scholarly journals The impact of climate variability on tobacco productivity over Temanggung Regency, Indonesia

2019 ◽  
Vol 76 ◽  
pp. 04003 ◽  
Author(s):  
Andi Syahid Muttaqin ◽  
Utia Suarma ◽  
Emilya Nurjani ◽  
Faricha Kurniadhini ◽  
Ratna Prabaningrum ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Climate Variability ◽  
Climate Adaptation ◽  
Southern Oscillation ◽  
Daily Rainfall ◽  
Ideal Condition ◽  
Crop Failure ◽  
Leaf Quality ◽  
Tobacco Cultivation ◽  
The Impact

Indonesia is among the most affected regions by climate variability and change. Located between the Pacific and the Indian Ocean, Indonesia is mostly influenced by some climate variabilities, such as the monsoon, El-Nino Southern Oscillation (ENSO), and Indian Ocean Dipole (IOD). These climate variabilities affect significantly on the Indonesian rainfall that further increase the chances of crop failure, specifically on the tobacco yield over Temanggung Regency which is known as the producer of good quality tobacco in Indonesia. Tobacco needs a sufficient dry condition prior to the harvest stage due to maintains its productivity and leaf quality. This ideal condition could be achieved when the dry season, typically in the mid of the year for Temanggung, is not affected by any wet climate variability. Moreover, based on this study, it was found that there was the most remarkable decline in tobacco productivity in 2016 since the required dry condition was interrupted by the prolonged significant rainfall which depicted by strong mid-year negative-IOD indices. The analysis utilized the dataset of tobacco productivity, daily rainfall intensity, and the indices of monsoon, ENSO, and IOD for the period of seven years, from 2010– 2016. This study concludes that the climate variabilities give a huge contribution to the profitable tobacco cultivation. Furthermore, efforts to adapt and to mitigate the impacts of the climate variability in Indonesia, specifically for the agriculture sector, is needed by way of increasing the various stakeholder's knowledge that involved in policy planning and decision-making as well as involving the farmers in the training on climate adaptation and mitigation.

scholarly journals Tree-ring-based spring precipitation reconstruction in the Sikhote-Alin' Mountain range

2021 ◽  
Vol 17 (2) ◽  
pp. 951-967
Author(s):  
Olga Ukhvatkina ◽  
Alexander Omelko ◽  
Dmitriy Kislov ◽  
Alexander Zhmerenetsky ◽  
Tatyana Epifanova ◽  
...  
Keyword(s):  
Climate Variability ◽  
Tree Ring ◽  
Southern Oscillation ◽  
Russian Far East ◽  
Pinus Koraiensis ◽  
Mountain Range ◽  
Korean Pine ◽  
Sikhote Alin ◽  
The Impact ◽  
Standard Tree

Abstract. Climate reconstructions provide important insight into past climate variability and help us to understand the large-scale climate drivers and impact of climate change. However, our knowledge about long-term year-to-year climate variability is still limited due to the lack of high-resolution reconstructions. Here, we present the first precipitation reconstructions based on tree rings from Pinus koraiensis (Korean pine) from three sites placed along a latitudinal (330 km) gradient in the Sikhote-Alin' mountains in the Russian Far East. The tree-ring width chronologies were built using standard tree-ring procedures. We reconstructed the April–June precipitation for the southern Sikhote-Alin' (SSA), March–June precipitation for the central Sikhote-Alin' (CSA) and March–July precipitation for the northwestern Sikhote-Alin' (NSA) over the years 1602 to 2013, 1804 to 2009 and 1858 to 2013, respectively. We found that an important limiting factor for Korean pine growth was precipitation within the period when the air current coming from the continent during the cold period is replaced with the impact of the wet ocean air current. We identified that common wet years for SSA, CSA and NSA occurred in 1805, 1853, 1877, 1903, 1906, 1927, 1983 and 2009 and common dry years occurred in 1821, 1869, 1919, 1949 and 2003. Our reconstructions have 3-, 15- and 60-year periods, which suggests the influence of the El Niño–Southern Oscillation and Pacific Decadal Oscillation on the region's climate and relevant processes. Despite the impact of various global processes, the main contribution to precipitation formation in the study area is still made by the Pacific Ocean, which determines their amount and periodicity.

scholarly journals Ubiquity of human-induced changes in climate variability

2021 ◽  
Vol 12 (4) ◽  
pp. 1393-1411
Author(s):  
Keith B. Rodgers ◽  
Sun-Seon Lee ◽  
Nan Rosenbloom ◽  
Axel Timmermann ◽  
Gokhan Danabasoglu ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Climate Adaptation ◽  
Southern Oscillation ◽  
System Modeling ◽  
Greenhouse Warming ◽  
Earth System ◽  
Wide Range ◽  
State Changes ◽  
Mean State

Abstract. While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño–Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher-order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850–2100 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming in the model alters variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and assessing potential stressors for terrestrial and marine ecosystems.

Recent Atmospheric Variability at Kibo Summit, Kilimanjaro, and Its Relation to Climate Mode Activity

2018 ◽  
Vol 31 (10) ◽  
pp. 3875-3891 ◽  
Author(s):  
Emily Collier ◽  
Thomas Mölg ◽  
Tobias Sauter
Keyword(s):  
Indian Ocean ◽  
Current Knowledge ◽  
Southern Oscillation ◽  
Strong Association ◽  
Atmospheric Modeling ◽  
High Mountain ◽  
Atmospheric Variability ◽  
Rain Season ◽  
The Indian Ocean ◽  
The Impact

Abstract Accurate knowledge of the impact of internal atmospheric variability is required for the detection and attribution of climate change and for interpreting glacier records. However, current knowledge of such impacts in high-mountain regions is largely based on statistical methods, as the observational data required for process-based assessments are often spatially or temporally deficient. Using a case study of Kilimanjaro, 12 years of convection-permitting atmospheric modeling are combined with an 8-yr observational record to evaluate the impact of climate oscillations on recent high-altitude atmospheric variability during the short rains (the secondary rain season in the region). The focus is on two modes that have a well-established relationship with precipitation during this season, El Niño–Southern Oscillation and the Indian Ocean zonal mode, and demonstrate their strong association with local and mesoscale conditions at Kilimanjaro. Both oscillations correlate positively with humidity fluctuations, but the association is strongest with the Indian Ocean zonal mode in the air layers near and above the glaciers because of changes in zonal circulation and moisture transport, emphasizing the importance of the moisture signal from this basin. However, the most anomalous conditions are found during co-occurring positive events because of the combined effects of the (i) extended positive sea surface temperature anomalies, (ii) enhanced atmospheric moisture capacity from higher tropospheric temperatures, (iii) most pronounced weakening of the subsiding branch of the Indian Ocean Walker circulation over East Africa, and (iv) stronger monsoonal moisture fluxes upstream from Kilimanjaro. This study lays the foundation for unraveling the contribution of climate modes to observed changes in Kilimanjaro’s glaciers.

Impact of Indo-Pacific Feedback Interactions on ENSO Dynamics Diagnosed Using Ensemble Climate Simulations

2012 ◽  
Vol 25 (21) ◽  
pp. 7743-7763 ◽  
Author(s):  
A. Santoso ◽  
M. H. England ◽  
W. Cai
Keyword(s):  
Indian Ocean ◽  
Climate Model ◽  
Southern Oscillation ◽  
Ocean Basin ◽  
Climate Feedback ◽  
Enso Events ◽  
Thermocline Feedback ◽  
Enso Dynamics ◽  
The Indian Ocean ◽  
The Impact

The impact of Indo-Pacific climate feedback on the dynamics of El Niño–Southern Oscillation (ENSO) is investigated using an ensemble set of Indian Ocean decoupling experiments (DCPL), utilizing a millennial integration of a coupled climate model. It is found that eliminating air–sea interactions over the Indian Ocean results in various degrees of ENSO amplification across DCPL simulations, with a shift in the underlying dynamics toward a more prominent thermocline mode. The DCPL experiments reveal that the net effect of the Indian Ocean in the control runs (CTRL) is a damping of ENSO. The extent of this damping appears to be negatively correlated to the coherence between ENSO and the Indian Ocean dipole (IOD). This type of relationship can arise from the long-lasting ENSO events that the model simulates, such that developing ENSO often coincides with Indian Ocean basin-wide mode (IOBM) anomalies during non-IOD years. As demonstrated via AGCM experiments, the IOBM enhances western Pacific wind anomalies that counteract the ENSO-enhancing winds farther east. In the recharge oscillator framework, this weakens the equatorial Pacific air–sea coupling that governs the ENSO thermocline feedback. Relative to the IOBM, the IOD is more conducive for ENSO growth. The net damping by the Indian Ocean in CTRL is thus dominated by the IOBM effect which is weaker with stronger ENSO–IOD coherence. The stronger ENSO thermocline mode in DCPL is consistent with the absence of any IOBM anomalies. This study supports the notion that the Indian Ocean should be viewed as an integral part of ENSO dynamics.

scholarly journals An Asymmetry in the IOD and ENSO Teleconnection Pathway and Its Impact on Australian Climate

2012 ◽  
Vol 25 (18) ◽  
pp. 6318-6329 ◽  
Author(s):  
Wenju Cai ◽  
Peter van Rensch ◽  
Tim Cowan ◽  
Harry H. Hendon
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Wave Train ◽  
Austral Spring ◽  
Southeast Australia ◽  
Unit Change ◽  
The Impact ◽  
Sst Anomalies

Abstract Recent research has shown that the climatic impact from El Niño–Southern Oscillation (ENSO) on middle latitudes west of the western Pacific (e.g., southeast Australia) during austral spring (September–November) is conducted via the tropical Indian Ocean (TIO). However, it is not clear whether this impact pathway is symmetric about the positive and negative phases of ENSO and the Indian Ocean dipole (IOD). It is shown that a strong asymmetry does exist. For ENSO, only the impact from El Niño is conducted through the TIO pathway; the impact from La Niña is delivered through the Pacific–South America pattern. For the IOD, a greater convection anomaly and wave train response occurs during positive IOD (pIOD) events than during negative IOD (nIOD) events. This “impact asymmetry” is consistent with the positive skewness of the IOD, principally due to a negative skewness of sea surface temperature (SST) anomalies in the east IOD (IODE) pole. In the IODE region, convection anomalies are more sensitive to a per unit change of cold SST anomalies than to the same unit change of warm SST anomalies. This study shows that the IOD skewness occurs despite the greater damping, rather than due to a breakdown of this damping as suggested by previous studies. This IOD impact asymmetry provides an explanation for much of the reduction in spring rainfall over southeast Australia during the 2000s. Key to this rainfall reduction is the increased occurrences of pIOD events, more so than the lack of nIOD events.

scholarly journals Ubiquity of human-induced changes in climate variability

2021 ◽  
Author(s):  
Keith B. Rodgers ◽  
Sun-Seon Lee ◽  
Nan Rosenbloom ◽  
Axel Timmermann ◽  
Gokhan Danabasoglu ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Climate Adaptation ◽  
Southern Oscillation ◽  
System Modeling ◽  
Greenhouse Warming ◽  
Earth System ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Mean State

Abstract. While climate change mitigation targets necessarily concern maximum mean state change, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño-Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability, distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming will in particular alter variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and for assessing potential stressors for terrestrial and marine ecosystems.

scholarly journals Influence of Natural Climate Variability on Extreme Wave Power over Indo-Pacific Ocean Assessed using ERA5

2021 ◽  
Author(s):  
Prashant Kumar ◽  
Sukhwinder Kaur ◽  
Evan Weller ◽  
Ian R. Young
Keyword(s):  
Pacific Ocean ◽  
Indian Ocean ◽  
Climate Variability ◽  
El Niño ◽  
El Nino ◽  
Extreme Value Analysis ◽  
Wave Power ◽  
Central Pacific ◽  
Natural Climate ◽  
The Impact

Abstract In recent decades, wave power (WP) energy from the ocean is one of the cleanest renewable energy sources associated with oceanic warming. In Indo-Pacific Ocean, the WP is significantly influenced by natural climate variabilities, such as El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO). In this study, the impact of major climate variability modes on seasonal extreme WP is examined over the period 1979–2019 using ERA5 reanalysis data and the non-stationary generalized extreme value analysis is applied to estimate the climatic extremes. Independent ENSO influence after removing the IOD trends (ENSO|IOD) on WP are evident over the eastern and central Pacific during December–February (DJF) and March–May (MAM), respectively, which subsequently shifts towards the western Pacific in June–August (JJA) and September–November (SON). The ENSO|PDO impact on WP exhibits similar yet weaker intensity year round compared to ENSO. Extreme WP responses due to the IOD|ENSO include widespread decreases over the tropical and eastern Indian Ocean (IO), with localized increases only over the South China and Philippine (SCP) seas and Bay of Bengal (BOB) during JJA, and the Arabian Sea during SON. Lastly, for the PDO|ENSO, the significant increases in WP are mostly confined to the Pacific, and most prominent in the North Pacific. Composite analysis of different phase combinations of PDO (IOD) with El Niño (La Niña) reveals stronger (weaker) influences year-round. The response patterns in significant wave height (SWH), peak wave period (PWP), sea surface temperatures (SST), and sea level pressure (SLP) helps to explain the seasonal variations in WP.

The Impact of Spatial Soil Variability on Simulation of Regional Maize Yield

2017 ◽  
Vol 60 (6) ◽  
pp. 2137-2148 ◽  
Author(s):  
Vaishali Sharda ◽  
Cameron Handyside ◽  
Bernardo Chaves ◽  
Richard T. McNider ◽  
Gerrit Hoogenboom
Keyword(s):  
Climate Variability ◽  
Soil Properties ◽  
Crop Yield ◽  
Climatic Factors ◽  
Southern Oscillation ◽  
Climatic Variability ◽  
Maize Yield ◽  
Soil Variability ◽  
Large Variability ◽  
The Impact

Abstract. The study of climate variability and its impacts on crop production has become a continuous effort for the scientific community over the past two decades. However, the impact of spatial soil variability along with climatic factors on crop yield remains uncertain. The objective of this study was to determine the impact of soil and climatic variability on maize yield. We used Alabama as a case study because the agriculture is predominantly rainfed and there is a large variability in growing season precipitation due to the influence of climate variability signals such as the El Niño Southern Oscillation (ENSO). The cropping system model CERES-Maize of the Decision Support System for Agrotechnology Transfer (DSSAT) was used to simulate growth, development, and grain yield for maize for the top ten maize-producing counties in Alabama under rainfed conditions during dry and wet ENSO years. Maize yield simulations were compared for one prominent agricultural soil in each county, the top three prominent agricultural soils in each county, and spatially distributed SSURGO soils in each county. Simulated yields were then compared with maize yields reported by the National Agricultural Statistical Services (NASS). The simulation results showed that maize yield was impacted by both climate variability and spatial soil variability. Statistical relationships were established between crop yield, yield changes, and soil properties. This simulation study established the clear importance of soil variability in crop-climate impact studies. Keywords: Crop Modeling, DSSAT, Database, Soil properties, Spatial variability.

scholarly journals Impact of Indo-Pacific Climate Variability on Rice Productivity in Bihar, India

2020 ◽  
Vol 12 (17) ◽  
pp. 7023 ◽  
Author(s):  
Netrananda Sahu ◽  
Atul Saini ◽  
Swadhin Behera ◽  
Takahiro Sayama ◽  
Sridhara Nayak ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Climate Variability ◽  
Southern Oscillation Index ◽  
Partial Correlation ◽  
Southern Oscillation ◽  
Maximum Temperature ◽  
Climate Indices ◽  
Rice Productivity ◽  
Pacific Climate Variability ◽  
The Impact

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).

Diverse impacts of Indian Ocean Dipole on El Niño-Southern Oscillation

2021 ◽  
pp. 1-46
Author(s):  
Lei Zhang ◽  
Weiqing Han ◽  
Gerald A. Meehl ◽  
Aixue Hu ◽  
Nan Rosenbloom ◽  
...  
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
Indian Ocean Dipole ◽  
El Nino ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
The Impact ◽  
The Tropical Pacific

AbstractUnderstanding the impact of the Indian Ocean Dipole (IOD) on El Niño-Southern Oscillation (ENSO) is important for climate prediction. By analyzing observational data and performing Indian and Pacific Ocean pacemaker experiments using a state-of-the-art climate model, we find that a positive IOD (pIOD) can favor both cold and warm sea surface temperature anomalies (SSTA) in the tropical Pacific, in contrast to the previously identified pIOD-El Niño connection. The diverse impacts of the pIOD on ENSO are related to SSTA in the Seychelles-Chagos thermocline ridge (SCTR; 60°E-85°E and 7°S-15°S) as part of the warm pole of the pIOD. Specifically, a pIOD with SCTR warming can cause warm SSTA in the southeast Indian Ocean, which induces La Niña-like conditions in the tropical Pacific through interbasin interaction processes associated with a recently identified climate phenomenon dubbed the “Warm Pool Dipole”. This study identifies a new pIOD-ENSO relationship and examines the associated mechanisms.

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