Large-scale Environmental Conditions Research Articles

Absence of Tropical Cyclone Genesis Over the Western North Pacific in July 2020 and Its Prediction by CFSv2

There were no TCs generated in July 2020 over the western North Pacific (WNP), which was the first time this had happened during since 1980. This study attempts to understand the cause of there having been no TCs generated in July 2020, and evaluates the prediction skill for the large-scale environmental conditions associated with the TC genesis number (TCGN). Results show that the main causes were the abnormal warming of sea surface temperature (SST) in the North Indian Ocean (NIO) and North Atlantic in July and the abnormal decrease in SST from April and May in the Niño4 region. The NIO SST can affect the large-scale environmental conditions via the SST–precipitation–wind feedback mechanism. Through the interaction between the tropical North Atlantic and the NIO, the abnormally warm North Atlantic SST further strengthened the impact of the NIO SST on the environmental conditions. The monthly difference (MD) of the Niño4 index from April to May is significantly correlated with the TCGN in July. Not only can the Niño4 MD in May affect the environmental conditions by affecting the WNP anticyclone, but it can also affect the NIO SST and precipitation anomalies through a shift in the position of the Walker circulation. Besides, the activity of the MJO also had a certain impact on the absence of TC genesis in July 2020. Although CFSv2 can successfully predict the local feedback affecting the July TCGN, it fails to forecast the large-scale environmental conditions associated with the absence of TC genesis over the WNP in July 2020.

Non-destructive aboveground biomass estimation of Leymus chinensis individual across large scale

Monitoring how plant biomass changes with environmental conditions is critical for evaluating ecosystem carbon storage and understanding the underlying mechanisms of carbon dynamics. Usually destructive methods require a lot of time and cost. And the non-destructive methods to repeatedly estimate the biomass of herbaceous plants across large scale environmental conditions are still limited. Leymus chinensis, as an important constructive species, constitutes a unique community type in the eastern Eurasian steppe across the semi-humid, semi-arid and arid areas in the middle temperate and warm temperate zones. Therefore, it is necessary to analyze the driving factors and establish a unified estimation equation of the aboveground biomass (AGB) of L. chinensis across large scale. In this study, for the first time, we combined climatic factors and plant characteristics to analyze the individual AGB of L. chinensis in northern China, and established a non-destructive prediction model that can accurately quantify the AGB of L. chinensis across large scale in China. 33 sites across different climate conditions with L. chinensis as the constructive species in China were sampled to measure plant traits of L. chinensis individual, including leaf thickness (LT), stem diameter (SD), stem length (SL), plant height (PH), etc. We found that plant traits (PH,SD) were the main factors driving the AGB of L. chinensis individuals, and climate factors mainly affected AGB of L. chinensis individuals indirectly by affecting plant traits. Then, we established the AGB estimation equation of L. chinensis individuals across large scale for the first time. The equation was: AGB = −0.638 + 0.405*SD + 0.017*PH, which had a high predictive ability. The result is not only helpful to quickly and conveniently measure the AGB of L. chinensis individuals in non-destructive experiments, but also important to evaluate the productivity and carbon storage of L. chinensis community across large scale. At the same time, it also laid the foundation for the subsequent non-destructive estimation of the aboveground biomass of individual plants.

Identifying meteorological influences on marine low-cloud mesoscale morphology using satellite classifications

Abstract. Marine low-cloud mesoscale morphology in the southeastern Pacific Ocean is analyzed using a large dataset of classifications spanning 3 years generated by machine learning methods. Meteorological variables and cloud properties are composited by the mesoscale cloud type of the classification, showing distinct meteorological regimes of marine low-cloud organization from the tropics to the midlatitudes. The presentation of mesoscale cellular convection, with respect to geographic distribution, boundary layer structure, and large-scale environmental conditions, agrees with prior knowledge. Two tropical and subtropical cumuliform boundary layer regimes, suppressed cumulus and clustered cumulus, are studied in detail. The patterns in precipitation, circulation, column water vapor, and cloudiness are consistent with the representation of marine shallow mesoscale convective self-aggregation by large eddy simulations of the boundary layer. Although they occur under similar large-scale conditions, the suppressed and clustered low-cloud types are found to be well separated by variables associated with low-level mesoscale circulation, with surface wind divergence being the clearest discriminator between them, regardless of whether reanalysis or satellite observations are used. Clustered regimes are associated with surface convergence, while suppressed regimes are associated with surface divergence.

Assessment of coastal anthropo-ecological system dynamics in response to a tsunami catastrophe of an unprecedented magnitude encountered in Japan

On 11 March 2011, a catastrophic earthquake and subsequent tsunami hit the Pacific coast of northern Japan, devastating many of the towns, villages and coastal ecosystems located along the shoreline. To assess the impacts of the disaster, we investigated temporal dynamics of fish and epibenthic megafaunal community structure in relation to changes in a range of physical, biological and anthropogenic variables between 2007 and 2018 in Onagawa Bay. Commercially important fish such as greenlings, Japanese anchovy, flatfishes, rockfishes were consistently abundant in both larval and adult fish assemblages. While abundance, species richness, and Shannon index H′ for adult fish and epibenthic megafaunal assemblages increased significantly soon after the disaster to peak values towards the end of the study period, the same metrics did not change accordingly for larval fish assemblages. Temporal dynamics of larval fish community clearly demonstrated significant seasonal variation along with changes in large-scale environmental conditions such as temperature and nutrients. However, anthropogenic components such as decline in human population, reduction in fishing pressure and the recovery of aquaculture operations significantly explained the observed post-disaster change in adult fish and epibenthic megafaunal communities. The pelagic and benthic components of Onagawa Bay appeared to have responded to the 2011 disaster very differently, and this study suggests the post-disaster recovery and dynamics of the coastal ecosystems may be regulated by how human societies respond to the impacts of a tsunami catastrophe through their influences on benthic habitat of ecosystems.

Assessing the Influence of Large-Scale Environmental Conditions on the Rainfall Structure of Atlantic Tropical Cyclones: An Observational Study

AbstractUnderstanding the mechanisms related to the variations in the rainfall structure of tropical cyclones (TCs) is crucial in improving forecasting systems of TC rainfall and its impact. Using satellite precipitation and reanalysis data, we examined the influence of along-track large-scale environmental conditions on inner-core rainfall strength (RS) and total rainfall area (RA) for Atlantic TCs during the TC season (July–November) from 1998 to 2019. Factor analysis revealed three major factors associated with variations in RS and RA: large-scale low and high pressure systems [factor 1 (F1)]; environmental flows, sea surface temperature, and humidity [factor 2 (F2)]; and maximum wind speed of TCs [factor 3 (F3)]. Results from our study indicate that RS increases with an increase in the inherent primary circulation of TCs (i.e., F3) but is less affected by large-scale environmental conditions (i.e., F1 and F2), whereas RA is primarily influenced by large-scale low and high pressure systems (i.e., F1) over the entire North Atlantic and partially influenced by environmental flows, sea surface temperature, humidity, and maximum wind speed (i.e., F2 and F3). A multivariable regression model based on the three factors accounted for the variations of RS and RA across the entire basin. In addition, regional distributions of mean RS and RA from the model significantly resembled those from observations. Therefore, our study suggests that large-scale environmental conditions over the North Atlantic Ocean are important predictors for TC rainfall forecasts, particularly with regard to RA.

Evaluation of Simulation Capability for Multiple Tropical Cyclone Events in the Western North Pacific of the UH_HCM Model

The intraseasonal variability of multiple tropical cyclone (MTC) events in the western North Pacific (WNP) during 1979–2015 is analyzed using the best-track dataset archived at the Joint Typhoon Warning Center. MTC events are divided into three phases according to the time intervals of the tropical cyclone (TC) genesis, that is, active, normal, and inactive phases. Composite analysis results indicate that MTC events tend to occur in the active phase when the monsoon trough is stronger and located farther north than at other times. Initialized by the data from a 10-year stable running result, a 12-year control experiment is carried out using the hybrid atmosphere–ocean coupled model developed at the University of Hawaii (UH_HCM model) to evaluate its simulation capability. Compared with the climate observations, the model shows good skill in simulating the large-scale environmental conditions in the WNP, especially the subtropical high and the monsoon trough. In addition, the model can well simulate the climate characteristics of TCs in the WNP, as well as the differences in each MTC phase. However, the simulated frequency of TCs is less and their locations are more northeast, compared with the observations. The vorticity and moisture in the model appear to be the two main factors affecting MTC activity based on analyses of the genesis potential index.

The pre-Columbian site of Roseau (Guadeloupe, F. W. I.): intra-site chronological variability of the subsistence strategies in a Late Ceramic archeological vertebrate assemblage

Evidence for chronological change in intra-site subsistence strategies is very rare in the Amerindian record of the Lesser Antilles. The study of the vertebrate assemblage from the archeological site of Roseau in the Guadeloupe Islands underlines the complexity and variability of Ceramic Age Amerindian subsistence behavior. This study establishes a more precise chronology of the previously identified strata of the site, and demonstrates that the Contact period was only represented by rare archeological artifacts dispersed in the stratigraphy. The results from this assemblage indicate that the earlier occupations of the site exhibit a more intensive exploitation of aquatic vertebrate resources compared to later occupations, which have a larger focus on terrestrial fauna, especially rodents and iguanas. This unusual pattern highlights how subsistence behaviors in the Lesser Antilles during the Late and Final Ceramic periods were highly variable. This new evidence of strong inter-site variability shows that the behaviors of Amerindians are not only dependent of large-scale environmental conditions but also influenced by more complex socio-cultural and local environmental parameters.

Tropical Cyclones Downscaled from Simulations of the Last Glacial Maximum

AbstractThe tracks, intensities, and other properties of tropical cyclones downscaled from three models’ simulations of the Last Glacial Maximum (LGM) are analyzed and compared to those of storms downscaled from simulations of the present climate. Globally, the mean maximum intensity of storms generated from each model is lower at LGM, as is the fraction of all storms that reach intensities of category 4 or higher on the Saffir–Simpson hurricane wind scale. The median day of the storm season shifts earlier by an average of one week in all three models in both hemispheres. Two of the three models’ LGM simulations feature a reduction in storm count and global power dissipation index compared to the current climate, but a third shows no significant difference between the two climates. Although each model is forced by the same global changes, differences in the way sea surface temperatures and other large-scale environmental conditions respond in the North Atlantic impart significant differences in the climatology at LGM between models. Our results from the cold LGM provide a novel opportunity to assess how tropical cyclones respond to climate changes.

Identifying meteorological influences on marine low cloud mesoscale morphology using deep learning classifications

Abstract. Marine low cloud mesoscale morphology in the southeastern Pacific Ocean is analyzed using a large dataset of machine-learning generated classifications spanning three years. Meteorological variables and cloud properties are composited by mesoscale cloud type, showing distinct meteorological regimes of marine low cloud organization from the tropics to the midlatitudes. The presentation of mesoscale cellular convection, with respect to geographic distribution, boundary layer structure, and large-scale environmental conditions, agrees with prior knowledge. Two tropical and subtropical cumuliform boundary layer regimes, suppressed cumulus and clustered cumulus, are studied in detail. The patterns in precipitation, circulation, column water vapor, and cloudiness are consistent with the representation of marine shallow mesoscale convective self-aggregation by large eddy simulations of the boundary layer. Although they occur under similar large-scale conditions, the suppressed and clustered low cloud types are found to be well-separated by variables associated with low-level mesoscale circulation, with surface wind divergence being the clearest discriminator between them, whether reanalysis or satellite observations are used. Clustered regimes are associated with surface convergence and suppressed regimes are associated with surface divergence.

Does the Pacific meridional mode dominantly affect tropical cyclogenesis in the western North Pacific?

The different impacts of Pacific meridional mode (PMM) and central Pacific (CP) El Nino on tropical cyclone (TC) genesis over the western North Pacific (WNP) in the period of 1965–2018 were investigated in this study. The results show that PMM is mainly related to the eastern subtropical Pacific warming and CP El Nino is mainly related to the central tropical Pacific warming. They have a similar impact on TC genesis over the WNP and more TCs form in the east of the WNP due to the high correlation between the central tropical Pacific warming and eastern subtropical Pacific warming. In the central tropical Pacific, due to the SST forcing of the atmosphere, SST warming leads to the remarkable atmospheric response. In the eastern subtropical Pacific, the variation of the atmosphere precedes SST to establish the SST warming, and the atmospheric response to this SST warming is limited. During the CP El Nino, the anomalous convention associated with the central tropical Pacific warming produces a poleward extension of anomalous westerlies over the WNP by the Matsuno-Gill-type Rossby wave response. Such anomalous westerlies strengthen the monsoon trough (MT) with an eastward shift. The enhanced MT accompanied by the changed large-scale environmental conditions and synoptic-scale perturbations are beneficial to TC genesis over the WNP. However, the PMM with the eastern subtropical Pacific warming has no significant impact on the tropical circulation over the WNP and only a limited effect on the subtropical high. As a result, it has no direct effect on the MT, and the PMM itself has no significant positive correlation with TC genesis over the WNP. However, the impact of the PMM with the central tropical Pacific warming on TC genesis over the WNP is consistent with that during the CP El Nino. These findings suggest the dominant role of the SST warming in the central tropical Pacific on TC genesis over WNP, and the simultaneous impact of PMM on TC genesis over WNP is mainly realized by it.

Summertime stationary waves integrate tropical and extratropical impacts on tropical cyclone activity

Tropical cyclones (TC) are one of the most severe storm systems on Earth and cause significant loss of life and property upon landfall in coastal areas. A better understanding of their variability mechanisms will help improve the TC seasonal prediction skill and mitigate the destructive impacts of the storms. Early studies focused primarily on tropical processes in regulating the variability of TC activity, while recent studies suggest also some long-range impacts of extratropical processes, such as lateral transport of dry air and potential vorticity by large-scale waves. Here we show that stationary waves in the Northern Hemisphere integrate tropical and extratropical impacts on TC activity in July through October. In particular, tropical upper-tropospheric troughs (TUTTs), as part of the summertime stationary waves, are associated with the variability of large-scale environmental conditions in the tropical North Atlantic and North Pacific and significantly correlated to the variability of TC activity in these basins. TUTTs are subject to the modulation of diabatic heating in various regions and are the preferred locations for extratropical Rossby wave breaking (RWB). A strong TUTT in a basin is associated with enhanced RWB and tropical-extratropical stirring in that basin, and the resultant changes in the tropical atmospheric conditions modulate TC activity. In addition, the anticorrelation of TUTTs between the North Atlantic and North Pacific makes the TC activity indices over the two basins compensate each other, rendering the global TC activity less variable than otherwise would be the case if TUTTs were independent.

El Niño phase-dependent high-frequency variability in Western Equatorial Pacific

The intensities of high-frequency (HF) variability with period less than 90 days at different phases of El Nino events were investigated through observational data analysis. A large asymmetry in the HF variability intensity between the developing phase and decaying phase (i.e., pre-peak stage versus post-peak stage) of eastern Pacific (EP) El Nino is revealed, while the amplitude and spatial pattern of the sea surface temperature anomaly during these two stages are almost same. The diagnosis shows that the asymmetry is significant not only on intraseasonal time scale (20–90 days) but also on synoptic time scale (less than 20 days). The anatomy analysis further unveils that the asymmetric synoptic variability between the two episodes arises from the asymmetric intensities of the equatorial Rossby and mixed Rossby gravity (MRG) waves. We suggest that the stronger vertical easterly wind shear in the pre-peak stage than that in the post-peak stage plays a vital role in causing the stronger synoptic equatorial Rossby and MRG waves in the pre-peak stage. Meanwhile, the drier atmosphere and more descending motion in the post-peak stage contribute to the weakened intraseasonal and synoptic variabilities in that stage. The aforementioned weakened easterly wind shear, drier atmosphere and more descending motion in the post-peak stage can be traced back to the occurrence of the anomalous anticyclone circulation over the western North Pacific since the decaying phase of El Nino. The essential role of large-scale environmental conditions in modulating the HF variability during the two episodes is further confirmed by modeling experiments.

Combining Crowdsourcing and Deep Learning to Explore the Mesoscale Organization of Shallow Convection

Abstract Humans excel at detecting interesting patterns in images, for example, those taken from satellites. This kind of anecdotal evidence can lead to the discovery of new phenomena. However, it is often difficult to gather enough data of subjective features for significant analysis. This paper presents an example of how two tools that have recently become accessible to a wide range of researchers, crowdsourcing and deep learning, can be combined to explore satellite imagery at scale. In particular, the focus is on the organization of shallow cumulus convection in the trade wind regions. Shallow clouds play a large role in the Earth’s radiation balance yet are poorly represented in climate models. For this project four subjective patterns of organization were defined: Sugar, Flower, Fish, and Gravel. On cloud-labeling days at two institutes, 67 scientists screened 10,000 satellite images on a crowdsourcing platform and classified almost 50,000 mesoscale cloud clusters. This dataset is then used as a training dataset for deep learning algorithms that make it possible to automate the pattern detection and create global climatologies of the four patterns. Analysis of the geographical distribution and large-scale environmental conditions indicates that the four patterns have some overlap with established modes of organization, such as open and closed cellular convection, but also differ in important ways. The results and dataset from this project suggest promising research questions. Further, this study illustrates that crowdsourcing and deep learning complement each other well for the exploration of image datasets.

Sugar, Gravel, Fish, and Flowers: Dependence of Mesoscale Patterns of Trade-Wind Clouds on Environmental Conditions.

Trade‐wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as flowers, fish, gravel, and sugar. We show that these four patterns can be identified objectively from satellite observations by analyzing the spatial distribution of infrared brightness temperatures. By applying this analysis to 19 years of data, we examine relationships between cloud patterns and large‐scale environmental conditions. This investigation reveals that on daily and interannual timescales, the near‐surface wind speed and the strength of the lower‐tropospheric stability discriminate the occurrence of the different organization patterns. These results, combined with the tight relationship between cloud patterns, low‐level cloud amount, and cloud‐radiative effects, suggest that the mesoscale organization of shallow clouds might change under global warming. The role of shallow convective organization in determining low‐cloud feedback should thus be investigated.

Monitoring nearshore ecosystem health using Pacific razor clams (Siliqua patula) as an indicator species.

An emerging approach to ecosystem monitoring involves the use of physiological biomarker analyses in combination with gene transcription assays. For the first time, we employed these tools to evaluate the Pacific razor clam (Siliqua patula), which is important both economically and ecologically, as a bioindicator species in the northeast Pacific. Our objectives were to (1) develop biomarker and gene transcription assays with which to monitor the health of the Pacific razor clam, (2) acquire baseline biomarker and gene transcription reference ranges for razor clams, (3) assess the relationship between physiological and gene transcription assays and (4) determine if site-level differences were present. Pacific razor clams were collected in July 2015 and 2016 at three sites within each of two national parks in southcentral Alaska. In addition to determining reference ranges, we found differences in biomarker assay and gene transcription results between parks and sites which indicate variation in both large-scale and local environmental conditions. Our intent is to employ these methods to evaluate Pacific razor clams as a bioindicator of nearshore ecosystem health. Links between the results of the biomarker and gene transcription assays were observed that support the applicability of both assays in ecosystem monitoring. However, we recognize the need for controlled studies to examine the range of responses in physiology and gene transcripts to different stressors.

Change of spatial distribution in the ichiotocenosis of the shabolat estuary in the process of its anthropogenic transformation

Consequences of Shabolat estuary natural ecosystems transformation under the influence of anthropogenic factors are reflected in the composition of ichthyocenosis, changes in the basic population characteristics of the most mass species.The purpose of the work was to find out the spatial distribution of the Shabolat estuary most massive representatives of the ichthyocenosis in terms of its anthropogenic transformation.Material and methods. The material for the study was selected from industrial fishing gear in the spring, summer and autumn periods of 2009-2012. A complete biological analysis of fish (goby round, goby grass, flounder, flounder, mullet pilengas, etc.) was carried out according to the conventional method.Result. The regularities of formation of ichthyocenosis largest masses populations were studied depending on: water salinity, connection with adjacent water areas, fish acclimatization and introduction, anthropogenic loading and peculiarities of spatial distribution of ichthyocenosis largest masses populations in aquatics.The most important Shabolat estuary ichthyocomplex components include representatives of the Gobiidae family, the Platichthys luscus population and the mullet family representatives.Of particular interest to the members of the goby family are the mass species of gobies: the round goby Neogobius melanostomus and the grass goby Zosterisessor ophiocephalus, which are able to hibernate and reproduce in the estuary. This is an important link in the food chains of the reservoir. By entering into competition with other representatives of ichthyocenosis, they significantly affect the state of the forage base and production capacity of the estuary.Representatives of the mullet family and gloss flounder are distributed in the estuary deep water areas and in areas with maximum salinity.Conclusions. It has been established, that in the conditions of anthropogenic transformation of the estuary, in the last 35-40 years, the round goby and grass goby numbers and distribution range have decreased. In bulk, they have survived only in reservoir small, local areas, due to the deterioration of reproduction conditions and the degradation of the zoster and reddest associations. The main reasons for the decline in the size and distribution range of gobies in the Shabolatsky estuary was their mass death as a result of a large-scale environmental catastrophe and reproduction conditions deterioration. The reason for the significant decrease in the flounder and mullet number and distribution range was the mass death in 1992, as well as changes in the salinity of the Shabolat estuary

Seasonal Climate Prediction Models for the Number of Landfalling Tropical Cyclones in China

Two prediction models are developed to predict the number of landfalling tropical cyclones (LTCs) in China during June–August (JJA). One is a statistical model using preceding predictors from the observation, and the other is a hybrid model using both the aforementioned preceding predictors and concurrent summer large-scale environmental conditions from the NCEP Climate Forecast System version 2 (CFSv2). (1) For the statistical model, the year-to-year increment method is adopted to analyze the predictors and their physical processes, and the JJA number of LTCs in China is then predicted by using the previous boreal summer sea surface temperature (SST) in Southwest Indonesia, preceding October South Australia sea level pressure, and winter SST in the Sea of Japan. The temporal correlation coefficient between the observed and predicted number of LTCs during 1983–2017 is 0.63. (2) For the hybrid prediction model, the prediction skill of CFSv2 initiated each month from February to May in capturing the relationships between summer environmental conditions (denoted by seven potential factors: three steering factors and four gene-sis factors) and the JJA number of LTCs is firstly evaluated. For the 2- and 1-month leads, CFSv2 has successfully reproduced these relationships. For the 4-, 3-, and 2-month leads, the predictor of geopotential height at 500 hPa over the western North Pacific (WNP) shows the worst forecasting skill among these factors. In general, the summer relative vorticity at 850 hPa over the WNP is a modest predictor, with stable and good forecasting skills at all lead times.

Temperature patterns and mechanisms influencing coral bleaching during the 2016 El Niño

Under extreme heat stress, corals expel their symbiotic algae and colour (that is, ‘bleaching’), which often leads to widespread mortality. Predicting the large-scale environmental conditions that reinforce or mitigate coral bleaching remains unresolved and limits strategic conservation actions1,2. Here we assessed coral bleaching at 226 sites and 26 environmental variables that represent different mechanisms of stress responses from East Africa to Fiji through a coordinated effort to evaluate the coral response to the 2014–2016 El Niño/Southern Oscillation thermal anomaly. We applied common time-series methods to study the temporal patterning of acute thermal stress and evaluated the effectiveness of conventional and new sea surface temperature metrics and mechanisms in predicting bleaching severity. The best models indicated the importance of peak hot temperatures, the duration of cool temperatures and temperature bimodality, which explained ~50% of the variance, compared to the common degree-heating week temperature index that explained only 9%. Our findings suggest that the threshold concept as a mechanism to explain bleaching alone was not as powerful as the multidimensional interactions of stresses, which include the duration and temporal patterning of hot and cold temperature extremes relative to average local conditions. Improved predictions of coral bleaching are critical. In a coordinated global survey effort during the 2016 El Niño, time-series patterns of peak hot temperatures, cool period durations and temperature bimodality were found to be better predictors of coral bleaching than common threshold metrics.

Assessment of Climatology and Predictability of Mid-Atlantic Tropical Cyclone Landfalls in a High-Atmospheric-Resolution Seasonal Prediction System

Abstract Tropical cyclone (TC) landfalls over the U.S. mid-Atlantic region, which include the so-called Sandy-like, or westward-curving, tracks, are among the most infrequent landfalls along the U.S. East Coast. However, when these events do occur, the resulting economic and societal consequences can be devastating. A recent example is Hurricane Sandy in 2012. Multimodel ensemble seasonal hindcasts conducted with a high-atmospheric-resolution coupled prediction system based on the ECMWF operational model (Project Minerva) are used here to compile the statistics of these rare events. Minerva hindcasts are found to exhibit skill in reproducing climatological characteristics of the mid-Atlantic TC landfalls particularly at the highest atmospheric horizontal spectral resolution of T1279 (16-km grid spacing). Historical forecasts are further interrogated to identify regional and large-scale environmental conditions associated with these rare TC tracks to better quantify their predictability on synoptic time scales, and their dependence on model resolution. Evolution of the large-scale atmospheric flow patterns leading to mid-Atlantic TC landfalls is analyzed using local finite-amplitude wave activity (LWA). We have identified large-amplitude quasi-stationary features in the LWA and sea surface temperature (SST) anomaly distributions that persist up to about a week leading to these land-falling events. A statistical model utilizing indices based on the LWA and SST anomalies as predictors is developed that exhibits skill (mostly at T1279) in predicting mid-Atlantic TC landfalls several days in advance. Implications of these results for longer time-scale predictions of mid-Atlantic TC landfalls including climate change projections are discussed.

Modulation of bay of bengal tropical cyclone activity by the madden-julian oscillation

The influence of the Madden-Julian oscillation (MJO) on global tropical cyclone (TC) activity has been well documented in many earlier studies. However, no prior studies have focused specifically on the MJO's impacts on TCs in the Bay of Bengal (BoB). Therefore, the present study examines the impact of the MJO on BoB TC activity during the two peak TC periods i.e. April–June (AMJ) and October–December (OND) from 1974 to 2015. The MJO considerably modulates various measures of TC activity in the BoB, including the number of TCs, the number of TC days, accumulated cyclone energy, the power dissipation index, TC genesis location and TC tracks. TC activity is significantly enhanced (suppressed) over the BoB when the convectively active MJO phase is positioned over the eastern Indian Ocean and the Maritime Continent (the Western Hemisphere and Africa). Alterations in the TC genesis locations and their tracks are more pronounced in OND than in AMJ. These changes in TC characteristics are mainly attributed to MJO-driven modulations in large-scale environmental conditions such as deep convection, mid-tropospheric relative humidity, sea surface temperature, sea level pressure, lower- and upper-level winds and vertical wind shear. A comprehensive knowledge of the MJO-TC relationship may be beneficial for short-term predictions of TC activity in the BoB.