scholarly journals Climate variability rather than overstocking causes recent large scale cover changes of Tibetan pastures

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
L. W. Lehnert ◽  
K. Wesche ◽  
K. Trachte ◽  
C. Reudenbach ◽  
J. Bendix
2021 ◽  
Author(s):  
Bin Yu ◽  
Xuebin Zhang ◽  
Guilong Li ◽  
Wei Yu

Abstract A recent study of future changes in global wind power using an ensemble of ten CMIP5 climate simulations indicated an interhemispheric asymmetry of wind power changes over the 21st century, featured by power decreases across the Northern Hemisphere mid-latitudes and increases across the tropics and subtropics of the Southern Hemisphere. Here we analyze future global projections of surface mean and extreme winds by means of a single-model initial-condition 50-member ensemble of climate simulations generated with CanESM5, the Canadian model participated in CMIP6. We analyze the ensemble mean and spread of boreal winter mean and extreme wind trends over the next half-century (2021-2070) and explore the contribution of internal climate variability to these trends. Surface wind speed is projected to mostly decrease in northern mid-low latitudes and southern mid-latitudes and increase in northern high latitudes and southern tropical and subtropical regions, with considerable regional variations. Large ensemble spreads are apparent, especially with remarkable differences over northern parts of South America and northern Russia. The interhemispheric asymmetry of wind projections is found in most ensemble members, and can be related to large-scale changes in surface temperature and atmospheric circulation. The extreme wind has similar structure of future projections, whereas its reductions tend to be more consistent over northern mid-latitudes. The projected mean and extreme wind changes are attributed to changes in both externally anthropogenic forced and internal climate variability generated components. The spread in wind projections is partially due to large-scale atmospheric circulation variability.


2021 ◽  
Author(s):  
Danielle Udy ◽  
Tessa Vance ◽  
Anthony Kiem ◽  
Neil Holbrook ◽  
Mark Curran

<p>Weather systems in the southern Indian Ocean drive synoptic-scale precipitation, temperature and wind variability in East Antarctica, sub-Antarctic islands and southern Australia.  Over seasonal to decadal timescales, the mean condition associated with combinations of these synoptic weather patterns (e.g., extratropical cyclones, fronts and regions of high pressure) is often referred to as variability in the westerly wind belt or the Southern Annular Mode (SAM). The westerly wind belt is generally considered to be zonally symmetric around Antarctica however, on a daily timescale this is not the case. To capture the daily variability of regional weather systems, we used synoptic typing (Self-Organising Maps) to group weather patterns based on similar features, which are often lost when using monthly or seasonal mean fields. We identified nine key regional weather types based on anomaly pattern and strength. These include four meridional nodes, three mixed nodes, one zonal node and one transitional node. The meridional nodes are favourable for transporting warm, moist air masses to the subantarctic and Antarctic region, and are associated with increased precipitation and temperature where the systems interact with the Antarctic coastline.  These nodes have limited association with the SAM, especially during austral spring.  In contrast, the zonal and mixed nodes were strongly correlated with the SAM however, the regional synoptic representation of SAM positive conditions is not zonally symmetric and is represented by three separate nodes.  These different types of SAM positive conditions mean that the commonly used hemispheric Marshall index often fails to capture the regional variability in surface weather conditions in the southern Indian Ocean. Our results show the importance of considering different synoptic set ups of SAM conditions, particularly SAM positive, and identify conditions that are potentially missed by SAM variability (e.g., extreme precipitation events). Our results are particularly important to consider when interpreting SAM or westerly wind belt reconstructions in the study region (from ice cores, tree rings, or lake sediments).  Here we present a case study using the synoptic typing results to enhance our understanding of the Law Dome (East Antarctica) ice core record, focussing on links to large scale modes of climate variability and Australian hydroclimate.  These results enhance the usefulness of ice core proxies in coastal East Antarctica and assist with determining where and how it is appropriate to use coastal East Antarctic ice core records for reconstructions of large scale modes of climate variability (e.g. SAM and ENSO) and remote hydroclimate conditions.</p>


2012 ◽  
Vol 70 (2) ◽  
pp. 319-328 ◽  
Author(s):  
Antoni Quetglas ◽  
Francesc Ordines ◽  
Manuel Hidalgo ◽  
Sebastià Monserrat ◽  
Susana Ruiz ◽  
...  

Abstract Quetglas, A., Ordines, F., Hidalgo, M., Monserrat, S., Ruiz, S., Amores, Á., Moranta, J., and Massutí, E. 2013. Synchronous combined effects of fishing and climate within a demersal community. – ICES Journal of Marine Science, 70: 319–328. Accumulating evidence shows that fishing exploitation and environmental variables can synergistically affect the population dynamics of exploited populations. Here, we document an interaction between fishing impact and climate variability that triggered a synchronic response in the population fluctuations of six exploited species in the Mediterranean from 1965–2008. Throughout this period, the fishing activity experienced a sharp increase in fishing effort, which caused all stocks to shift from an early period of underexploitation to a later period of overexploitation. This change altered the population resilience of the stocks and brought about an increase in the sensitivity of its dynamics to climate variability. Landings increased exponentially when underexploited but displayed an oscillatory behaviour once overexploited. Climatic indices, related to the Mediterranean mesoscale hydrography and large-scale north Atlantic climatic variability, seemed to affect the species with broader age structure and longer lifespan, while the global-scale El Niño Southern Oscillation index (ENSO) positively influenced the population abundances of species with a narrow age structure and short lifespan. The species affected by ENSO preferentially inhabit the continental shelf, suggesting that Mediterranean shelf ecosystems are sensitive to the hydroclimatic variability linked to global climate.


Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 374 ◽  
Author(s):  
Taereem Kim ◽  
Ju-Young Shin ◽  
Hanbeen Kim ◽  
Sunghun Kim ◽  
Jun-Haeng Heo

Climate variability is strongly influencing hydrological processes under complex weather conditions, and it should be considered to forecast reservoir inflow for efficient dam operation strategies. Large-scale climate indices can provide potential information about climate variability, as they usually have a direct or indirect correlation with hydrologic variables. This study aims to use large-scale climate indices in monthly reservoir inflow forecasting for considering climate variability. For this purpose, time series and artificial intelligence models, such as Seasonal AutoRegressive Integrated Moving Average (SARIMA), SARIMA with eXogenous variables (SARIMAX), Artificial Neural Network (ANN), Adaptive Neural-based Fuzzy Inference System (ANFIS), and Random Forest (RF) models were employed with two types of input variables, autoregressive variables (AR-) and a combination of autoregressive and exogenous variables (ARX-). Several statistical methods, including ensemble empirical mode decomposition (EEMD), were used to select the lagged climate indices. Finally, monthly reservoir inflow was forecasted by SARIMA, SARIMAX, AR-ANN, ARX-ANN, AR-ANFIS, ARX-ANFIS, AR-RF, and ARX-RF models. As a result, the use of climate indices in artificial intelligence models showed a potential to improve the model performance, and the ARX-ANN and AR-RF models generally showed the best performance among the employed models.


2019 ◽  
Vol 116 (52) ◽  
pp. 26444-26449
Author(s):  
Kimberly L. Oremus

Climate change is already affecting fish productivity and distributions worldwide, yet its impact on fishing labor has not been examined. Here I directly link large-scale climate variability with fishery employment by studying the effects of sea-surface pressure changes in the North Atlantic region, whose waters are among the world’s fastest warming. I find that climate shocks reduce not only regional catch and revenue in the New England fishing sector, but also ultimately county-level wages and employment among commercial harvesters. Each SD increase from the climatic mean decreases county-level fishing employment by 13%, on average. The South Atlantic region serves as a control due to its different ecological response to climate. Overall, I estimate that climate variability from 1996 to 2017 is responsible for a 16% (95% CI: 10% to 22%) decline in county-level fishing employment in New England, beyond the changes in employment attributable to management or other factors. This quantitative evidence linking climate variability and fishing labor has important implications for management in New England, which employs 20% of US commercial harvesters. Because the results are mediated by the local biology and institutions, they cannot be directly extrapolated to other regions. But they show that climate can impact fishing outcomes in ways unaccounted by management and offer a template for study of this relationship in fisheries around the world.


Radiocarbon ◽  
2014 ◽  
Vol 56 (04) ◽  
pp. S61-S68
Author(s):  
Ramzi Touchan ◽  
David M. Meko ◽  
Kevin J. Anchukaitis

Dendroclimatology in the Eastern Mediterranean (EM) region has made important contributions to the understanding of climate variability on timescales of decades to centuries. These contributions, beginning in the mid-20th century, have value for resource management, archaeology, and climatology. A gradually expanding tree-ring network developed by the first author over the past 15 years has been the framework for some of the most important recent advances in EM dendroclimatology. The network, now consisting of 79 sites, has been widely applied in large-scale climatic reconstruction and in helping to identify drivers of climatic variation on regional to global spatial scales. This article reviews EM dendroclimatology and highlights contributions on the national and international scale.


2010 ◽  
Vol 23 (11) ◽  
pp. 2902-2915 ◽  
Author(s):  
Xuebin Zhang ◽  
Jiafeng Wang ◽  
Francis W. Zwiers ◽  
Pavel Ya Groisman

Abstract The generalized extreme value (GEV) distribution is fitted to winter season daily maximum precipitation over North America, with indices representing El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the North Atlantic Oscillation (NAO) as predictors. It was found that ENSO and PDO have spatially consistent and statistically significant influences on extreme precipitation, while the influence of NAO is regional and is not field significant. The spatial pattern of extreme precipitation response to large-scale climate variability is similar to that of total precipitation but somewhat weaker in terms of statistical significance. An El Niño condition or high phase of PDO corresponds to a substantially increased likelihood of extreme precipitation over a vast region of southern North America but a decreased likelihood of extreme precipitation in the north, especially in the Great Plains and Canadian prairies and the Great Lakes/Ohio River valley.


2014 ◽  
Vol 27 (13) ◽  
pp. 5119-5131 ◽  
Author(s):  
Katinka Bellomo ◽  
Amy Clement ◽  
Thorsten Mauritsen ◽  
Gaby Rädel ◽  
Bjorn Stevens

This study examines the influence of the northeast and southeast Pacific subtropical stratocumulus cloud regions on the modes of Pacific climate variability simulated by an atmospheric general circulation model (ECHAM6) coupled to a slab ocean. The sensitivity of cloud liquid water to underlying SST is changed in the radiation module of the atmospheric model to increase the strength of positive low-cloud feedback in the two regions. Enhanced low-cloud feedback increases the persistence and variance of the leading modes of climate variability at decadal and longer time scales. Additional integrations show that the southeast Pacific influences climate variability in the equatorial ENSO region, whereas the effects of the northeast Pacific remain confined to the North Pacific. The results herein suggest that a positive feedback among SST, cloud cover, and large-scale atmospheric circulation can explain decadal climate variability in the Pacific Ocean. In particular, cloud feedbacks over the subtropical stratocumulus regions set the time scale of climate variability. A proper representation of low-level cloud feedbacks in the subtropical stratocumulus regions could therefore improve the simulation of Pacific climate variability.


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