This page has only limited features, please log in for full access.

Prof. Dr. JAMSTEC人材育成・研修担当 Behera
JAMSTEC

Basic Info


Research Keywords & Expertise

0 Physical Oceanography
0 climate prediction
0 Ocean Circulation
0 Climate Variability and Change
0 climate application

Fingerprints

Climate Variability and Change
Ocean Circulation
climate prediction

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Research article
Published: 16 August 2021 in Journal of Geophysical Research: Oceans
Reads 0
Downloads 0

Sea ice in the Weddell Sea plays important roles in the albedo, air-sea heat, freshwater, and gas exchanges and the formation of the Antarctic Bottom Water on the continental shelf that regulates global climate through deep thermohaline circulation. Sea ice extent in the Weddell Sea does not show any significant trend in the four-decade satellite observation period but does experience large interannual-to-decadal variability. Physical processes underlying this variability are difficult to examine because of a paucity of prolonged observations. Using a coupled general circulation model, we corroborate the observational finding that decadal increases in sea ice extent are preceded by weakening of the mean westerly winds linked to the Southern Annular Mode. Weakening of the westerly winds over the Weddell Sea reduces the northward Ekman current and suppresses upwelling of warm water from the subsurface ocean; this lowers the upper-ocean temperature, causing an increase in sea ice. In a sensitivity experiment where the interannual sea surface temperature variations are suppressed outside the South Atlantic and the Weddell Sea, decadal increase in the sea ice extent over the Weddell Sea is induced by a decrease in the upper ocean temperature owing to enhanced horizontal advection by the Weddell Gyre. The strengthening of the Weddell Gyre increases the upper-ocean salinity as a result of enhanced evaporation and brine rejection associated with the sea ice increase. These results demonstrate that both the remote atmospheric forcing and local ice-ocean interaction are crucial for generation of decadal sea ice variability in the Weddell Sea.

ACS Style

Yushi Morioka; Swadhin K. Behera. Remote and Local Processes Controlling Decadal Sea Ice Variability in the Weddell Sea. Journal of Geophysical Research: Oceans 2021, 126, 1 .

AMA Style

Yushi Morioka, Swadhin K. Behera. Remote and Local Processes Controlling Decadal Sea Ice Variability in the Weddell Sea. Journal of Geophysical Research: Oceans. 2021; 126 (8):1.

Chicago/Turabian Style

Yushi Morioka; Swadhin K. Behera. 2021. "Remote and Local Processes Controlling Decadal Sea Ice Variability in the Weddell Sea." Journal of Geophysical Research: Oceans 126, no. 8: 1.

Preprint content
Published: 03 March 2021
Reads 0
Downloads 0

Presence of a stationary zonal wavenumber-4 (W4) pattern is revealed in the sea surface temperature (SST) anomaly over southern subtropics (20°S-55°S) using empirical orthogonal function analysis. This W4 pattern is found to be seasonally phase-locked to the austral summer (persists up to mid-autumn) and independent of other known tropical and extra-tropical climate phenomena. A thermodynamic coupling of atmosphere and the upper ocean helps in generating the W4 pattern, which later terminates due to the breaking of the ocean-atmosphere positive feedback. Due to anomalous convection over western subtropical pacific near the westerly jet, the signal appears first in the atmosphere during early November. Later, the disturbance gets trapped in the westerly waveguide which circumnavigates the globe and produces an atmospheric W4 pattern in early December (20-30 days later). Then, the signal transported to the ocean through the ocean-atmosphere feedback and sustained in the ocean (after it disappears from the atmosphere) as it has high specific heat capacity. During the positive phase of the W4 event, the cold SST anomaly develops over the southeastern and -western side (SE-NW) of Australia creating an anomalous divergence circulation. It favours the moisture transport towards the south-eastern region of the continent. Consequently, the specific humidity increases and causes an above-normal rainfall in a SE-NW axis over Australia. An opposite process is seen in case of a negative W4 event.

ACS Style

Balaji Senapati; Mihir Dash; Swadhin Behera. Global wave number-4 pattern in the southern subtropics. 2021, 1 .

AMA Style

Balaji Senapati, Mihir Dash, Swadhin Behera. Global wave number-4 pattern in the southern subtropics. . 2021; ():1.

Chicago/Turabian Style

Balaji Senapati; Mihir Dash; Swadhin Behera. 2021. "Global wave number-4 pattern in the southern subtropics." , no. : 1.

Journal article
Published: 13 November 2020 in Atmosphere
Reads 0
Downloads 0

In this paper, the rainfall trend of the West Coast Plain and Hill Agro-Climatic Region is analyzed for 117 years (1901–2017). This region is a globally recognized biodiversity hotspot and known for one of the highest rainfall receiving regions in India. Rainfall grid dataset is used for the analysis of rainfall trends on monthly, seasonal, and decadal time scales. Modified Mann–Kendall’s test, Linear Regression, Innovative Trend Analysis, Sen’s Slope test, Weibull’s Recurrence Interval, Pearson’s Coefficient of Skewness, Consecutive Disparity Index, Kurtosis, and some other important statistical techniques are employed for trend analysis. Results indicate that the rainfall trend is significant in January, July, August, September as well as the Winter season. Among all the significant trends, January and July showed a decreasing rainfall trend. July has the highest contribution (30%) among all the obtained monotonic trend to annual rainfall and coincidentally has the highest trend magnitude. August and September months with a combined contribution of 30% to annual rainfall, show an increasing monotonic trend with high magnitude whereas Winter season shows a monotonic decreasing rainfall trend with comparatively low magnitudes. Decadal analysis along with the study of recurrence interval of excess and deficit years helps to understand the decadal rhythm of trend and the magnitude of extreme monthly and seasonal events. Skewness reveals that rainfall dataset of all the periodic results is right-skewed and the recurrence interval also supports the skewness results. Sharply decreasing rainfall in July and rising rainfall in August and September is predictive of the impact on agriculture, biodiversity and indicates the rainfall regime shift in the region.

ACS Style

Atul Saini; Netrananda Sahu; Pankaj Kumar; Sridhara Nayak; Weili Duan; Ram Avtar; Swadhin Behera. Advanced Rainfall Trend Analysis of 117 Years over West Coast Plain and Hill Agro-Climatic Region of India. Atmosphere 2020, 11, 1225 .

AMA Style

Atul Saini, Netrananda Sahu, Pankaj Kumar, Sridhara Nayak, Weili Duan, Ram Avtar, Swadhin Behera. Advanced Rainfall Trend Analysis of 117 Years over West Coast Plain and Hill Agro-Climatic Region of India. Atmosphere. 2020; 11 (11):1225.

Chicago/Turabian Style

Atul Saini; Netrananda Sahu; Pankaj Kumar; Sridhara Nayak; Weili Duan; Ram Avtar; Swadhin Behera. 2020. "Advanced Rainfall Trend Analysis of 117 Years over West Coast Plain and Hill Agro-Climatic Region of India." Atmosphere 11, no. 11: 1225.

Comment
Published: 12 November 2020 in Nature Communications
Reads 0
Downloads 0

Early studies of weather, seasonality, and environmental influences on COVID-19 have yielded inconsistent and confusing results. To provide policy-makers and the public with meaningful and actionable environmentally-informed COVID-19 risk estimates, the research community must meet robust methodological and communication standards.

ACS Style

Benjamin F. Zaitchik; Neville Sweijd; Joy Shumake-Guillemot; Andy Morse; Chris Gordon; Aileen Marty; Juli Trtanj; Juerg Luterbacher; Joel Botai; Swadhin Behera; Yonglong Lu; Jane Olwoch; Ken Takahashi; Jennifer D. Stowell; Xavier Rodó. A framework for research linking weather, climate and COVID-19. Nature Communications 2020, 11, 1 -3.

AMA Style

Benjamin F. Zaitchik, Neville Sweijd, Joy Shumake-Guillemot, Andy Morse, Chris Gordon, Aileen Marty, Juli Trtanj, Juerg Luterbacher, Joel Botai, Swadhin Behera, Yonglong Lu, Jane Olwoch, Ken Takahashi, Jennifer D. Stowell, Xavier Rodó. A framework for research linking weather, climate and COVID-19. Nature Communications. 2020; 11 (1):1-3.

Chicago/Turabian Style

Benjamin F. Zaitchik; Neville Sweijd; Joy Shumake-Guillemot; Andy Morse; Chris Gordon; Aileen Marty; Juli Trtanj; Juerg Luterbacher; Joel Botai; Swadhin Behera; Yonglong Lu; Jane Olwoch; Ken Takahashi; Jennifer D. Stowell; Xavier Rodó. 2020. "A framework for research linking weather, climate and COVID-19." Nature Communications 11, no. 1: 1-3.

Research letter
Published: 23 September 2020 in Geophysical Research Letters
Reads 0
Downloads 0

Many parts of East Asia, including Japan, experienced extremely warm conditions during the 2019–2020 winter. These were successfully predicted in October of 2019 by the 108‐member ensemble seasonal prediction system based on the SINTEX‐F climate model. By analyzing covariability of intermember anomalies defined as deviations from the ensemble mean, we have found that the active convection over the western pole of the Indian Ocean Dipole (IOD) caused these unusual conditions over East Asia by generating the meander of the subtropical jet.

ACS Style

Takeshi Doi; Swadhin K. Behera; Toshio Yamagata. Wintertime Impacts of the 2019 Super IOD on East Asia. Geophysical Research Letters 2020, 47, 1 .

AMA Style

Takeshi Doi, Swadhin K. Behera, Toshio Yamagata. Wintertime Impacts of the 2019 Super IOD on East Asia. Geophysical Research Letters. 2020; 47 (18):1.

Chicago/Turabian Style

Takeshi Doi; Swadhin K. Behera; Toshio Yamagata. 2020. "Wintertime Impacts of the 2019 Super IOD on East Asia." Geophysical Research Letters 47, no. 18: 1.

Journal article
Published: 28 August 2020 in Sustainability
Reads 0
Downloads 0

The impact of Indo-Pacific climate variability in the South Asian region is very pronounced and their impact on agriculture is very important for the Indian subcontinent. In this study, rice productivity, climatic factors (Rainfall, Temperature and Soil Moisture) and associated major Indo-Pacific climate indices in Bihar were investigated. Bihar is one of the major rice-producing states of India and the role of climate variability and prevailing climate indices in six events (between 1991–2014) with severer than −10% rice productivity are analyzed. The Five-year moving average, Pearson’s Product Moment Correlation, Partial Correlation, Linear Regression Model, Mann Kendall Test, Sen’s Slope and some other important statistical techniques were used to understand the association between climatic variables and rice productivity. Pearson’s Product Moment Correlation provided an overview of the significant correlation between climate indices and rice productivity. Whereas, Partial Correlation provided the most refined results on it and among all the climate indices, Niño 3, Ocean Niño Index and Southern Oscillation Index are found highly associated with years having severer than −10% decline in rice productivity. Rainfall, temperature and soil moisture anomalies are analyzed to observe the importance of climate factors in rice productivity. Along with the lack of rainfall, lack of soil moisture and persistent above normal temperature (especially maximum temperature) are found to be the important factors in cases of severe loss in rice productivity. Observation of the dynamics of ocean-atmosphere coupling through the composite map shows the Pacific warming signals during the event years. The analysis revealed a negative (positive) correlation of rice productivity with the Niño 3 and Ocean Niño Index (Southern Oscillation Index).

ACS Style

Netrananda Sahu; Atul Saini; Swadhin Behera; Takahiro Sayama; Sridhara Nayak; Limonlisa Sahu; Weili Duan; Ram Avtar; Masafumi Yamada; R. Singh; Kaoru Takara. Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India. Sustainability 2020, 12, 7023 .

AMA Style

Netrananda Sahu, Atul Saini, Swadhin Behera, Takahiro Sayama, Sridhara Nayak, Limonlisa Sahu, Weili Duan, Ram Avtar, Masafumi Yamada, R. Singh, Kaoru Takara. Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India. Sustainability. 2020; 12 (17):7023.

Chicago/Turabian Style

Netrananda Sahu; Atul Saini; Swadhin Behera; Takahiro Sayama; Sridhara Nayak; Limonlisa Sahu; Weili Duan; Ram Avtar; Masafumi Yamada; R. Singh; Kaoru Takara. 2020. "Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India." Sustainability 12, no. 17: 7023.

Journal article
Published: 09 July 2020 in Water
Reads 0
Downloads 0

The potential impact of climate variability on the hydrological regime in the Mahanadi river basin is of great importance for sustainable water resources management. The impact of climate variability on streamflow is analyzed in this study. The impact of climate variability modes on extreme events of Mahanadi basin during June, July, and August (JJA), and September, October, and November (SON) seasons were analyzed, with daily streamflow data of four gauge stations for 34 years from 1980 to 2013 found to be associated with the sea surface temperature variations over Indo-Pacific oceans and Indian monsoon. Extreme events are identified based on their persistent flow for six days or more, where selection of the stations was based on the fact that there was no artificially regulated streamflow in any of the stations. Adequate scientific analysis was done to link the streamflow variability with the climate variability and very significant correlation was found with Indian Ocean Dipole (IOD), El Nino Southern Oscillation (ENSO), El Nino Modoki Index (EMI), and Indian monsoon. Agriculture covers major portion of the basin; hence, the streamflow is very much essential for agriculture as well as population depending on it. Any disturbances in the general flow of the river has subjected an adverse impact on the inhabitants’ livelihood. While analyzing the correlation values, it was found that all stations displayed a significant positive correlation with Indian Monsoon. The respective correlation values were 0.53, 0.38, 0.44, and 0.38 for Andhiyarkore, Baronda, Rajim, and Kesinga during JJA season. Again in the case of stepwise regression analysis, Monsoon Index for the June, July, and August (MI-JJA) season (0.537 for Andhiyarkore) plays significant role in determining streamflow of Mahanadi basin during the JJA season and Monsoon Index for July, August, and September (MI-JAS) season (0.410 for Baronda) has a strong effect in affecting streamflow of Mahanadi during the SON season. Flood frequency analysis with Weibull’s plotting position method indicates future floods in the Mahanadi river basin in JJA season.

ACS Style

Netrananda Sahu; Arpita Panda; Sridhara Nayak; Atul Saini; Manoranjan Mishra; Takahiro Sayama; Limonlisa Sahu; Weili Duan; Ram Avtar; Swadhin Behera. Impact of Indo-Pacific Climate Variability on High Streamflow Events in Mahanadi River Basin, India. Water 2020, 12, 1952 .

AMA Style

Netrananda Sahu, Arpita Panda, Sridhara Nayak, Atul Saini, Manoranjan Mishra, Takahiro Sayama, Limonlisa Sahu, Weili Duan, Ram Avtar, Swadhin Behera. Impact of Indo-Pacific Climate Variability on High Streamflow Events in Mahanadi River Basin, India. Water. 2020; 12 (7):1952.

Chicago/Turabian Style

Netrananda Sahu; Arpita Panda; Sridhara Nayak; Atul Saini; Manoranjan Mishra; Takahiro Sayama; Limonlisa Sahu; Weili Duan; Ram Avtar; Swadhin Behera. 2020. "Impact of Indo-Pacific Climate Variability on High Streamflow Events in Mahanadi River Basin, India." Water 12, no. 7: 1952.

Research letter
Published: 16 April 2020 in Geophysical Research Letters
Reads 0
Downloads 0

A positive Indian Ocean Dipole (IOD) in 2019 that reached the level of the strongest events occurred in 1994 and 1997 and caused disasters in countries around the Indian Ocean. Using a quasi real‐time ensemble seasonal prediction system based on the Scale Interaction Experiment‐Frontier climate model, its occurrence was predicted a few seasons ahead and the possible impacts were warned by overcoming the so‐called winter predictability barrier. The successful prediction of such a super event at long lead time may contribute to reducing the risks of socioeconomic losses by introducing suitable measures for adaptation. Here, we have investigated possible sources of the successful prediction by analyzing covariability of intermember anomalies defined as deviations from the mean in the ensemble reforecasts. Interestingly, it is found that the potential predictability of the 2019 super positive event is linked with the preexisting El Niño Modoki in the tropical Pacific.

ACS Style

Takeshi Doi; Swadhin K. Behera; Toshio Yamagata. Predictability of the Super IOD Event in 2019 and Its Link With El Niño Modoki. Geophysical Research Letters 2020, 47, 1 .

AMA Style

Takeshi Doi, Swadhin K. Behera, Toshio Yamagata. Predictability of the Super IOD Event in 2019 and Its Link With El Niño Modoki. Geophysical Research Letters. 2020; 47 (7):1.

Chicago/Turabian Style

Takeshi Doi; Swadhin K. Behera; Toshio Yamagata. 2020. "Predictability of the Super IOD Event in 2019 and Its Link With El Niño Modoki." Geophysical Research Letters 47, no. 7: 1.

Publisher correction
Published: 05 February 2020 in Scientific Reports
Reads 0
Downloads 0

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

ACS Style

Yoonhee Kim; J. V. Ratnam; Takeshi Doi; Yushi Morioka; Swadhin Behera; Ataru Tsuzuki; Noboru Minakawa; Neville Sweijd; Philip Kruger; Rajendra Maharaj; Chisato Chrissy Imai; Chris Fook Sheng Ng; Yeonseung Chung; Masahiro Hashizume. Publisher Correction: Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model. Scientific Reports 2020, 10, 1 -1.

AMA Style

Yoonhee Kim, J. V. Ratnam, Takeshi Doi, Yushi Morioka, Swadhin Behera, Ataru Tsuzuki, Noboru Minakawa, Neville Sweijd, Philip Kruger, Rajendra Maharaj, Chisato Chrissy Imai, Chris Fook Sheng Ng, Yeonseung Chung, Masahiro Hashizume. Publisher Correction: Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model. Scientific Reports. 2020; 10 (1):1-1.

Chicago/Turabian Style

Yoonhee Kim; J. V. Ratnam; Takeshi Doi; Yushi Morioka; Swadhin Behera; Ataru Tsuzuki; Noboru Minakawa; Neville Sweijd; Philip Kruger; Rajendra Maharaj; Chisato Chrissy Imai; Chris Fook Sheng Ng; Yeonseung Chung; Masahiro Hashizume. 2020. "Publisher Correction: Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model." Scientific Reports 10, no. 1: 1-1.

Journal article
Published: 15 January 2020 in Scientific Reports
Reads 0
Downloads 0

The focus of this study is to evaluate the efficacy of Machine Learning (ML) algorithms in the long-lead prediction of El Niño (La Niña) Modoki (ENSO Modoki) index (EMI). We evaluated two widely used non-linear ML algorithms namely Support Vector Regression (SVR) and Random Forest (RF) to forecast the EMI at various lead times, viz. 6, 12, 18 and 24 months. The predictors for the EMI are identified using Kendall’s tau correlation coefficient between the monthly EMI index and the monthly anomalies of the slowly varying climate variables such as sea surface temperature (SST), sea surface height (SSH) and soil moisture content (SMC). The importance of each of the predictors is evaluated using the Supervised Principal Component Analysis (SPCA). The results indicate both SVR and RF to be capable of forecasting the phase of the EMI realistically at both 6-months and 12-months lead times though the amplitude of the EMI is underestimated for the strong events. The analysis also indicates the SVR to perform better than the RF method in forecasting the EMI.

ACS Style

Manali Pal; Rajib Maity; J. V. Ratnam; Masami Nonaka; Swadhin K. Behera. Long-lead Prediction of ENSO Modoki Index using Machine Learning algorithms. Scientific Reports 2020, 10, 1 -13.

AMA Style

Manali Pal, Rajib Maity, J. V. Ratnam, Masami Nonaka, Swadhin K. Behera. Long-lead Prediction of ENSO Modoki Index using Machine Learning algorithms. Scientific Reports. 2020; 10 (1):1-13.

Chicago/Turabian Style

Manali Pal; Rajib Maity; J. V. Ratnam; Masami Nonaka; Swadhin K. Behera. 2020. "Long-lead Prediction of ENSO Modoki Index using Machine Learning algorithms." Scientific Reports 10, no. 1: 1-13.

Journal article
Published: 27 December 2019 in Scientific Reports
Reads 0
Downloads 0

The out of phase tropical cyclone (TC) formation in the subtropical and tropical western North Pacific associated with local low-level wind vorticity anomaly, driven by the remote central and eastern equatorial Pacific warming/cooling, is investigated based on the reanalysis and observational data in the period of 1979−2017. TC frequencies in the subtropical and tropical western North Pacific appear to be connected to different remote heating/cooling sources and are linked to eastern and central Pacific warming/cooling, which are in turn related to canonical El Niño/Southern Oscillation (ENSO) and ENSO Modoki, respectively. TCs formed in subtropics (SfTC) are generally found to be associated with a dipole in wind vorticity anomaly, which is driven by the tropical eastern Pacific warming/cooling. Tropically formed TCs (TfTC) are seen to be triggered by the single-core of wind vorticity anomaly locally associated with the warming/cooling of central and eastern Pacific. The predicted ENSOs and ENSO Modokis, therefore, provide a potential source of seasonal predictability for SfTC and TfTC frequencies.

ACS Style

Yu-Lin K. Chang; Yasumasa Miyazawa; Swadhin Behera. Role of climate variability in the potential predictability of tropical cyclone formation in tropical and subtropical western North Pacific Ocean. Scientific Reports 2019, 9, 19827 -8.

AMA Style

Yu-Lin K. Chang, Yasumasa Miyazawa, Swadhin Behera. Role of climate variability in the potential predictability of tropical cyclone formation in tropical and subtropical western North Pacific Ocean. Scientific Reports. 2019; 9 (1):19827-8.

Chicago/Turabian Style

Yu-Lin K. Chang; Yasumasa Miyazawa; Swadhin Behera. 2019. "Role of climate variability in the potential predictability of tropical cyclone formation in tropical and subtropical western North Pacific Ocean." Scientific Reports 9, no. 1: 19827-8.

Journal article
Published: 29 November 2019 in Scientific Reports
Reads 0
Downloads 0

Although there have been enormous demands and efforts to develop an early warning system for malaria, no sustainable system has remained. Well-organized malaria surveillance and high-quality climate forecasts are required to sustain a malaria early warning system in conjunction with an effective malaria prediction model. We aimed to develop a weather-based malaria prediction model using a weekly time-series data including temperature, precipitation, and malaria cases from 1998 to 2015 in Vhembe, Limpopo, South Africa and apply it to seasonal climate forecasts. The malaria prediction model performed well for short-term predictions (correlation coefficient, r > 0.8 for 1- and 2-week ahead forecasts). The prediction accuracy decreased as the lead time increased but retained fairly good performance (r > 0.7) up to the 16-week ahead prediction. The demonstration of the malaria prediction process based on the seasonal climate forecasts showed the short-term predictions coincided closely with the observed malaria cases. The weather-based malaria prediction model we developed could be applicable in practice together with skillful seasonal climate forecasts and existing malaria surveillance data. Establishing an automated operating system based on real-time data inputs will be beneficial for the malaria early warning system, and can be an instructive example for other malaria-endemic areas.

ACS Style

Yoonhee Kim; J. V. Ratnam; Takeshi Doi; Yushi Morioka; Swadhin Behera; Ataru Tsuzuki; Noboru Minakawa; Neville Sweijd; Philip Kruger; Rajendra Maharaj; Chisato Imai; Chris Fook Sheng Ng; Yeonseung Chung; Masahiro Hashizume. Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model. Scientific Reports 2019, 9, 1 -10.

AMA Style

Yoonhee Kim, J. V. Ratnam, Takeshi Doi, Yushi Morioka, Swadhin Behera, Ataru Tsuzuki, Noboru Minakawa, Neville Sweijd, Philip Kruger, Rajendra Maharaj, Chisato Imai, Chris Fook Sheng Ng, Yeonseung Chung, Masahiro Hashizume. Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model. Scientific Reports. 2019; 9 (1):1-10.

Chicago/Turabian Style

Yoonhee Kim; J. V. Ratnam; Takeshi Doi; Yushi Morioka; Swadhin Behera; Ataru Tsuzuki; Noboru Minakawa; Neville Sweijd; Philip Kruger; Rajendra Maharaj; Chisato Imai; Chris Fook Sheng Ng; Yeonseung Chung; Masahiro Hashizume. 2019. "Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model." Scientific Reports 9, no. 1: 1-10.

Journal article
Published: 28 October 2019 in Climate
Reads 0
Downloads 0

Most tropical regions in the world are vulnerable to climate variability, given their dependence on rain-fed agricultural production and limited adaptive capacity owing to socio-economic conditions. The Kalahandi, Bolangir, and Koraput districts of the south-western part of Odisha province of India experience an extreme sub-humid tropical climate. Based on the observed changes in the magnitude and distribution of rainfall and temperature, this study evaluates the potential impact of climate variation on agricultural yield and production in these districts. The study is conducted by taking into account meteorological data like rainfall and temperature from 1980 to 2017 and crop productivity data from 1980–81 to 2016–17. Additionally, climate variability indices like Monsoon Index, Oceanic Nino Index, and NINO-3 and NINO 3.4 are used. To analyse the data, various statistical techniques like correlation and multiple linear regression are used. The amount of monsoon rainfall is found to have a significant impact on crop productivity, compared to temperature, in the study area, and as a result the Monsoon Index has a determining impact on crop yield among various indices.

ACS Style

Arpita Panda; Netrananda Sahu; Swadhin Behera; Takahiro Sayama; Limonlisa Sahu; Ram Avtar; R.B. Singh; Masafumi Yamada. Impact of Climate Variability on Crop Yield in Kalahandi, Bolangir, and Koraput Districts of Odisha, India. Climate 2019, 7, 126 .

AMA Style

Arpita Panda, Netrananda Sahu, Swadhin Behera, Takahiro Sayama, Limonlisa Sahu, Ram Avtar, R.B. Singh, Masafumi Yamada. Impact of Climate Variability on Crop Yield in Kalahandi, Bolangir, and Koraput Districts of Odisha, India. Climate. 2019; 7 (11):126.

Chicago/Turabian Style

Arpita Panda; Netrananda Sahu; Swadhin Behera; Takahiro Sayama; Limonlisa Sahu; Ram Avtar; R.B. Singh; Masafumi Yamada. 2019. "Impact of Climate Variability on Crop Yield in Kalahandi, Bolangir, and Koraput Districts of Odisha, India." Climate 7, no. 11: 126.

Journal article
Published: 05 September 2019 in Atmosphere
Reads 0
Downloads 0

Diarrheal disease is one of the leading causes of morbidity and mortality globally, particularly in children under 5 years of age. Factors related to diarrheal disease incidence include infection, malnutrition, and exposure to contaminated water and food. Climate factors also contribute to diarrheal disease. We aimed to explore the relationship between temperature, precipitation and diarrhoea case counts of hospital admissions among vulnerable communities living in a rural setting in South Africa. We applied ‘contour analysis’ to visually examine simultaneous observations in frequencies of anomalously high and low diarrhoea case counts occurring in a season, and assigning colours to differences that were statistically significant based on chi-squared test results. Children under 5 years of age were especially vulnerable to diarrhoea during very dry, hot conditions as well as when conditions were wetter than usual. We saw an anomalously higher number of diarrhoea cases during ‘warmer than usual’ conditions in the dry winter season, with average winter temperatures in Limpopo being from about 5 to 10 °C. As for ‘wetter than usual’ conditions, we saw an anomalously higher number of diarrhoea cases during ‘drier than usual’ conditions for the winter and spring. The lagged association seen in cumulative rainfall could not be distinguished in the same way for temperature-related variables (indicating rainfall had a larger impact on higher cases of diarrhoea), nor for the older age group of 5 years and older. Dry conditions were associated with diarrhoea in children under 5 years of age; such conditions may lead to increased water storage, raising the risks of water contamination. Reduced use of water for personal hygiene and cleaning of outdoor pit latrines also affect sanitation quality. Rural communities require adequate and uninterrupted water provision, and healthcare providers should raise awareness about potential diarrhoeal risks, especially during the dry season as well as during wintertime when conditions are warmer than usual.

ACS Style

Takayoshi Ikeda; Thandi Kapwata; Swadhin K. Behera; Noboru Minakawa; Masahiro Hashizume; Neville Sweijd; Angela Mathee; Caradee Yael Wright. Climatic Factors in Relation to Diarrhoea Hospital Admissions in Rural Limpopo, South Africa. Atmosphere 2019, 10, 522 .

AMA Style

Takayoshi Ikeda, Thandi Kapwata, Swadhin K. Behera, Noboru Minakawa, Masahiro Hashizume, Neville Sweijd, Angela Mathee, Caradee Yael Wright. Climatic Factors in Relation to Diarrhoea Hospital Admissions in Rural Limpopo, South Africa. Atmosphere. 2019; 10 (9):522.

Chicago/Turabian Style

Takayoshi Ikeda; Thandi Kapwata; Swadhin K. Behera; Noboru Minakawa; Masahiro Hashizume; Neville Sweijd; Angela Mathee; Caradee Yael Wright. 2019. "Climatic Factors in Relation to Diarrhoea Hospital Admissions in Rural Limpopo, South Africa." Atmosphere 10, no. 9: 522.

Journal article
Published: 04 September 2019 in Scientific Reports
Reads 0
Downloads 0

Seasonal forecasts of air-temperature generated by numerical models provide guidance to the planners and to the society as a whole. However, generating accurate seasonal forecasts is challenging mainly due to the stochastic nature of the atmospheric internal variability. Therefore, an array of ensemble members is often used to capture the prediction signals. With large spread in the prediction plumes, it becomes important to employ techniques to reduce the effects of unrealistic members. One such technique is to create a weighted average of the ensemble members of seasonal forecasts. In this study, we applied a machine learning technique, viz. a genetic algorithm, to derive optimum weights for the 24-ensemble members of the coupled general circulation model; the Scale Interaction Experiment-Frontier research center for global change version 2 (SINTEX-F2) boreal summer forecasts. Our analysis showed the technique to have significantly improved the 2m-air temperature anomalies over several regions of South America, North America, Australia and Russia compared to the unweighted ensemble mean. The spatial distribution of air temperature anomalies is improved by the GA technique leading to better representation of anomalies in the predictions. Hence, machine learning techniques could help in improving the regional air temperature forecasts over the mid- and high-latitude regions where the model skills are relatively modest.

ACS Style

J. V. Ratnam; H. A. Dijkstra; Takeshi Doi; Yushi Morioka; Masami Nonaka; Swadhin K. Behera. Improving seasonal forecasts of air temperature using a genetic algorithm. Scientific Reports 2019, 9, 1 -11.

AMA Style

J. V. Ratnam, H. A. Dijkstra, Takeshi Doi, Yushi Morioka, Masami Nonaka, Swadhin K. Behera. Improving seasonal forecasts of air temperature using a genetic algorithm. Scientific Reports. 2019; 9 (1):1-11.

Chicago/Turabian Style

J. V. Ratnam; H. A. Dijkstra; Takeshi Doi; Yushi Morioka; Masami Nonaka; Swadhin K. Behera. 2019. "Improving seasonal forecasts of air temperature using a genetic algorithm." Scientific Reports 9, no. 1: 1-11.

Journal article
Published: 25 February 2019 in Scientific Reports
Reads 0
Downloads 0

Potential impact of sea-ice initialization on the interannual climate predictability over the Weddell Sea is investigated using a coupled general circulation model. Climate variability in the Weddell Sea is generally believed to have association with remote forcing such as El Niño-Southern Oscillation and the Southern Annual Mode. However, sea-ice variability in the Weddell Sea has been recently suggested to play additional roles in modulating local atmospheric variability through changes in surface air temperature and near-surface baroclinicity. Reforecast experiments from September 1st, in which the model’s sea-surface temperature (SST) and sea-ice concentration (SIC) are initialized with observations using nudging schemes, show improvements in predicting the observed SIC anomalies in the Weddell Sea up to four months ahead, compared to the other experiments in which only the model’s SST is initialized. During austral spring (Oct–Dec) of lower-than-normal sea-ice years in the Weddell Sea, reforecast experiments with the SST and SIC initializations reasonably predict high surface air temperature anomalies in the Weddell Sea and high sea-level pressure anomalies over the Atlantic sector of the Southern Ocean. These results suggest that accurate initialization of sea-ice conditions during austral winter is necessary for skillful prediction of climate variability over the Weddell Sea during austral spring.

ACS Style

Yushi Morioka; Takeshi Doi; Doroteaciro Iovino; Simona Masina; Swadhin K. Behera. Role of sea-ice initialization in climate predictability over the Weddell Sea. Scientific Reports 2019, 9, 1 -11.

AMA Style

Yushi Morioka, Takeshi Doi, Doroteaciro Iovino, Simona Masina, Swadhin K. Behera. Role of sea-ice initialization in climate predictability over the Weddell Sea. Scientific Reports. 2019; 9 (1):1-11.

Chicago/Turabian Style

Yushi Morioka; Takeshi Doi; Doroteaciro Iovino; Simona Masina; Swadhin K. Behera. 2019. "Role of sea-ice initialization in climate predictability over the Weddell Sea." Scientific Reports 9, no. 1: 1-11.

Preprint content
Published: 11 February 2019
Reads 0
Downloads 0

BackgroundDiarrheal disease is one of the leading causes of morbidity and mortality globally, particularly in children under 5 years of age. Factors related to diarrheal disease incidence include infection, malnutrition, and exposure to contaminated water and food. Climate factors also contribute to diarrheal disease.ObjectivesWe aimed to explore the relationship between temperature, precipitation and diarrhea case counts of hospital admissions among vulnerable communities living in a rural setting in South Africa.MethodsWe applied a novel approach of ‘contour analysis’ to visually examine simultaneous observations in frequencies of anomalously high and low diarrhea case counts occurring in a season and assigning colors to differences that were statistically significant based on chi-squared test results.ResultsThere was a significantly positive difference between high and low ‘groups’ when there was a lack of rain (0 mm of cumulative rain) for 1 to 2 weeks in winter for children under 5.Diarrhea prevalence was greater among children under 5 years when conditions were hotter than usual during winter and spring.DiscussionDry conditions may lead to increased water storage raising the risks of water contamination. Reduced use of water for personal hygiene and cleaning of outdoor pit latrines affect sanitation quality. Rural communities require adequate and uninterrupted water provision and healthcare providers should raise awareness about potential diarrheal risks especially during the dry season.

ACS Style

Takayoshi Ikeda; Thandi Kapwata; Swadhin K. Behera; Noboru Minakawa; Masahiro Hashizume; Neville Sweijd; Angela Mathee; Caradee Yael Wright. Climatic Factors in Relation to Diarrhea for Informed Public Health Decision-Making: A Novel Methodological Approach. 2019, 545046 .

AMA Style

Takayoshi Ikeda, Thandi Kapwata, Swadhin K. Behera, Noboru Minakawa, Masahiro Hashizume, Neville Sweijd, Angela Mathee, Caradee Yael Wright. Climatic Factors in Relation to Diarrhea for Informed Public Health Decision-Making: A Novel Methodological Approach. . 2019; ():545046.

Chicago/Turabian Style

Takayoshi Ikeda; Thandi Kapwata; Swadhin K. Behera; Noboru Minakawa; Masahiro Hashizume; Neville Sweijd; Angela Mathee; Caradee Yael Wright. 2019. "Climatic Factors in Relation to Diarrhea for Informed Public Health Decision-Making: A Novel Methodological Approach." , no. : 545046.

Journal article
Published: 01 February 2019 in Journal of Climate
Reads 0
Downloads 0

This paper explores merits of 100-ensemble simulations from a single dynamical seasonal prediction system by evaluating differences in skill scores between ensembles predictions with few (~10) and many (~100) ensemble members. A 100-ensemble retrospective seasonal forecast experiment for 1983–2015 is beyond current operational capability. Prediction of extremely strong ENSO and the Indian Ocean dipole (IOD) events is significantly improved in the larger ensemble. It indicates that the ensemble size of 10 members, used in some operational systems, is not adequate for the occurrence of 15% tails of extreme climate events, because only about 1 or 2 members (approximately 15% of 12) will agree with the observations. We also showed an ensemble size of about 50 members may be adequate for the extreme El Niño and positive IOD predictions at least in the present prediction system. Even if running a large-ensemble prediction system is quite costly, improved prediction of disastrous extreme events is useful for minimizing risks of possible human and economic losses.

ACS Style

Takeshi Doi; Swadhin K. Behera; Toshio Yamagata. Merits of a 108-Member Ensemble System in ENSO and IOD Predictions. Journal of Climate 2019, 32, 957 -972.

AMA Style

Takeshi Doi, Swadhin K. Behera, Toshio Yamagata. Merits of a 108-Member Ensemble System in ENSO and IOD Predictions. Journal of Climate. 2019; 32 (3):957-972.

Chicago/Turabian Style

Takeshi Doi; Swadhin K. Behera; Toshio Yamagata. 2019. "Merits of a 108-Member Ensemble System in ENSO and IOD Predictions." Journal of Climate 32, no. 3: 957-972.

Preprint content
Published: 09 January 2019
Reads 0
Downloads 0

Malaria poses a great challenge for the maintenance of good public health and sustenance of human wellbeing in many parts of the world. Apparently, the anthropogenic global warming has expanded the spatio-temporal extent of the disease; incidences are now reported beyond tropics and in non-endemic seasons. This emerging trend of climate change has increased the malaria risk factor for millions more across the globe. While global warming remains a key factor to address the future adaptations and mitigation measures, the existing association between climate and malaria prevalence needs careful observations and analyses besides the non-climatic factors. Such a climate association is investigated here with the available malaria case counts in the northeastern districts of South Africa. It is found that the regional variations in seasonal rainfall and temperature, that primarily control mosquito population and thereby infection rates, are linked with a basin-scale climate phenomenon manifested as a dipole pattern in the interannual anomalies of sea surface temperature (SST) of southwestern Indian Ocean. In addition to the year-to-year variations, partly related to the basin warming, a decadal shift in the SST dipole pattern, and associated decrease in seasonal rainfall, leads to decreasing number of case counts in recent years as indicated by the malaria records.

ACS Style

Swadhin Behera; Takayoshi Ikeda; Yushi Morioka; Venkata Ratnam Jayanthi; Takeshi Doi; Masami Nonaka; Ataru Tsuzuki; Chisato Imai; Yoonhee Kim; Masahiro Hashizume; Shingo Iwami; Philip Kruger; Qavanisi Mabunda; Rajendra Maharaj; Neville Sweijd; Noboru Minakawa. A decadal climate shift in the southwest Indian Ocean linked to recent malaria downturn in South Africa. 2019, 1 .

AMA Style

Swadhin Behera, Takayoshi Ikeda, Yushi Morioka, Venkata Ratnam Jayanthi, Takeshi Doi, Masami Nonaka, Ataru Tsuzuki, Chisato Imai, Yoonhee Kim, Masahiro Hashizume, Shingo Iwami, Philip Kruger, Qavanisi Mabunda, Rajendra Maharaj, Neville Sweijd, Noboru Minakawa. A decadal climate shift in the southwest Indian Ocean linked to recent malaria downturn in South Africa. . 2019; ():1.

Chicago/Turabian Style

Swadhin Behera; Takayoshi Ikeda; Yushi Morioka; Venkata Ratnam Jayanthi; Takeshi Doi; Masami Nonaka; Ataru Tsuzuki; Chisato Imai; Yoonhee Kim; Masahiro Hashizume; Shingo Iwami; Philip Kruger; Qavanisi Mabunda; Rajendra Maharaj; Neville Sweijd; Noboru Minakawa. 2019. "A decadal climate shift in the southwest Indian Ocean linked to recent malaria downturn in South Africa." , no. : 1.

Journal article
Published: 01 December 2018 in Journal of Applied Meteorology and Climatology
Reads 0
Downloads 0

In this study, we attempted to forecast the onset of summer rains over South Africa using seasonal precipitation forecasts generated by the Scale Interaction Experiment–Frontier Research Center for Global Change, version 2 (SINTEX-F2), seasonal forecasting system. The precipitation forecasts of the 12-member SINTEX-F2 system, initialized on 1 August and covering the period 1998–2015, were used for the study. The SINTEX-F2 forecast precipitation was also downscaled using dynamical and statistical techniques to improve the spatial and temporal representation of the forecasts. The Weather Research and Forecasting (WRF) Model with two cumulus parameterization schemes was used to dynamically downscale the SINTEX-F2 forecasts. The WRF and SINTEX-F2 precipitation forecasts were corrected for biases using a linear scaling method with a 31-day moving window. The results indicate the onset dates derived from the raw and bias-corrected model precipitation forecasts to have realistic spatial distribution over South Africa. However, the forecast onset dates have root-mean-square errors of more than 30 days over most parts of South Africa except over the northeastern province of Limpopo and over the Highveld region of Mpumalanga province, where the root-mean-square errors are about 10–15 days. The WRF Model with Kain–Fritsch cumulus scheme (bias-corrected SINTEX-F2) has better performance in forecasting the onset dates over Limpopo (the Highveld region) compared to other models, thereby indicating the forecast of onset dates over different regions of South Africa to be model dependent. The results of this study are important for improving the forecast of onset dates over South Africa.

ACS Style

J. V. Ratnam; Takeshi Doi; Willem A. Landman; Swadhin K. Behera. Seasonal Forecasting of Onset of Summer Rains over South Africa. Journal of Applied Meteorology and Climatology 2018, 57, 2697 -2711.

AMA Style

J. V. Ratnam, Takeshi Doi, Willem A. Landman, Swadhin K. Behera. Seasonal Forecasting of Onset of Summer Rains over South Africa. Journal of Applied Meteorology and Climatology. 2018; 57 (12):2697-2711.

Chicago/Turabian Style

J. V. Ratnam; Takeshi Doi; Willem A. Landman; Swadhin K. Behera. 2018. "Seasonal Forecasting of Onset of Summer Rains over South Africa." Journal of Applied Meteorology and Climatology 57, no. 12: 2697-2711.