scholarly journals Potential volcanic impacts on future climate variability

2017 ◽  
Vol 7 (11) ◽  
pp. 799-805 ◽  
Author(s):  
Ingo Bethke ◽  
Stephen Outten ◽  
Odd Helge Otterå ◽  
Ed Hawkins ◽  
Sebastian Wagner ◽  
...  
Keyword(s):  
Climate Variability ◽  
Future Climate ◽  
Volcanic Impacts

scholarly journals Responses of runoff to historical and future climate variability over China

2017 ◽  
Author(s):  
Chuanhao Wu ◽  
Bill X. Hu ◽  
Guoru Huang ◽  
Peng Wang ◽  
Kai Xu
Keyword(s):  
Climate Variability ◽  
Arid Regions ◽  
Southern China ◽  
Aridity Index ◽  
Global Climate Models ◽  
Future Climate ◽  
Western China ◽  
Climate Projections ◽  
Positive Contribution ◽  
The Mean

Abstract. China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960–2012) water budget data and climate projections from 28 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.2 to 3.3) and potential evaporation (PET) elasticity (from −2.3 to −0.2) across China. The P elasticity is larger in northeast and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960–2012, the climate contribution to R ranges from −2.4 % a−1 to 3.3 % a−1 across China, with the negative contribution in the North China plain and the positive contribution in western China and some parts of the southwest. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071–2100, the mean annual P will likely increase in most parts of China, especially the western regions, while the mean annual PET will likely increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China will likely become wetter and drier in the period 2071–2100, respectively (relative to the baseline 1971–2000).

scholarly journals Evaluating the Yield Response of Maize (Zea mays L.) and Rice (Oryza sativa L.) to Future Climate Variability in The Gambia

2019 ◽  
Vol 7 (2) ◽  
pp. 11
Author(s):  
Ebrima Sonko ◽  
Sampson K. Agodzo ◽  
Philip Antwi-Agyei
Keyword(s):  
Climate Variability ◽  
Rice Yield ◽  
Oryza Sativa L ◽  
Maize Yield ◽  
Future Climate ◽  
Yield Response ◽  
Climate Data ◽  
Negative Effects ◽  
Yield Data ◽  
Maize Cultivars

Climate change and variability impact on staple food crops present a daunting challenge in the 21st century. The study assesses future climate variability on maize and rice yield over a 30-year period by comparing the outcomes under two GCM models, namely, CSIRO_RCP4.5 and NOAA_RCP4.5 of Australia’s Commonwealth Scientific and National Oceanic and Atmospheric Administration respectively. Historical climate data and yield data were used to establish correlations and then subsequently used to project future yields between 2021 and 2050. Using the average yield data for the period 1987-2016 as baseline yield data, future yield predictions for 2021-2030, 2031-2040 and 2041-2050 were then compared with the baseline data. The results showed that the future maize and rice yield would be vulnerable to climate variability with CSIRO_RCP4.5 showing increase in maize yield whilst CSIRO_RCP4.5 gives a better projection for rice yield. Furthermore, the results estimated the percentage mean yield gain for maize under CSIRO_RCP4.5 and NOAA_ RCP4.5 by about 17 %, 31 % and 48 % for the period 2021-2030, 2031-2040 and 2041-2050 respectively. Mean rice yield lossess of -23 %, -19 % and -23 % were expected for the same period respectively. The study recommended the use of improved rice and maize cultivars to offset the negative effects of climate variability in future.

Interactions of the Indian Ocean climate with other tropical oceans

2020 ◽  
Author(s):  
Matthieu Lengaigne ◽  
Keyword(s):  
Indian Ocean ◽  
Climate Variability ◽  
Future Climate ◽  
Future Climate Change ◽  
The Pacific ◽  
Ocean Atmosphere ◽  
The Indian Ocean ◽  
The Tropics ◽  
Modes Of Climate Variability ◽  
The Tropical Pacific

<p>Ocean-atmosphere interactions in the tropics have a profound influence on the climate system. El Niño–Southern Oscillation (ENSO), which is spawned in the tropical Pacific, is the most prominent and well-known year-to-year variation on Earth. Its reach is global, and its impacts on society and the environment are legion. Because ENSO is so strong, it can excite other modes of climate variability in the Indian Ocean by altering the general circulation of the atmosphere. However, ocean-atmosphere interactions internal to the Indian Ocean are capable of generating distinct modes of climate variability as well. Whether the Indian Ocean can feedback onto Atlantic and Pacific climate has been an on-going matter of debate. We are now beginning to realize that the tropics, as a whole, are a tightly inter-connected system, with strong feedbacks from the Indian and Atlantic Oceans onto the Pacific. These two-way interactions affect the character of ENSO and Pacific decadal variability and shed new light on the recent hiatus in global warming.</p><p>Here we review advances in our understanding of pantropical interbasins climate interactions with the Indian Ocean and their implications for both climate prediction and future climate projections. ENSO events force changes in the Indian Ocean than can feed back onto the Pacific. Along with reduced summer monsoon rainfall over the Indian subcontinent, a developing El Niño can trigger a positive Indian Ocean Dipole (IOD) in fall and an Indian Ocean Basinwide (IOB) warming in winter and spring. Both IOD and IOB can feed back onto ENSO. For example, a positive IOD can favor the onset of El Niño, and an El Niño–forced IOB can accelerate the demise of an El Niño and its transition to La Niña. These tropical interbasin linkages however vary on decadal time scales. Warming during a positive phase of Atlantic Multidecadal Variability over the past two decades has strengthened the Atlantic forcing of the Indo-Pacific, leading to an unprecedented intensification of the Pacific trade winds, cooling of the tropical Pacific, and warming of the Indian Ocean. These interactions forced from the tropical Atlantic were largely responsible for the recent hiatus in global surface warming.</p><p>Climate modeling studies to address these issues are unfortunately compromised by pronounced systematic errors in the tropics that severely suppress interactions with the Indian and Pacific Oceans. As a result, there could be considerable uncertainty in future projections of Indo-Pacific climate variability and the background conditions in which it is embedded. Projections based on the current generation of climate models suggest that Indo-Pacific mean-state changes will involve slower warming in the eastern than in the western Indian Ocean. Given the presumed strength of the Atlantic influence on the pantropics, projections of future climate change could be substantially different if systematic model errors in the Atlantic were corrected. There is hence tremendous potential for improving seasonal to decadal climate predictions and for improving projections of future climate change in the tropics though advances in our understanding of the dynamics that govern interbasin linkages.</p>

scholarly journals Future climate variability impacts on potential erosion and soil organic carbon in European croplands

2014 ◽  
Vol 11 (1) ◽  
pp. 1561-1585 ◽  
Author(s):  
M. van der Velde ◽  
J. Balkovič ◽  
C. Beer ◽  
N. Khabarov ◽  
M. Kuhnert ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Climate Variability ◽  
Future Climate ◽  
Climate Data ◽  
Climate Trend ◽  
Erosion Rates ◽  
Soc Stock ◽  
The Impact ◽  
Earth System Models

Abstract. We investigate the impact of future climate variability on the potential vulnerability of soils to erosion and the consequences for soil organic carbon (SOC) in European croplands. Soil erosion is an important carbon flux not characterized in Earth System Models. We use a~European implementation of EPIC, driven by reference climate data (CNTRL), and climate data with reduced variability (REDVAR). Whether erosion regimes will change across European cropland depends on the spatial conjunction of expected changes in climate variability and physiographic conditions conducive to erosion. We isolated the effect of erosion by performing simulations with and without erosion. Median CNTRL and REDVAR erosion rates equalled 14.4 and 9.1 ton ha−1, and 19.1 and 9.7, for 1981–2010 and 2071–2100, respectively. The total amount of carbon lost from European cropland due to erosion was estimated at 769 Tg C for 1981–2010 (from a total storage of 6197 Tg C without erosion) under CNTRL climate. Climate trend impacts reduce the European cropland SOC stock by 578 Tg C without – and by 683 Tg C with erosion, from 1981 to 2100. Climate variability compounds these impacts and decreases the stock by an estimated 170 Tg without erosion and by 314 Tg C with erosion, by the end of the century. Future climate variability and erosion will thus compound impacts on SOC stocks arising from gradual climate change alone.

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