As one of the most predominant interannual variabilities, the Indian Ocean Dipole (IOD) exerts great socio-economic impacts globally, especially on Asia, Africa, and Australia. While enormous efforts have been made since its discovery to... more
As one of the most predominant interannual variabilities, the Indian Ocean Dipole (IOD) exerts great socio-economic impacts globally, especially on Asia, Africa, and Australia. While enormous efforts have been made since its discovery to improve both climate models and statistical methods for better prediction, current skills in IOD predictions are mostly limited up to three months ahead. Here, we challenge this long-standing problem using a multi-task deep learning model that we name MTL-NET. Hindcasts of the IOD events during the past four decades indicate that the MTL-NET can predict the IOD well up to 7-month ahead, outperforming most of world-class dynamical models used for comparison in this study. Moreover, the MTL-NET can help assess the importance of different predictors and correctly capture the nonlinear relationships between the IOD and predictors. Given its merits, the MTL-NET is demonstrated to be an efficient model for improved IOD prediction.
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ACCESS-S1 will be the next version of the Australian Bureau of Meteorology's seasonal prediction system, due to become operational in early 2018. The multiweek and seasonal performance of ACCESS-S1 has been evaluated based on a... more
ACCESS-S1 will be the next version of the Australian Bureau of Meteorology's seasonal prediction system, due to become operational in early 2018. The multiweek and seasonal performance of ACCESS-S1 has been evaluated based on a 23-year hindcast set and compared to the current operational system, POAMA. The system has considerable enhancements compared to POAMA, including higher vertical and horizontal resolution of the component models and state-ofthe-art physics parameterisation schemes. ACCESS-S1 is based on the UK Met Office GloSea5-GC2 seasonal prediction system, but has enhancements to the ensemble generation strategy to make it appropriate for multi-week forecasting, and a larger ensemble size. ACCESS-S1 has markedly reduced biases in the mean state of the climate, both globally and over Australia, compared to POAMA. ACCESS-S1 also better predicts the early stages of the development of the El Niño Southern Oscillation (through the predictability barrier) and the Indian Oce...
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Under global warming, surface air temperature has risen rapidly and sea ice has decreased markedly in the Arctic. These drastic climate changes have brought about various severe impacts on the vulnerable environment and ecosystem there.... more
Under global warming, surface air temperature has risen rapidly and sea ice has decreased markedly in the Arctic. These drastic climate changes have brought about various severe impacts on the vulnerable environment and ecosystem there. Thus, accurate prediction of Arctic climate becomes more important than before. Here we examine the seasonal to interannual predictive skills of 2-m air temperature (2-m T) and sea ice cover (SIC) over the Arctic region (70°–90°N) during 1980–2014 with a high-resolution global coupled model called the Met Office Decadal Prediction System, version 3 (DePreSys3). The model captures well both the climatology and interannual variability of the Arctic 2-m T and SIC. Moreover, the anomaly correlation coefficient of Arctic-averaged 2-m T and SIC shows statistically significant skills at lead times up to 16 months. This is mainly due to the contribution of strong decadal trends. In addition, it is found that the peak warming trend of Arctic 2-m T lags the ma...
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In this study, a spatial model has been developed to investigate the role of water temperature to the distribution of bacteria over the selected regions in the Bay of Bengal, located in the southern region of Bangladesh using... more
In this study, a spatial model has been developed to investigate the role of water temperature to the distribution of bacteria over the selected regions in the Bay of Bengal, located in the southern region of Bangladesh using next-generation sequencing. Bacterial concentration, quantitative polymerase chain reactions, and sequencing were performed on water samples and identified Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, Planctomycetes, Proteobacteria, and Verrucomicrobia. The spatial model tessellated the parts of the Bay of Bengal with hexagons and analyzed the relationship between the distribution of bacteria and water temperature. A geographically weighted regression was used to observe whether water temperature contributed strongly or weakly to the distribution of bacteria. The residuals were examined to assess the model’s fitness. The spatial model has the potential to predict the bacterial diversity in the sele...
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The Atlantic Niño/Niña, one of the dominant interannual variability in the equatorial Atlantic, exerts prominent influence on the Earth’s climate, but its prediction skill shown previously was unsatisfactory and limited to two to three... more
The Atlantic Niño/Niña, one of the dominant interannual variability in the equatorial Atlantic, exerts prominent influence on the Earth’s climate, but its prediction skill shown previously was unsatisfactory and limited to two to three months. By diagnosing the recently released North American Multimodel Ensemble (NMME) models, we find that the Atlantic Niño/Niña prediction skills are improved, with the multi-model ensemble (MME) reaching five months. The prediction skills are season-dependent. Specifically, they show a marked dip in boreal spring, suggesting that the Atlantic Niño/Niña prediction suffers a “spring predictability barrier” like ENSO. The prediction skill is higher for Atlantic Niña than for Atlantic Niño, and better in the developing phase than in the decaying phase. The amplitude bias of the Atlantic Niño/Niña is primarily attributed to the amplitude bias in the annual cycle of the equatorial sea surface temperature (SST). The anomaly correlation coefficient scores ...
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Natural modes of climate variations such as Indian Ocean Dipole (IOD), El Nino/Southern Oscillation (ENSO) and recently identified ENSO Modoki have huge impacts on many parts of the world. For example, some of the extreme flooding events... more
Natural modes of climate variations such as Indian Ocean Dipole (IOD), El Nino/Southern Oscillation (ENSO) and recently identified ENSO Modoki have huge impacts on many parts of the world. For example, some of the extreme flooding events in East Africa and droughts in Australia are associated with the positive IODs. The impact was severe when in a rare turn of the history three positive dipole events evolved back to back during 2006, 2007 and 2008. In addition, more number of El Nino Modoki (which causes a different teleconnection pattern as compared to that of ENSO) events are observed in recent decades. These climate phenomena also influence high-frequency weather events by either anchoring or destroying the triggering mechanisms. Furthermore, these climate variations influence the coastal securities by modulating coastal sea level variations on interannual to decadal time scales. Therefore, it has become an essential task to understand these changes in the characteristics of the ...
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The middle and lower reaches of the Yangtze River valley (YRV), which are among the most densely populated regions in China, are subject to frequent flooding. In this study, the predictor importance analysis model was used to sort and... more
The middle and lower reaches of the Yangtze River valley (YRV), which are among the most densely populated regions in China, are subject to frequent flooding. In this study, the predictor importance analysis model was used to sort and select predictors, and five methods (multiple linear regression (MLR), decision tree (DT), random forest (RF), backpropagation neural network (BPNN), and convolutional neural network (CNN)) were used to predict the interannual variation of summer precipitation over the middle and lower reaches of the YRV. Predictions from eight climate models were used for comparison. Of the five tested methods, RF demonstrated the best predictive skill. Starting the RF prediction in December, when its prediction skill was highest, the 70-year correlation coefficient from cross validation of average predictions was 0.473. Using the same five predictors in December 2019, the RF model successfully predicted the YRV wet anomaly in summer 2020, although it had weaker ampli...
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This study investigates the contribution of Boreal Summer Intraseasonal Oscillation (BSISO) to the tropical cyclone (TC) activity over the North Indian Ocean (NIO) and assesses the prediction skill of a statistical Generalised Additive... more
This study investigates the contribution of Boreal Summer Intraseasonal Oscillation (BSISO) to the tropical cyclone (TC) activity over the North Indian Ocean (NIO) and assesses the prediction skill of a statistical Generalised Additive Model (GAM) and two machine learning techniques—Random Forest (RF) and Support Vector Regression (SVR). Joint Typhoon Warning Centre TC and BSISO1 Index data have been used for a period of 33-year (1981–2013). By considering eight phases of BSISO, prediction models have been developed using a kernel density estimation for the TC genesis, Euler integration step to fit the tracks, and a country mask approach for the landfall across the NIO rim countries. Result shows that GAM has the highest prediction skill compared to the RF and SVR. Westward and Northward moving TCs are controlled by the wind and the TC activities during BSISO phases which modulated by wind matched well against observations over the NIO. Distance calculation validation method is applied to assess the skill of models.
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Future changes in the frequency of extreme drought events are of vital importance for risk assessment and relevant policy making. But a reliable estimation of their probability is intrinsically challenging due to limited available... more
Future changes in the frequency of extreme drought events are of vital importance for risk assessment and relevant policy making. But a reliable estimation of their probability is intrinsically challenging due to limited available observations or simulations. Here, we use two large ensemble simulations, 50 members from CanESM2 and 40 members from CESM1 under the future RCP8.5 scenario, to elaborate a reliable projection of the 100-year drought events (once in a century) under different warming levels. It is however necessary to firstly remove systematic biases for the simulated temperature and precipitation through a bias-correction method based on quantile mapping. Droughts are diagnosed with the Standardized Precipitation Evapotranspiration Index (SPEI), which considers both precipitation and potential evapotranspiration (PET, involving temperature). The results show that the frequency of extreme droughts increases with the continued global warming. Some differences between the tw...
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Abstract The present study investigates the association of East Asian westerly jet (EAWJ) variations with spring rainfall anomalies in Northern China and Yangtze-Huaihe River Valley (NC-YHV) and the dynamics using reanalysis datasets.... more
Abstract The present study investigates the association of East Asian westerly jet (EAWJ) variations with spring rainfall anomalies in Northern China and Yangtze-Huaihe River Valley (NC-YHV) and the dynamics using reanalysis datasets. Based on the climatology and interannual variation in 200-hPa zonal winds, the index EAWJI is defined as the average 200-hPa zonal wind velocity over a zonal 10-degree-width belt centered around the seasonal-mean jet axis between 105°E and 145°E. Associated with anomalously strengthened EAWJ, significant negative rainfall anomalies are observed over NC-YHV. The dynamics are as follows. When the EAWJ is anomalously intensified, a quasi-barotropic Pacific-Japan-like (PJ) teleconnection along coastal China and an associated anomalous westerly flow over NC-YHV are observed. In middle-lower troposphere, Tibetan Plateau (TP) drastically reduces the anomalous southwesterly momentum transported into NC-YHV, turning the westerly anomalies into northwesterly anomalies. The anomalous northwesterly winds over NC-YHV advect cold and dry air southeastward toward NC-YHV, which induce downward motion (diabatic heating feedback is weak) and negative moisture anomalies, respectively, and thus cause reduced rainfall anomalies over NC-YHV. Anomalous winter SSTAs in western Pacific and tropical Indian Ocean associated with ENSO are sustained until spring, inducing barotropic waves that propagate northwards to cause EAWJ-associated circulation anomalies and thus bring about spring rainfall anomalies in NC-YHV. The quasi-barotropic features of the EAWJ-associated circulation anomalies and their association with the northward propagation of tropical SSTA-induced barotropic waves together suggest that EAWJ-associated circulation variations are at least partly among the external forcings responsible for spring rainfall anomalies in NC-YHV.
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Thunderstorms (TS) are one of the most devastating atmospheric phenomena, which causes massive damage and adverse losses in various sectors, including agriculture and infrastructure. This study investigates the spatiotemporal... more
Thunderstorms (TS) are one of the most devastating atmospheric phenomena, which causes massive damage and adverse losses in various sectors, including agriculture and infrastructure. This study investigates the spatiotemporal variabilities of TS days over Bangladesh and their connection with El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The TS, ENSO and IOD years’ data for 42 years (1975–2016) are used. The trend in TS days at the spatiotemporal scale is calculated using Mann Kendall and Spearman’s rho test. Results suggest that the trend in TS days is positive for all months except December and January. The significant trends are found for May and June, particularly in the northern and northeastern regions of Bangladesh. In the decadal scale, most of the regions show a significant upward trend in TS days. Results from the Weibull probability distribution model show the highest TS days in the northeastern region. The connection between TS days and ENSO/IOD indic...
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Over time, the initial algorithms to derive atmospheric density from accelerometers have been significantly enhanced. In this study, we discussed one of the accurate accelerometers—the Earth’s Magnetic Field and Environment Explorers,... more
Over time, the initial algorithms to derive atmospheric density from accelerometers have been significantly enhanced. In this study, we discussed one of the accurate accelerometers—the Earth’s Magnetic Field and Environment Explorers, more commonly known as the Swarm satellites. Swarm satellite–C level 2 (measurements from the Swam accelerometers) density, solar index (F10.7), and geomagnetic index (Kp) data have been used for a year (mid 2014–2015), and the different types of temporal (the diurnal, multi–day, solar–rotational, semi–annual, and annual) atmospheric density variations have been investigated using the statistical approaches of correlation coefficient and wavelet transform. The result shows the density varies due to the recurrent geomagnetic force at multi–day, solar irradiance during the day, appearance and disappearance of the Sun’s active region, Sun–Earth distance, large scale circulation, and the formation of an aurora. Additionally, a correlation coefficient was u...
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Central Africa (CA) is identified as a location of a large positive trend of the occurrence of heat waves (HWs) during 1979–2016, appearing to result mostly from a regime shift around the year 2000. Therefore, we study the evolution of... more
Central Africa (CA) is identified as a location of a large positive trend of the occurrence of heat waves (HWs) during 1979–2016, appearing to result mostly from a regime shift around the year 2000. Therefore, we study the evolution of synoptic features associated with the occurrence of HW events in CA. It is found that the HW-related circulation is typically characterized by an anomalous convergence in the upper troposphere but there are important differences for HW events occurring in the south region of CA (CA_S) versus the north region (CA_N). For the occurrence of the HW events in CA_S, the anomalous subsidence associated with upper troposphere anomalous convergence is the dominant factor for their occurrence and magnitude: the strong subsidence leads to warming through greater solar insolation. The HW events in CA_S are also accompanied by an anomalous surface anticyclone in the north with anomalous northerly flow transporting heat into the CA_S region. In contrast, although t...
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El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation,... more
El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation, affecting global climate, marine and terrestrial ecosystems, fisheries and human activities. The alternation of warm El Niño and cold La Niña conditions, referred to as the El Niño-Southern Oscillation (ENSO), represents the strongest year-to-year fluctuation of the global climate system. Here we provide a synopsis of our current understanding of the spatio-temporal complexity of this important climate mode and its influence on the Earth system.
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During year-to-year El Niño events in recent decades, major sea surface warming has occurred frequently in the central Pacific. This is distinct from the eastern Pacific warming pattern during canonical El Niño events. Accordingly, the... more
During year-to-year El Niño events in recent decades, major sea surface warming has occurred frequently in the central Pacific. This is distinct from the eastern Pacific warming pattern during canonical El Niño events. Accordingly, the central-Pacific El Niño exerts distinct impacts on ecosystems, climate and hurricanes worldwide. The increased frequency of the new type of El Niño presents a challenge not only for the understanding of El Niño dynamics and its change but also for the prediction of El Niño and its global impacts at present and future climate. Previous studies have proposed different indices to represent the two types of El Niño for better understanding, prediction and impact assessment. Here, we find that all popularly used indices for the central-Pacific El Niño show a dominant spectral peak at a decadal period with comparatively weak variance at interannual timescales. Our results suggest that decadal anomalies have an important contribution to the occurrence of the...
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Multi-year La Niña events often induce persistent cool and wet climate over global lands, altering and in some case mitigating regional climate warming impacts. The latest event lingered from mid-2010 to early 2012 and brought about... more
Multi-year La Niña events often induce persistent cool and wet climate over global lands, altering and in some case mitigating regional climate warming impacts. The latest event lingered from mid-2010 to early 2012 and brought about intensive precipitation over many land regions of the world, particularly Australia. This resulted in a significant drop in global mean sea level despite the background upwards trend. This La Niña event is surprisingly predicted out to two years ahead in a few coupled models, even though the predictability of El Niño-Southern Oscillation during 2002-2014 has declined owing to weakened ocean-atmosphere interactions. However, the underlying mechanism for high predictability of this multi-year La Niña episode is still unclear. Experiments based on a climate model that demonstrates a successful two-year forecast of the La Niña support the hypothesis that warm sea surface temperature (SST) anomalies in the Atlantic and Indian Oceans act to intensify the easte...
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Extreme El Niño events severely disrupt the global climate, causing pronounced socio-economic losses. A prevailing view is that extreme El Niño events, defined by total precipitation or convection in the Niño3 area, will increase 2-fold... more
Extreme El Niño events severely disrupt the global climate, causing pronounced socio-economic losses. A prevailing view is that extreme El Niño events, defined by total precipitation or convection in the Niño3 area, will increase 2-fold in the future. However, this projected change was drawn without removing the potential impacts of Coupled Model Intercomparison Project phase 5 (CMIP5) models’ common biases. Here, we find that the models’ systematic biases in simulating tropical climate change over the past century can reduce the reliability of the projected change in the Pacific sea surface temperature (SST) and its related extreme El Niño frequency. The projected Pacific SST change, after removing the impacts of 13 common biases, displays a ‘La Niña-like’ rather than ‘El Niño-like’ change. Consequently, the extreme El Niño frequency, which is highly linked to the zonal distribution of the Pacific SST change, would remain mostly unchanged under CMIP5 warming scenarios. This finding...
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Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation... more
Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate th...
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A global high-resolution coupled general circulation model (CGCM) consisting of a T319 atmosphere general circulation model and an eddy-permitted ocean general circulation model is examined in terms of the reproducibility of the northern... more
A global high-resolution coupled general circulation model (CGCM) consisting of a T319 atmosphere general circulation model and an eddy-permitted ocean general circulation model is examined in terms of the reproducibility of the northern hemisphere tropical cyclone (TC) activity as well as the large-scale environmental conditions. The CGCM successfully simulates the realistic TC structure, TC-induced ocean response, and TC genesis frequency. The global TC genesis frequency simulated by the high-resolution CGCM is much closer to the observed, compared that simulated by the mediumresolution (T106) CGCM. In addition, the high-resolution CGCM partially reproduces the bimodal seasonal cycle of the North Indian Ocean cyclogenesis, while the mediumresolution CGCM fails to simulate it. The high-resolution CGCM also reasonably reproduces the environmental conditions favorable for the TC genesis: warm sea surface temperature, low-level cyclonic circulation, weak vertical wind shear, and high ...
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Accurate prediction of the Asian-Australian monsoon (A-AM) seasonal variation is one of the most important and challenging tasks in climate prediction. In order to understand the causes of the low accuracy in the current prediction of the... more
Accurate prediction of the Asian-Australian monsoon (A-AM) seasonal variation is one of the most important and challenging tasks in climate prediction. In order to understand the causes of the low accuracy in the current prediction of the A-AM precipitation, this study strives to determine to what extent the ten state-of-the-art coupled atmosphere-ocean-land climate models and their multi-model ensemble (MME) can
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Abstract The effect of atmospheric horizontal resolution on tropical variability is investigated within the modified Scale Interaction Experiment (SINTEX) coupled model, SINTEX-Frontier (SINTEX-F), developed jointly at Istituto Nazionale... more
Abstract The effect of atmospheric horizontal resolution on tropical variability is investigated within the modified Scale Interaction Experiment (SINTEX) coupled model, SINTEX-Frontier (SINTEX-F), developed jointly at Istituto Nazionale di Geofisica e Vulcanologia (INGV), L' ...
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The physical mechanism for the amplitude asymmetry of SST anomalies (SSTA) between the positive and negative phases of the Indian Ocean dipole (IOD) is investigated, using Simple Ocean Data Assimi- lation (SODA) and NCAR-NCEP data. It is... more
The physical mechanism for the amplitude asymmetry of SST anomalies (SSTA) between the positive and negative phases of the Indian Ocean dipole (IOD) is investigated, using Simple Ocean Data Assimi- lation (SODA) and NCAR-NCEP data. It is found that a strong negative skewness appears in the IOD east pole (IODE) in the mature phase (September-November (SON)), while the skewness in the IOD west pole is insignificant. Thus, the IOD asymmetry is primarily caused by the negative skewness in IODE. A mixed-layer heat budget analysis indicates that the following two air-sea feedback processes are responsible for the negative skewness. The first is attributed to the asymmetry of the wind stress-ocean advection-SST feedback. During the IOD developing stage (June-September (JJAS)), the ocean linear advection tends to enhance the mixed-layer temperature tendency, while nonlinear advection tends to cool the ocean in both the positive and negative events, thus contributing to the negative skewness in IODE. The second process is attributed to the asymmetry of the SST-cloud-radiation (SCR) feedback. For a positive IODE, the negative SCR feedback continues with the increase of warm SSTA. For a negative IODE, the same negative SCR feedback works when the amplitude of SSTA is small. After reaching a critical value, the cold SSTA may completely suppress the mean convection and lead to cloud free conditions; a further drop of the cold SSTA does not lead to additional thermal damping so that the cold SSTA may grow faster. A wind-evaporation-SST feedback may further amplify the asymmetry induced by the aforementioned nonlinear advection and SCR feedback processes.