Typological bottlenecks: How large-scale regional language typologies help us interpret global prehistory

2016 ◽  
Vol 20 (3) ◽  
Author(s):  
Roger Blench

AbstractIt is unlikely that local or highly specific typological characteristics of language correlate with other aspects of human culture and history. However, at regional scale, the broad typology of languages does reflect bottlenecks. The paper argues that these regions of high typological similarity are due neither to chance nor long-term convergence, but reflect the initial conditions of settlement. This suggests that regions can be characterised by negative typology, i.e., the absence of globally common traits. Conversely, typological uniformity occurs in mainland Southeast Asia, a region notable for the similarities between language structures. An expansion of the remit of typology can uncover large regional patterns which can be tied to the archaeological narrative of the early expansion of modern humans.

2008 ◽  
Vol 73 (2) ◽  
pp. 200-226 ◽  
Author(s):  
Lisa Kealhofer ◽  
Peter Grave

Debates about the development of political complexity and cities are typically focused on material cultural correlates and situated within the wider context of the emergence of states. Conventionally, state emergence is linked to agricultural surpluses and a new phase of agricultural intensification. However, this approach remains fundamentally reliant on the preservation of an appropriate and diverse suite of material cultural correlates. For mainland Southeast Asia, archaeological correlates of early political complexity are comparatively impoverished and are dominated by evidence from disparate burial contexts and architecture. In this paper, we employ an alternative approach based on a case study from north central Thailand that uses paleoenvironmental evidence of land use. These data are then related to historical urban development in the region. We suggest that large-scale patterns of agricultural expansion relate directly to increases in political complexity. Our results demonstrate that the long-term development of large-scale agricultural landscapes in this region predates the earliest evidence of monumental cities in central Thailand. We conclude that significant progress in better understanding the emergence of complex societies, both in Southeast Asia and elsewhere, is unlikely to be possible without more systematic integration of archaeological and paleoenvironmental approaches.


2017 ◽  
Vol 18 (5) ◽  
pp. 1227-1245 ◽  
Author(s):  
Edwin Sumargo ◽  
Daniel R. Cayan

Abstract This study investigates the spatial and temporal variability of cloudiness across mountain zones in the western United States. Daily average cloud albedo is derived from a 19-yr series (1996–2014) of half-hourly Geostationary Operational Environmental Satellite (GOES) images. During springtime when incident radiation is active in driving snowmelt–runoff processes, the magnitude of daily cloud variations can exceed 50% of long-term averages. Even when aggregated over 3-month periods, cloud albedo varies by ±10% of long-term averages in many locations. Rotated empirical orthogonal functions (REOFs) of daily cloud albedo anomalies over high-elevation regions of the western conterminous United States identify distinct regional patterns, wherein the first five REOFs account for ~67% of the total variance. REOF1 is centered over Northern California and Oregon and is pronounced between November and March. REOF2 is centered over the interior northwest and is accentuated between March and July. Each of the REOF/rotated principal components (RPC) modes associates with anomalous large-scale atmospheric circulation patterns and one or more large-scale teleconnection indices (Arctic Oscillation, Niño-3.4, and Pacific–North American), which helps to explain why anomalous cloudiness patterns take on regional spatial scales and contain substantial variability over seasonal time scales.


2020 ◽  
Vol 117 (16) ◽  
pp. 8757-8763 ◽  
Author(s):  
Ji Nie ◽  
Panxi Dai ◽  
Adam H. Sobel

Responses of extreme precipitation to global warming are of great importance to society and ecosystems. Although observations and climate projections indicate a general intensification of extreme precipitation with warming on global scale, there are significant variations on the regional scale, mainly due to changes in the vertical motion associated with extreme precipitation. Here, we apply quasigeostrophic diagnostics on climate-model simulations to understand the changes in vertical motion, quantifying the roles of dry (large-scale adiabatic flow) and moist (small-scale convection) dynamics in shaping the regional patterns of extreme precipitation sensitivity (EPS). The dry component weakens in the subtropics but strengthens in the middle and high latitudes; the moist component accounts for the positive centers of EPS in the low latitudes and also contributes to the negative centers in the subtropics. A theoretical model depicts a nonlinear relationship between the diabatic heating feedback (α) and precipitable water, indicating high sensitivity of α (thus, EPS) over climatological moist regions. The model also captures the change of α due to competing effects of increases in precipitable water and dry static stability under global warming. Thus, the dry/moist decomposition provides a quantitive and intuitive explanation of the main regional features of EPS.


Land ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 29 ◽  
Author(s):  
Martin Jepsen ◽  
Matilda Palm ◽  
Thilde Bruun

Mainland Southeast Asia (MSA) has seen sweeping upland land use changes in the past decades, with transition from primarily subsistence shifting cultivation to annual commodity cropping. This transition holds implications for local upland communities and ecosystems. Due to its particular political regime, Myanmar is at the tail of this development. However, with Myanmar’s official strategy of agricultural commercialization and intensification, recent liberalization of the national economy, and influx of multinational agricultural companies, the effects on upland land transitions could come fast. We analyze the current state of upland land use in Myanmar in a socio-economic and political context, identify the dynamics in three indicator commodity crops (maize, cassava, and rubber), and discuss the state driven economic, tenurial and policy reforms that have occurred in upland areas of mainland Southeast Asian countries in past decades. We draw on these insights to contextualize our study and hypothesize about possible transition pathways for Myanmar. The transition to annual commodity cropping is generally driven by a range of socio-economic and technical factors. We find that land use dynamics for the three indicator crops are associated with market demand and thus the opening of national Southeast-Asian economies, research and development of locally suitable high yielding varieties (HYVs), and subsidies for the promotion of seeds and inputs. In contrast, promotion of HYVs in marginal areas and without adequate agricultural extension services may results in agricultural contraction and yield dis-intensification. The environmental impacts of the transition depend on the transition pathway, e.g., through large-scale plantation projects or smallholder initiatives. The agricultural development in upland MSA follows a clear diffusion pattern with transition occurring first in Thailand, spreading to Vietnam, Cambodia and Laos. While these countries point to prospects for Myanmar, we hypothesize that changes will come slow due to Myanmar’s sparse rural infrastructure, with uncertainty about tenure, in particular in areas still troubled by armed conflicts, and unwillingness of international investors to approach Myanmar given the recent setbacks to the democratization process.


2021 ◽  
Vol 34 (3) ◽  
pp. 949-965
Author(s):  
Edward Blanchard-Wrigglesworth ◽  
Lettie A. Roach ◽  
Aaron Donohoe ◽  
Qinghua Ding

AbstractAntarctic sea ice extent (SIE) has slightly increased over the satellite observational period (1979 to the present) despite global warming. Several mechanisms have been invoked to explain this trend, such as changes in winds, precipitation, or ocean stratification, yet there is no widespread consensus. Additionally, fully coupled Earth system models run under historic and anthropogenic forcing generally fail to simulate positive SIE trends over this time period. In this work, we quantify the role of winds and Southern Ocean SSTs on sea ice trends and variability with an Earth system model run under historic and anthropogenic forcing that nudges winds over the polar regions and Southern Ocean SSTs north of the sea ice to observations from 1979 to 2018. Simulations with nudged winds alone capture the observed interannual variability in SIE and the observed long-term trends from the early 1990s onward, yet for the longer 1979–2018 period they simulate a negative SIE trend, in part due to faster-than-observed warming at the global and hemispheric scale in the model. Simulations with both nudged winds and SSTs show no significant SIE trends over 1979–2018, in agreement with observations. At the regional scale, simulated sea ice shows higher skill compared to the pan-Antarctic scale both in capturing trends and interannual variability in all nudged simulations. We additionally find negligible impact of the initial conditions in 1979 on long-term trends.


2015 ◽  
Vol 11 (6) ◽  
pp. 5307-5343 ◽  
Author(s):  
T. A. Räsänen ◽  
V. Lindgren ◽  
J. H. A. Guillaume ◽  
B. M. Buckley ◽  
M. Kummu

Abstract. The variability in the hydroclimate over mainland Southeast Asia is strongly influenced by the El Niño–Southern Oscillation (ENSO) phenomenon, which has been linked to severe drought and floods that profoundly influence human societies and ecosystems alike. However, the spatial characteristics and long-term stationarity of ENSO's influence in the region are not well understood. We thus aim to analyse seasonal evolution and spatial variations in the effect of ENSO on precipitation over the period of 1980–2013, and long-term variation in the ENSO-teleconnection using tree-ring derived Palmer Drought Severity Indices (PDSI) that span from 1650–2004. We found that the majority of the study area is under the influence of ENSO, which has affected the region's hydroclimate over the majority (96 %) of the 355 year study period. Our results further indicate that there is a pattern of seasonal evolution of precipitation anomalies during ENSO. However, considerable variability in the ENSO's influence is revealed: the strength of ENSO's influence was found to vary in time and space, and the different ENSO events resulted in varying precipitation anomalies. Additional research is needed to investigate how this variation in ENSO teleconnection is influenced by other factors, such as the properties of the ENSO events and other ocean and atmospheric phenomena. In general, the high variability we found in ENSO teleconnection combined with limitations of current knowledge, suggests that the adaptation to extremes in hydroclimate in mainland Southeast Asia needs to go beyond "predict-and-control" and recognise both uncertainty and complexity as fundamental principles.


2020 ◽  
Author(s):  
Thomas Ulrich ◽  
Alice-Agnes Gabriel ◽  
Elizabeth Madden

Megathrust faults host the largest earthquakes on Earth which can trigger cascading hazards such as devastating tsunamis.Determining characteristics that control subduction zone earthquake and tsunami dynamics is critical to mitigate megathrust hazards, but is impeded by structural complexity, large spatio-temporal scales, and scarce or asymmetric instrumental coverage.Here we show that tsunamigenesis and earthquake dynamics are controlled by along-arc variability in regional tectonic stresses together with depth-dependent variations in rigidity and yield strength of near-fault sediments. We aim to identify dominant regional factors controlling megathrust hazards. To this end, we demonstrate how to unify and verify the required initial conditions for geometrically complex, multi-physics earthquake-tsunami modeling from interdisciplinary geophysical observations. We present large-scale computational models of the 2004 Sumatra-Andaman earthquake and Indian Ocean tsunami that reconcile near- and far-field seismic, geodetic, geological, and tsunami observations and reveal tsunamigenic trade-offs between slip to the trench, splay faulting, and bulk yielding of the accretionary wedge.Our computational capabilities render possible the incorporation of present and emerging high-resolution observations into dynamic-rupture-tsunami models. Our findings highlight the importance of regional-scale structural heterogeneity to decipher megathrust hazards.


2021 ◽  
Author(s):  
Christopher ODell ◽  
Annmarie Eldering ◽  
Michael Gunson ◽  
David Crisp ◽  
Brendan Fisher ◽  
...  

<p>While initial plans for measuring carbon dioxide from space hoped for 1-2 ppm levels of accuracy (bias) and precision in the CO<sub>2</sub> column mean dry air mole fraction (XCO<sub>2</sub>), in the past few years it has become clear that accuracies better than 0.5 ppm are required for most current science applications.  These include measuring continental (1000+ km) and regional scale (100s of km) surface fluxes of CO<sub>2</sub> at monthly-average timescales.  Considering the 400+ ppm background, this translates to an accuracy of roughly 0.1%, an incredibly challenging target to hit. </p><p>Improvements in both instrument calibration and retrieval algorithms have led to significant improvements in satellite XCO<sub>2</sub> accuracies over the past decade.  The Atmospheric Carbon Observations from Space (ACOS) retrieval algorithm, including post-retrieval filtering and bias correction, has demonstrated unprecedented accuracy with our latest algorithm version as applied to the Orbiting Carbon Observatory-2 (OCO-2) satellite sensor.   This presentation will discuss the performance of the v10 XCO<sub>2</sub> product by comparisons to TCCON and models, and showcase its performance with some recent examples, from the potential to infer large-scale fluxes to its performance on individual power plants.  The v10 product yields better agreement with TCCON over land and ocean, plus reduced biases over tropical oceans and desert areas as compared to a median of multiple global carbon inversion models, allowing better accuracy and faith in inferred regional-scale fluxes.  More specifically, OCO-2 has single sounding precision of ~0.8 ppm over land and ~0.5 ppm over water, and RMS biases of 0.5-0.7 ppm over both land and water.  Given the six-year and growing length of the OCO-2 data record, this also enables new studies on carbon interannual variability, while at the same time allowing identification of more subtle and temporally-dependent errors.  Finally, we will discuss the prospects of future improvements in the next planned version (v11), and the long-term prospects of greenhouse gas retrievals in the coming years. </p><p> </p>


Author(s):  
Teddy Lazebnik ◽  
Svetlana Bunimovich-Mendrazitsky ◽  
Leonid Shaikhet

We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the SIR-type epidemiological model that we developed for viral diseases with long-term immunity memory pandemic. This is a large-scale model containing 15 nonlinear ODE equations, and classical methods have failed to analytically obtain its equilibria. The proposed method is used to conduct a comprehensive analysis by a stochastic representation of the dynamics of the model, followed by finding all asymptotic stable equilibrium states of the model for any values of parameters and initial conditions.


2016 ◽  
Vol 12 (9) ◽  
pp. 1889-1905 ◽  
Author(s):  
Timo A. Räsänen ◽  
Ville Lindgren ◽  
Joseph H. A. Guillaume ◽  
Brendan M. Buckley ◽  
Matti Kummu

Abstract. The variability of the hydroclimate over mainland Southeast Asia is strongly influenced by the El Niño–Southern Oscillation (ENSO), which has been linked to severe droughts and floods that profoundly influence human societies and ecosystems alike. Although the significance of ENSO is well understood, there are still limitations in the understanding of its effects on hydroclimate, particularly with regard to understanding the spatio-temporal characteristics and the long-term variation of its effects. Therefore we analysed the seasonal evolution and spatial variations in the effect of ENSO on precipitation over the period of 1980–2013 and the long-term variation in the ENSO teleconnection using tree-ring-derived Palmer drought severity indices (PDSIs) for the March–May season that span over the time period 1650–2004. The analyses provided an improved understanding of the seasonal evolution of the precipitation anomalies during ENSO events. The effects of ENSO were found to be most consistent and expressed over the largest areal extents during March–May of the year when the ENSO events decay. On a longer timescale, we found that ENSO has affected the region's March–May hydroclimate over the majority (95 %) of the 355-year study period and that during half (52 %) of the time ENSO caused a significant increase in hydroclimatic variability. The majority of the extremely wet and dry March–May seasons also occurred during ENSO events. However, considerable variability in ENSO's influence was revealed: the spatial pattern of precipitation anomalies varied between individual ENSO events, and the strength of ENSO's influence was found to vary through time. Given the high variability in ENSO teleconnection that we described and the limitations of the current understanding of the effects of ENSO, we suggest that the adaptation to ENSO-related extremes in hydroclimate over mainland Southeast Asia needs to recognise uncertainty as an inherent part of adaptation, must go beyond "predict and control", and should seek adaptation opportunities widely within society.


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