Dependence of Large-Scale Precipitation Climatologies on Temporal and Spatial Sampling

The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.

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A Potential of microRNAs for High-Content Screening

Journal of Nucleic Acids ◽

10.4061/2011/870903 ◽

2011 ◽

Vol 2011 ◽

pp. 1-15 ◽

Cited By ~ 9

Author(s):

Andrius Serva ◽

Christoph Claas ◽

Vytaute Starkuviene

Keyword(s):

Large Scale ◽

Cellular Processes ◽

Comprehensive Knowledge ◽

Functional Models ◽

Rapid Accumulation ◽

Health And Disease ◽

Temporal And Spatial ◽

And Function ◽

Functional Analyses ◽

Immense Potential

In the last years miRNAs have increasingly been recognised as potent posttranscriptional regulators of gene expression. Possibly, miRNAs exert their action on virtually any biological process by simultaneous regulation of numerous genes. The importance of miRNA-based regulation in health and disease has inspired research to investigate diverse aspects of miRNA origin, biogenesis, and function. Despite the recent rapid accumulation of experimental data, and the emergence of functional models, the complexity of miRNA-based regulation is still far from being well understood. In particular, we lack comprehensive knowledge as to which cellular processes are regulated by which miRNAs, and, furthermore, how temporal and spatial interactions of miRNAs to their targets occur. Results from large-scale functional analyses have immense potential to address these questions. In this review, we discuss the latest progress in application of high-content and high-throughput functional analysis for the systematic elucidation of the biological roles of miRNAs.

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Influence of Stratospheric Sudden Warming on AIRS Midtropospheric CO2

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-13-064.1 ◽

2013 ◽

Vol 70 (8) ◽

pp. 2566-2573 ◽

Cited By ~ 10

Author(s):

Xun Jiang ◽

Jingqian Wang ◽

Edward T. Olsen ◽

Thomas Pagano ◽

Luke L. Chen ◽

...

Keyword(s):

Large Scale ◽

Principal Component ◽

Department Of Energy ◽

Atmospheric Infrared Sounder ◽

Stratospheric Sudden Warming ◽

Chemical Tracers ◽

Before And After ◽

Temporal And Spatial ◽

Global Reanalysis ◽

Height Data

Abstract Midtropospheric CO2 retrievals from the Atmospheric Infrared Sounder (AIRS) were used to explore the influence of stratospheric sudden warming (SSW) on CO2 in the middle to upper troposphere. To choose the SSW events that had strong coupling between the stratosphere and troposphere, the authors applied a principal component analysis to the NCEP/Department of Energy Global Reanalysis 2 (NCEP-2) geopotential height data at 17 pressure levels. Two events (April 2003 and March 2005) that have strong couplings between the stratosphere and troposphere were chosen to investigate the influence of SSW on AIRS midtropospheric CO2. The authors investigated the temporal and spatial variations of AIRS midtropospheric CO2 before and after the SSW events and found that the midtropospheric CO2 concentrations increased by 2–3 ppm within a few days after the SSW events. These results can be used to better understand how the chemical tracers respond to the large-scale dynamics in the high latitudes.

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Temporal and spatial distributions of precipitation on the Huang-Huai-Hai Plain during 1960–2019, China

Journal of Water and Climate Change ◽

10.2166/wcc.2021.313 ◽

2021 ◽

Author(s):

Minhua Ling ◽

Hongbao Han ◽

Xingling Wei ◽

Cuimei Lv

Keyword(s):

Spatial Distribution ◽

Large Scale ◽

Kendall Test ◽

Winter Precipitation ◽

Annual Precipitation ◽

Temporal And Spatial Distribution ◽

Global Pattern ◽

The North ◽

Variance Contribution ◽

Temporal And Spatial

Abstract The Huang-Huai-Hai Plain is an important commercial grain production base in China. Understanding the temporal and spatial variations in precipitation can help prevent drought and flood disasters and ensure food security. Based on the precipitation data for the Huang-Huai-Hai Plain from 1960 to 2019, this study analysed the spatiotemporal distribution of total precipitation at different time scales using the Mann–Kendall test, the wavelet analysis, the empirical orthogonal function (EOF), and the centre-of-gravity model. The results were as follows: (1) The winter precipitation showed a significant upward trend on the Huang-Huai-Hai Plain, while other seasonal trends were not significant. (2) The precipitation on the Huang-Huai-Hai Plain shows a zonal decreasing distribution from southeast to northwest. (3) The application of the EOF method revealed the temporal and spatial distribution characteristics of the precipitation field. The cumulative variance contribution rate of the first two eigenvectors reached 51.5%, revealing two typical distribution fields, namely a ‘global pattern’ and a ‘north-south pattern’. The ‘global pattern’ is the decisive mode, indicating that precipitation on the Huang-Huai-Hai Plain is affected by large-scale weather systems. (4) The annual precipitation barycentres on the Huang-Huai-Hai Plain were located in Jining city and Taian city, Shandong Province, and the spatial distribution pattern was north-south. The annual precipitation barycentres tended to move southwest, but the trend was not obvious. The annual precipitation barycentre is expected to continue to shift to the north in 2020.

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Temporal and Spatial Fluctuations in Widths of solar Euv Lines

International Astronomical Union Colloquium ◽

10.1017/s0252921100075205 ◽

1980 ◽

Vol 51 ◽

pp. 53-53

Author(s):

R.G. Athay ◽

O.R. White

Keyword(s):

Line Width ◽

Sound Speed ◽

Large Scale ◽

Small Cells ◽

The Sun ◽

Doppler Shifts ◽

Spatial Fluctuations ◽

Local Sound ◽

Line Widths ◽

Temporal And Spatial

AbstractAnalyses of some 300 hours of time sequences of solar EUV line profiles obtained with 0S0-8 show large fluctuations in line widths. At a given location on the sun, line widths fluctuate temporally on time scales ranging from less than a minute to over an hour. At any given time, line widths fluctuate spatially on a variety of scales ranging from active region size to arc second size. Temporal and spatial fluctuations are of approximately the same amplitude. Thus, the sun can be characterized by an aggregate of small cells in each of which line widths are fluctuating in time and which have random phases with respect to each other.Spatial fluctuations in line width are correlated with large scale spatial fluctuations in brightness for some lines but not for others. Temporal fluctuations in width are sometimes correlated with either Doppler shifts or intensity fluctuations, but more often such correlations are absent.For a given line, the line width varies through an extreme range of about a factor of two. Nonthermal components of line width vary from approximately the local sound speed to a small fraction of the sound speed.

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Multi-scale snowdrift-permitting modelling of mountain snowpack

10.5194/tc-2020-187 ◽

2020 ◽

Author(s):

Vincent Vionnet ◽

Christopher B. Marsh ◽

Brian Menounos ◽

Simon Gascoin ◽

Nicholas E. Wayand ◽

...

Keyword(s):

High Resolution ◽

Snow Depth ◽

Large Scale ◽

Small Scale ◽

Topographic Effects ◽

Blowing Snow ◽

Wind Fields ◽

Canopy Interception ◽

Multi Scale ◽

Temporal And Spatial

Abstract. The interaction of mountain terrain with meteorological processes causes substantial temporal and spatial variability in snow accumulation and ablation. Processes impacted by complex terrain include large-scale orographic enhancement of snowfall, small-scale processes such as gravitational and wind-induced transport of snow, and variability in the radiative balance such as through terrain shadowing. In this study, a multi-scale modeling approach is proposed to simulate the temporal and spatial evolution of high mountain snowpacks using the Canadian Hydrological Model (CHM), a multi-scale, spatially distributed modelling framework. CHM permits a variable spatial resolution by using the efficient terrain representation by unstructured triangular meshes. The model simulates processes such as radiation shadowing and irradiance to slopes, blowing snow redistribution and sublimation, avalanching, forest canopy interception and sublimation and snowpack melt. Short-term, km-scale atmospheric forecasts from Environment and Climate Change Canada's Global Environmental Multiscale Model through its High Resolution Deterministic Prediction System (HRDPS) drive CHM, and were downscaled to the unstructured mesh scale using process-based procedures. In particular, a new wind downscaling strategy combines meso-scale HRDPS outputs and micro-scale pre-computed wind fields to allow for blowing snow calculations. HRDPS-CHM was applied to simulate snow conditions down to 50-m resolution during winter 2017/2018 in a domain around the Kananaskis Valley (~1000 km2) in the Canadian Rockies. Simulations were evaluated using high-resolution airborne Light Detection and Ranging (LiDAR) snow depth data and snow persistence indexes derived from remotely sensed imagery. Results included model falsifications and showed that both blowing snow and gravitational snow redistribution need to be simulated to capture the snowpack variability and the evolution of snow depth and persistence with elevation across the region. Accumulation of wind-blown snow on leeward slopes and associated snow-cover persistence were underestimated in a CHM simulation driven by wind fields that did not capture leeside flow recirculation and associated wind speed decreases. A terrain-based metric helped to identify these lee-side areas and improved the wind field and the associated snow redistribution. An overestimation of snow redistribution from windward to leeward slopes and subsequent avalanching was still found. The results of this study highlight the need for further improvements of snowdrift-permitting models for large-scale applications, in particular the representation of subgrid topographic effects on snow transport.

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Transport of Goods Powered by Cereal Straw: Temporal and Spatial Biomass Availability for Future Bio-LNG Production in Germany

10.21203/rs.3.rs-16344/v1 ◽

2020 ◽

Author(s):

André Brosowski ◽

Ralf Bill ◽

Daniela Thrän

Keyword(s):

Large Scale ◽

Transport Sector ◽

Data Sets ◽

Climate Target ◽

Cereal Straw ◽

Arable Fields ◽

Biomethane Production ◽

Temporal And Spatial ◽

The Difference ◽

Biomass Availability

Abstract Background: Half of the UN climate target for 2030 has been achieved and further progress requires swiftly implementable solutions. In this context, the fermentation of cereal straw is a promising option. Returning the digestate to the farmland can close agricultural cycles while simultaneously producing biomethane for the transport sector. The world's first large-scale, mono-digestion plant for straw is operational since 2014. The temporal and spatial biomass availability is a key issue when replicating this concept. No detailed calculations on this subject are available, and the strategic relevance of biomethane from straw in the transport sector cannot be sufficiently evaluated.Methods: To assess the balance of straw supply and use, a total of 30 data sets are combined, taking into account the cultivation of the five most important cereal types and the straw required for ten animal species, two special crops and twelve industrial uses. The data are managed at district level and presented for the years 2010 to 2018. In combination with high-resolution geodata, the results are linked to actual arable fields, and the availability of straw throughout the country is evaluated using a GIS.Results: During the analysis period, the mobilisable potential for future biomethane production is between 13.9–21.5 Tg fm a-1; this is up to 62 % higher than the previously known level. The annual potential fluctuates considerably due to weather anomalies. The all-time maximum in 2014 and the minimum for the last 26 years in 2018 are separated by just four years and a difference of 7.6 Tg fm. However, large parts of the potential are concentrated only in a few regions and liquefied biomethane could fully cover the fuel required for vessels, and up to a quarter of that for heavy goods vehicles. Up to 11.3 Tg CO2-eq. could be saved, reducing the difference to achieve the UN climate target by 3.7 %.Conclusion: Despite the strong fluctuations, the potential is sufficient to supply numerous plants and to produce relevant quantities of liquefied biomethane even in weak years. To unlock the potential, the outcomes should be discussed further with stakeholders in the identified priority regions.

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Remote-Sensing Evaluation and Temporal and Spatial Change Detection of Ecological Environment Quality in Coal-Mining Areas

Remote Sensing ◽

10.3390/rs14020345 ◽

2022 ◽

Vol 14 (2) ◽

pp. 345

Author(s):

Xinran Nie ◽

Zhenqi Hu ◽

Mengying Ruan ◽

Qi Zhu ◽

Huang Sun

Keyword(s):

Coal Mining ◽

Coal Mine ◽

Large Scale ◽

Coal Dust ◽

Ecological Environment ◽

Ecological Index ◽

Mining Areas ◽

Environment Quality ◽

Temporal And Spatial

The large-scale development and utilization of coal resources have brought great challenges to the ecological environment of coal-mining areas. Therefore, this paper has used scientific and effective methods to monitor and evaluate whether changes in ecological environment quality in coal-mining areas are helpful to alleviate the contradiction between human and nature and realize the sustainable development of such coal-mining areas. Firstly, in order to quantify the degree of coal dust pollution in coal-mining areas, an index-based coal dust index (ICDI) is proposed. Secondly, based on the pressure-state-response (PSR) framework, a new coal-mine ecological index (CMEI) was established by using the principal component analysis (PCA) method. Finally, the coal-mine ecological index (CMEI) was used to evaluate and detect the temporal and spatial changes of the ecological environment quality of the Ningwu Coalfield from 1987 to 2021. The research shows that ICDI has a strong ability to extract coal dust with an overall accuracy of over 96% and a Kappa coefficient of over 0.9. As a normalized difference index, ICDI can better quantify the pollution degree of coal dust. The effectiveness of CMEI was evaluated by four methods: sample image-based, classification-based, correlation-based, and distance-based. From 1987 to 2021, the ecological environment quality of Ningwu Coalfield was improved, and the mean of CMEI increased by 0.1189. The percentages of improvement and degradation of ecological environment quality were 71.85% and 27.01%, respectively. The areas with obvious degradation were mainly concentrated in coal-mining areas and built-up areas. The ecological environment quality of Pingshuo Coal Mine, Shuonan Coal Mine, Xuangang Coal Mine, and Lanxian Coal Mine also showed improvement. The results of Moran’s Index show that CMEI has a strong positive spatial correlation, and its spatial distribution is clustered rather than random. Coal-mining areas and built-up areas showed low–low clustering (LL), while other areas showed high–high clustering (HH). The utilization and popularization of CMEI provides an important reference for decision makers to formulate ecological protection policies and implement regional coordinated development strategies.

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Understanding the Distribution of Multimodel Ensembles

Journal of Climate ◽

10.1175/jcli-d-20-0186.1 ◽

2020 ◽

Vol 33 (21) ◽

pp. 9447-9465

Author(s):

Bo Christiansen

Keyword(s):

Statistical Model ◽

Large Scale ◽

Climate Models ◽

Spatial Scales ◽

Model Errors ◽

High Dimensions ◽

Ensemble Mean ◽

Temporal And Spatial ◽

Multimodel Ensembles ◽

Annual Means

AbstractWhen analyzing multimodel climate ensembles it is often assumed that the ensemble is either truth centered or that models and observations are drawn from the same distribution. Here we analyze CMIP5 ensembles focusing on three measures that separate the two interpretations: the error of the ensemble mean relative to the error of individual models, the decay of the ensemble mean error for increasing ensemble size, and the correlations of the model errors. The measures are analyzed using a simple statistical model that includes the two interpretations as different limits and for which analytical results for the three measures can be obtained in high dimensions. We find that the simple statistical model describes the behavior of the three measures in the CMIP5 ensembles remarkably well. Except for the large-scale means we find that the indistinguishable interpretation is a better assumption than the truth centered interpretation. Furthermore, the indistinguishable interpretation becomes an increasingly better assumption when the errors are based on smaller temporal and spatial scales. Building on this, we present a simple conceptual mechanism for the indistinguishable interpretation based on the assumption that the climate models are calibrated on large-scale features such as, e.g., annual means or global averages.

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UAS for Forest Inventory Traits: A Review

10.32942/osf.io/xjdt3 ◽

2021 ◽

Author(s):

Anna Spiers ◽

Victoria Scholl ◽

Joe McGlinchy ◽

Jennifer Balch ◽

Megan Elizabeth Cattau

Keyword(s):

Forest Inventory ◽

Carbon Stock ◽

Spatial Ecology ◽

Large Scale ◽

Forest Ecology ◽

Spatial Extent ◽

Field Methods ◽

Trait Mapping ◽

Temporal And Spatial ◽

Aerial Systems

Traits are notoriously challenging to measure at a desirably large spatial extent with traditional field methods, which limits the discoveries that forest ecologists can make with these data. There is a ripe opportunity for uncrewed aerial systems (UAS) to contribute to ecology through forest inventory trait mapping. UAS can help overcome the challenge of scale by collecting data at a larger spatial extent with comparable resolution. With the proliferation of large-scale spatially explicit analyses, using UAS for forest trait mapping is synergistic with the direction that the field of forest ecology is headed, and thus an essential method for forest ecology toolkits. Here we provide evidence that forest traits are increasingly used as the metrics of focus in forest ecology, review what forest inventory traits and attributes can be derived from UAS-based data, and dive into a case example of how researchers derive a particular trait, carbon stock, from UAS-based data. Our results highlight the underutilization and infancy of UAS in forest ecology. From our review of the carbon stock literature, we found a different method of calculating carbon stock from UAS data in every paper, each with their own hurdles and caveats in estimating plant-based carbon stock. UAS can push forest ecology and the concomitant field of spatial ecology into a future with better temporal and spatial resolution of data collected on an evermore affordable budget.

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