scholarly journals Current Climate Variability and Future Climate Change: Estimated Growth and Poverty Impacts for Zambia

2012 ◽  
Vol 16 (3) ◽  
pp. 394-411 ◽  
Author(s):  
James Thurlow ◽  
Tingju Zhu ◽  
Xinshen Diao
2018 ◽  
Vol 9 (3) ◽  
pp. 999-1012 ◽  
Author(s):  
Femke J. M. M. Nijsse ◽  
Henk A. Dijkstra

Abstract. One of the approaches to constrain uncertainty in climate models is the identification of emergent constraints. These are physically explainable empirical relationships between a particular simulated characteristic of the current climate and future climate change from an ensemble of climate models, which can be exploited using current observations. In this paper, we develop a theory to understand the appearance of such emergent constraints. Based on this theory, we also propose a classification for emergent constraints, and applications are shown for several idealized climate models.


2018 ◽  
Author(s):  
Femke J. M. M. Nijsse ◽  
Henk A. Dijkstra

Abstract. One of the approaches to constrain uncertainty in climate models is the identification of emergent constraints. These are physically explainable empirical relationships between a particular simulated characteristic of the current climate versus future climate change from an ensemble of climate models, which can be exploited using current observations. In this paper, we develop a theory to understand the appearance of such emergent constraints. Based on this theory, we also propose a classification for emergent constraints and applications are shown for several idealized climate models.


Author(s):  
Rob Marchant

The climatology of East Africa results from the complex interaction between major global convergence zones with more localized regional feedbacks to the climate system; these in turn are moderated by a diverse land surface characterized by coastal to land transitions, high mountains, and large lakes. The main climatic character of East Africa, and how this varies across the region, takes the form of seasonal variations in rainfall that can fall as one, two, or three rainy seasons, the times and duration of which will be determined by the interplay between major convergence zones with more localized regional feedbacks. One of the key characteristics of East Africa are climatic variations with altitude as climates change along an altitudinal gradient that can extend from hot, dry, “tropical” conditions to cool, wet, temperate conditions and on the highest mountains “polar” climates with permanent ice caps. With this complex and variable climate landscape of the present, as scientists move through time to explore past climatic variability, it is apparent there have been a series of relatively rapid and high-magnitude environmental shifts throughout East Africa, particularly characterized by changing hydrological budgets. How climate change has impacted on ecosystems, and how those ecosystems have responded and interacted with human populations, can be unearthed by drawing on evidence from the sedimentary and archaeological record of the past six thousand years. As East African economies, and the livelihoods of millions of people in the region, have been clearly heavily affected by climate variability in the past, so it is expected that future climate variability will impact on ecosystem functioning and the preparedness of communities for future climate change.


2008 ◽  
Vol 7 (Suppl 2) ◽  
pp. S4 ◽  
Author(s):  
Stephanie K Moore ◽  
Vera L Trainer ◽  
Nathan J Mantua ◽  
Micaela S Parker ◽  
Edward A Laws ◽  
...  

2014 ◽  
Vol 15 (5) ◽  
pp. 2085-2103 ◽  
Author(s):  
Guoyong Leng ◽  
Qiuhong Tang

Abstract Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China.


Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
Christian Franzke ◽  
Naiming Yuan

Most climate variability is organized by a simple principle—scaling laws—allowing us to understand past and future climate change.


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