scholarly journals Potential for long-range regional precipitation prediction over India

MAUSAM ◽  
2021 ◽  
Vol 52 (1) ◽  
pp. 47-56
Author(s):  
NEELIMA A. SONTAKKE ◽  
DENNIS J. SHEA ◽  
ROLAND A. MADDEN ◽  
RICHARD W. KATZ
Keyword(s):  
Long Range ◽  
Spatial Scales ◽  
Monsoon Season ◽  
Regional Scale ◽  
Climate Signal ◽  
Precipitation Prediction ◽  
Northwest India ◽  
Sw Monsoon ◽  
Climate Noise ◽  
Long Range Prediction

The potential for long-range precipitation prediction over the Indian monsoon region is generally good where climate noise (i.e., variability due to daily weather fluctuations) is small as compared to the climate signal (i.e., variability due to year to year fluctuations in monthly/seasonal means) being in the tropical belt. In order to understand the potential on smaller spatial scales, the ratios of inter-annual variability to that associated with climate noise have been computed for precipitation of four seasons as well as SW monsoon sub-seasons/months over 1656 stations in the Indian subcontinent.   Precipitation in SW monsoon has been found potentially predictable on seasonal as well as intra-seasonal scale. The west coast and contiguous northwest India, part of the 'northeast India are more predictable. Potential for long-range prediction over northwest India is highest during the active monsoon period from July to September. Over eastern peninsula potential for prediction is generally found low whereas over north-central India it is always moderate. Over northern latitudes precipitation due to western disturbances during January to May is potentially predictable. Precipitation over southeast India and Sri Lanka during October to February due to northeast (NE) monsoon shows good potential for long-range prediction. It is manifested that long-range precipitation forecasting schemes for SW monsoon season, sub-seasons and months and for the other seasons over India on point to regional scale have good scope by taking into account the potential predictability at the individual stations as well as at contiguous resemblance areas over the country.

scholarly journals Setting the Flow Accumulation Threshold Based on Environmental and Morphologic Features to Extract River Networks from Digital Elevation Models

2021 ◽  
Vol 10 (3) ◽  
pp. 186
Author(s):  
HuiHui Zhang ◽  
Hugo A. Loáiciga ◽  
LuWei Feng ◽  
Jing He ◽  
QingYun Du
Keyword(s):  
Spatial Scales ◽  
Digital Elevation Models ◽  
Regional Scale ◽  
Drainage Density ◽  
River Network ◽  
Landscape Patterns ◽  
Estimation Methods ◽  
River Networks ◽  
Flow Accumulation ◽  
Digital Elevation

Determining the flow accumulation threshold (FAT) is a key task in the extraction of river networks from digital elevation models (DEMs). Several methods have been developed to extract river networks from Digital Elevation Models. However, few studies have considered the geomorphologic complexity in the FAT estimation and river network extraction. Recent studies estimated influencing factors’ impacts on the river length or drainage density without considering anthropogenic impacts and landscape patterns. This study contributes two FAT estimation methods. The first method explores the statistical association between FAT and 47 tentative explanatory factors. Specifically, multi-source data, including meteorologic, vegetation, anthropogenic, landscape, lithology, and topologic characteristics are incorporated into a drainage density-FAT model in basins with complex topographic and environmental characteristics. Non-negative matrix factorization (NMF) was employed to evaluate the factors’ predictive performance. The second method exploits fractal geometry theory to estimate the FAT at the regional scale, that is, in basins whose large areal extent precludes the use of basin-wide representative regression predictors. This paper’s methodology is applied to data acquired for Hubei and Qinghai Provinces, China, from 2001 through 2018 and systematically tested with visual and statistical criteria. Our results reveal key local features useful for river network extraction within the context of complex geomorphologic characteristics at relatively small spatial scales and establish the importance of properly choosing explanatory geomorphologic characteristics in river network extraction. The multifractal method exhibits more accurate extracting results than the box-counting method at the regional scale.

scholarly journals Large but decreasing effect of ozone on the European carbon sink

2018 ◽  
Vol 15 (13) ◽  
pp. 4245-4269 ◽  
Author(s):  
Rebecca J. Oliver ◽  
Lina M. Mercado ◽  
Stephen Sitch ◽  
David Simpson ◽  
Belinda E. Medlyn ◽  
...  
Keyword(s):  
Carbon Storage ◽  
Primary Productivity ◽  
Carbon Sink ◽  
Spatial Scales ◽  
Stomatal Closure ◽  
Regional Scale ◽  
Surface Model ◽  
Background Concentrations ◽  
Tropospheric O3 ◽  
The Impact

Abstract. The capacity of the terrestrial biosphere to sequester carbon and mitigate climate change is governed by the ability of vegetation to remove emissions of CO2 through photosynthesis. Tropospheric O3, a globally abundant and potent greenhouse gas, is, however, known to damage plants, causing reductions in primary productivity. Despite emission control policies across Europe, background concentrations of tropospheric O3 have risen significantly over the last decades due to hemispheric-scale increases in O3 and its precursors. Therefore, plants are exposed to increasing background concentrations, at levels currently causing chronic damage. Studying the impact of O3 on European vegetation at the regional scale is important for gaining greater understanding of the impact of O3 on the land carbon sink at large spatial scales. In this work we take a regional approach and update the JULES land surface model using new measurements specifically for European vegetation. Given the importance of stomatal conductance in determining the flux of O3 into plants, we implement an alternative stomatal closure parameterisation and account for diurnal variations in O3 concentration in our simulations. We conduct our analysis specifically for the European region to quantify the impact of the interactive effects of tropospheric O3 and CO2 on gross primary productivity (GPP) and land carbon storage across Europe. A factorial set of model experiments showed that tropospheric O3 can suppress terrestrial carbon uptake across Europe over the period 1901 to 2050. By 2050, simulated GPP was reduced by 4 to 9 % due to plant O3 damage and land carbon storage was reduced by 3 to 7 %. The combined physiological effects of elevated future CO2 (acting to reduce stomatal opening) and reductions in O3 concentrations resulted in reduced O3 damage in the future. This alleviation of O3 damage by CO2-induced stomatal closure was around 1 to 2 % for both land carbon and GPP, depending on plant sensitivity to O3. Reduced land carbon storage resulted from diminished soil carbon stocks consistent with the reduction in GPP. Regional variations are identified with larger impacts shown for temperate Europe (GPP reduced by 10 to 20 %) compared to boreal regions (GPP reduced by 2 to 8 %). These results highlight that O3 damage needs to be considered when predicting GPP and land carbon, and that the effects of O3 on plant physiology need to be considered in regional land carbon cycle assessments.

scholarly journals Palaeogeographic controls on climate and proxy interpretation

2016 ◽  
Vol 12 (5) ◽  
pp. 1181-1198 ◽  
Author(s):  
Daniel J. Lunt ◽  
Alex Farnsworth ◽  
Claire Loptson ◽  
Gavin L. Foster ◽  
Paul Markwick ◽  
...  
Keyword(s):  
Global Change ◽  
Carbon Cycle ◽  
Ocean Circulation ◽  
General Circulation ◽  
Regional Scale ◽  
Circulation Model ◽  
Adjustment Factor ◽  
Climate Signal ◽  
Proxy Records ◽  
Global Mean

Abstract. During the period from approximately 150 to 35 million years ago, the Cretaceous–Paleocene–Eocene (CPE), the Earth was in a “greenhouse” state with little or no ice at either pole. It was also a period of considerable global change, from the warmest periods of the mid-Cretaceous, to the threshold of icehouse conditions at the end of the Eocene. However, the relative contribution of palaeogeographic change, solar change, and carbon cycle change to these climatic variations is unknown. Here, making use of recent advances in computing power, and a set of unique palaeogeographic maps, we carry out an ensemble of 19 General Circulation Model simulations covering this period, one simulation per stratigraphic stage. By maintaining atmospheric CO2 concentration constant across the simulations, we are able to identify the contribution from palaeogeographic and solar forcing to global change across the CPE, and explore the underlying mechanisms. We find that global mean surface temperature is remarkably constant across the simulations, resulting from a cancellation of opposing trends from solar and palaeogeographic change. However, there are significant modelled variations on a regional scale. The stratigraphic stage–stage transitions which exhibit greatest climatic change are associated with transitions in the mode of ocean circulation, themselves often associated with changes in ocean gateways, and amplified by feedbacks related to emissivity and planetary albedo. We also find some control on global mean temperature from continental area and global mean orography. Our results have important implications for the interpretation of single-site palaeo proxy records. In particular, our results allow the non-CO2 (i.e. palaeogeographic and solar constant) components of proxy records to be removed, leaving a more global component associated with carbon cycle change. This “adjustment factor” is used to adjust sea surface temperatures, as the deep ocean is not fully equilibrated in the model. The adjustment factor is illustrated for seven key sites in the CPE, and applied to proxy data from Falkland Plateau, and we provide data so that similar adjustments can be made to any site and for any time period within the CPE. Ultimately, this will enable isolation of the CO2-forced climate signal to be extracted from multiple proxy records from around the globe, allowing an evaluation of the regional signals and extent of polar amplification in response to CO2 changes during the CPE. Finally, regions where the adjustment factor is constant throughout the CPE could indicate places where future proxies could be targeted in order to reconstruct the purest CO2-induced temperature change, where the complicating contributions of other processes are minimised. Therefore, combined with other considerations, this work could provide useful information for supporting targets for drilling localities and outcrop studies.

scholarly journals Are Distribution Patterns Correlated with Plant Traits?

2021 ◽  
Author(s):  
◽  
Benjamin Magana-Rodriguez
Keyword(s):  
Life History ◽  
Leaf Area ◽  
Spatial Patterns ◽  
Life History Traits ◽  
Multiple Scales ◽  
Spatial Scales ◽  
Regional Scale ◽  
Distribution Patterns ◽  
Spatial Arrangement ◽  
Scaling Relationship

<p>The current crisis in loss of biodiversity requires rapid action. Knowledge of species' distribution patterns across scales is of high importance in determining their current status. However, species display many different distribution patterns on multiple scales. A positive relationship between regional (broad-scale) distribution and local abundance (fine-scale) of species is almost a constant pattern in macroecology. Nevertheless interspecific relationships typically contain much scatter. For example, species that possess high local abundance and narrow ranges, or species that are widespread, but locally rare. One way to describe these spatial features of distribution patterns is by analysing the scaling properties of occupancy (e.g., aggregation) in combination with knowledge of the processes that are generating the specific spatial pattern (e.g., reproduction, dispersal, and colonisation). The main goal of my research was to investigate if distribution patterns correlate with plant life-history traits across multiple scales. First, I compared the performance of five empirical models for their ability to describe the scaling relationship of occupancy in two datasets from Molesworth Station, New Zealand. Secondly, I analysed the association between spatial patterns and life history traits at two spatial scales in an assemblage of 46 grassland species in Molesworth Station. The spatial arrangement was quantified using the parameter k from the Negative Binomial Distribution (NBD). Finally, I investigated the same association between spatial patterns and life-history traits across local, regional and national scales, focusing in one of the most diverse families of plant species in New Zealand, the Veronica sect. Hebe (Plantaginaceae). The spatial arrangement was investigated using the mass fractal dimension. Cross-species correlations and phylogenetically independent contrasts were used to investigate the relationships between plant life-history traits and spatial patterns on both data bases. There was no superior occupancy-area model overall for describing the scaling relationship, however the results showed that a variety of occupancy-area models can be fit to different data sets at diverse spatial scales using nonlinear regression. Additionally, here I showed that it is possible to deduce and extrapolate information on occupancy at fine scales from coarse-scale data. For the 46 plantassemblage in Molesworth Station, Specific leaf area (SLA) exhibits a positive association with aggregation in cross-species analysis, while leaf area showed a negative association, and dispersule mass a positive correlation with degree of aggregation in phylogenetic contrast analysis at a local-scale (20 × 20 m resolution). Plant height was the only life-history trait that was associated with degree of aggregation at a regional-scale (100 × 60 mresolution). For the Veronica sect. Hebe dataset, leaf area showed a positive correlation with aggregation while specific leaf area showed a negative correlation with aggregation at a fine local-scale (2.5-60 m resolution). Inflorescence length, breeding system and leaf area showed a negative correlation with degree of aggregation at a regional-scale (2.5-20 km resolution). Height was positively associated with aggregation at national-scale (20-100 km resolution). Although life-history traits showed low predictive ability in explaining aggregation throughout this thesis, there was a general pattern about which processes and traits were important at different scales. At local scales traits related to dispersal and completion such as SLA , leaf area, dispersule mass and the presence of structures in seeds for dispersal, were important; while at regional scales traits related to reproduction such as breeding system, inflorescence length and traits related to dispersal (seed mass) were significant. At national scales only plant height was important in predicting aggregation. Here, it was illustrated how the parameters of these scaling models capture an important aspect of spatial pattern that can be related to other macroecological relationships and the life-history traits of species. This study shows that when several scales of analysis are considered, we can improve our understanding about the factors that are related to species' distribution patterns.</p>

scholarly journals Consistent predictors of microbial community composition across scales in grasslands reveal low context-dependency

2021 ◽  
Author(s):  
Dajana Radujković ◽  
Sara Vicca ◽  
Margaretha van Rooyen ◽  
Peter Wilfahrt ◽  
Leslie Brown ◽  
...  
Keyword(s):  
Microbial Community ◽  
Community Composition ◽  
Spatial Scales ◽  
Regional Scale ◽  
Microbial Community Composition ◽  
Soil Microbial Communities ◽  
Plant Productivity ◽  
Context Dependency ◽  
Fungal Community Composition ◽  
Soil Microbial

Environmental circumstances shaping soil microbial communities have been studied extensively, but due to disparate study designs it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 sampled across regional plant productivity gradients) to examine i) if the same abiotic or biotic factors predict both large- and regional-scale patterns in bacterial and fungal community composition, and ii) if microbial community composition differs consistently with regional plant productivity (low vs high) across different sites. We found that there is high congruence between predictors of microbial community composition across spatial scales; bacteria were predominantly associated with soil properties and fungi with plant community composition. Moreover, there was a microbial community signal that clearly distinguished high and low productivity soils that was shared across worldwide distributed grasslands suggesting that microbial assemblages vary predictably depending on grassland productivity.

New Analog Experiment for Convergent Regime an example of planet Mercury

2021 ◽  
Author(s):  
Sinan Özeren ◽  
A. M. Celal Şengör ◽  
Dursun Acar ◽  
M. Nazmi Postacıoğlu ◽  
Christian Klimczak ◽  
...  
Keyword(s):  
Coherent Structures ◽  
Spatial Scales ◽  
Regional Scale ◽  
Homogeneous Case ◽  
Thrust Faulting ◽  
Slip Planes ◽  
Series Of Experiments ◽  
Analog Experiment ◽  
Stress Patterns ◽  
Cohesive Material

&lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;p&gt;We conduct a series of experiments to understand the nature of thrust faulting as a result of global thermal contraction in planetary bodies such as Mercury. The spatial scales and patterns of faulting due to contraction are still not very well understood. However, the problem is complicated even for the homogeneous case where the crustal thickness and material properties do not vary spatially. Previous research showed that the thrust faulting patterns are non-random and are arranged in long systems. This is probably due to the regional-scale stress patterns interacting with each other, leading to the creation of coherent structures. We first conduct 1-Axis experiments where we simulate the contraction of the substratum using an elastic ribbon. On top of this we place the material for which the friction, cohesion and thickness can be controlled for each experiment. The shared interface between the frictional-cohesive material and the shortening elastic substratum dictates undulations and finally the generation of slip planes in the upper layer. We discuss the spatial distribution of these patterns spatially. We then speculate the interaction of such patterns on a 2D plane.&lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt; &lt;div&gt;&amp;#160;&lt;/div&gt; &lt;/div&gt;&lt;div&gt; &lt;div&gt;&amp;#160;&lt;/div&gt; &lt;/div&gt;

scholarly journals Evaluating impacts of bottom trawling and hypoxia on benthic communities at the local, habitat, and regional scale using a modelling approach

2019 ◽  
Vol 77 (1) ◽  
pp. 278-289 ◽  
Author(s):  
P D van Denderen ◽  
S G Bolam ◽  
R Friedland ◽  
J G Hiddink ◽  
K Norén ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Spatial Scales ◽  
Benthic Communities ◽  
Regional Scale ◽  
The Baltic Sea ◽  
Benthic Habitats ◽  
Bottom Trawling ◽  
Management Actions ◽  
The Baltic ◽  
Local Habitat

Abstract Bottom trawling disturbance and hypoxia are affecting marine benthic habitats worldwide. We present an approach to predict their effects on benthic communities, and use the approach to estimate the state, the biomass relative to carrying capacity, of the Baltic Sea at the local, habitat, and regional scale. Responses to both pressures are expected to depend on the longevity of fauna, which is predicted from benthic data from 1558 locations. We find that communities in low-salinity regions mostly consist of short-lived species, which are, in our model, more resilient than those of the saline areas. The model predicts that in 14% of the Baltic Sea region benthic biomass is reduced by at least 50%, whereas an additional 8% of the region has reductions of 10–50%. The effects of hypoxia occur over larger spatial scales and lead to a low state of especially deep habitats. The approach is based on a simple characterization of the benthic community, which comes with high uncertainty, but allows for the identification of benthic habitats that are at greatest risk and prioritization of management actions at the regional scale. This information supports the development of sustainable approaches to manage impact of human activities on benthic ecosystems.

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