determination of particulate matter (PM2.5 and PM10) is very important due to its impact on climate, visibility reduction and natural environment. In order to identify their nature and relationship with the major synoptic-scale circulation patterns, particles were collected from Pune atmosphere and were analyzed in terms of morphology, carbonaceous species (organic and elemental carbon) and elemental concentration. Average mass concentrations of PM2.5 and PM10 were 104.57±25.70μgm−3 and 169.91±60.75μgm−3, respectively for the entire study period. This indicates that observed values of PM are substantially higher than NAAQS and WHO standards, respectively. The ratio between PM2.5 and PM10 was calculated and varied from 0.51 to 0.78 indicating abundance of fine particles over Pune during the study period. Carbonaceous analysis results showed that concentrations of OC and EC were 31.25 and 2.73μgm−3 for PM2.5 while 33.14 and 2.40μgm−3 for PM10, respectively. The calculated OC/EC ratios were 15.83 and 17.24 for PM2.5 and PM10, respectively indicating abundance of organic carbon which suggests the excess of secondary organic aerosols. The morphological traits such as circularity (<1) and aspect ratio (>1) were determined which indicate that the particles are not perfectly spherical and not elongated in any direction in both size ranges. Effective carbon ratio (ECR) an approach for climate was found to have an average value of 2.42 and 1.74 for PM2.5 and PM10. This clearly indicates that abundance of SOC and lower values of POC and EC could lead to the reduction in atmospheric warming effect due to combustion PM and increases scattering properties of incoming radiations. The monthly air mass backward trajectory cluster analysis was performed which supports the transport of aerosols from the long range transportation as well as the dominance of local sources over SW Indian region. The contribution of local sources was further determined which indicates that motor vehicle is the dominant emitter of carbonaceous aerosols in Pune.

Automated classification of the atmospheric circulation patterns that drive regional wave climates

Abstract. Wave climates are fundamental drivers of coastal vulnerability; changing trends in wave heights, periods and directions can severely impact a coastline. In a diverse storm environment, the changes in these parameters are difficult to detect and quantify. Since wave climates are linked to atmospheric circulation patterns, an automated and objective classification scheme was developed to explore links between synoptic-scale circulation patterns and wave climate variables, specifically wave heights. The algorithm uses a set of objective functions based on wave heights to guide the classification and find atmospheric classes with strong links to wave behaviour. Spatially distributed fuzzy numbers define the classes and are used to detect locally high- and low-pressure anomalies. Classes are derived through a process of simulated annealing. The optimized classification focuses on extreme wave events. The east coast of South Africa was used as a case study. The results show that three dominant patterns drive extreme wave events. The circulation patterns exhibit some seasonality with one pattern present throughout the year. Some 50–80% of the extreme wave events are explained by these three patterns. It is evident that strong low-pressure anomalies east of the country drive a wind towards the KwaZulu-Natal coastline which results in extreme wave conditions. We conclude that the methodology can be used to link circulation patterns to wave heights within a diverse storm environment. The circulation patterns agree with qualitative observations of wave climate drivers. There are applications to the assessment of coastal vulnerability and the management of coastlines worldwide.