scholarly journals Streamflow indices to identify catchment drivers of hydrograph

2021 ◽  
Author(s):  
Jeenu Mathai ◽  
Pradeep Mujumdar
Keyword(s):  
Large Scale ◽  
Catchment Scale ◽  
Regional Variability ◽  
Data Set ◽  
Temporal Asymmetry ◽  
Hydrologic Processes ◽  
Statistical Assumptions ◽  
Comparative Hydrology ◽  
Time Irreversibility ◽  
Characteristic Features

Abstract. Streamflow indices are flow descriptors that quantify the streamflow dynamics, which are usually determined for a specific basin and are distinct from other basin features. The flow descriptors are appropriate for large-scale and comparative hydrology studies, independent of statistical assumptions and can distinguish signals that indicate basin behavior over time. In this paper, the characteristic features of the hydrograph's temporal asymmetry due to its different underlying hydrologic processes are primarily highlighted. Streamflow indices linked to each limb of the hydrograph within the time-irreversibility paradigm are distinguished with respect to its processes driving the rising and falling limbs. Various streamflow indices relating the rising and falling limbs, and the catchment attributes such as climate, topography, vegetation, geology and soil are then correlated. Finally, the key attributes governing rising and falling limbs are identified. The novelty of the work is on differentiating hydrographs by their time irreversibility property and offering an alternative way to recognize primary drivers of streamflow hydrographs. A set of streamflow indices at the catchment scale for 671 basins in the Contiguous United States (CONUS) is presented here. These streamflow indices complement the catchment attributes provided earlier (Addor et al., 2017) for the CAMELS data set. A series of spatial maps describing the streamflow indices and their regional variability over the CONUS is illustrated in this study.

scholarly journals A UT/LS ozone climatology of the nineteen seventies deduced from the GASP aircraft measurement program

2007 ◽  
Vol 7 (22) ◽  
pp. 5917-5936 ◽  
Author(s):  
C. Schnadt Poberaj ◽  
J. Staehelin ◽  
D. Brunner ◽  
V. Thouret ◽  
V. Mohnen
Keyword(s):  
Large Scale ◽  
Marine Boundary Layer ◽  
Control Program ◽  
Data Set ◽  
Nineteen Seventies ◽  
Research Aircraft ◽  
Independent Observations ◽  
Characteristic Features ◽  
Flight Route ◽  
Atmospheric Sampling

Abstract. We present ozone measurements of the Global Atmospheric Sampling Program (GASP) performed from four commercial and one research aircraft in the late 1970s. The GASP quality assurance and control program was reviewed, and an ozone climatology of the upper troposphere and lower stratosphere (UT/LS) of the years 1975–1979 was built. The data set was estimated to have an overall uncertainty of 9% or 3 ppb whichever is greater for the first two years and 4% or 3 ppb for the remaining years, i.e. after implementation of silicone rubber membranes in the pumps. Two cases of nearly coincident flights of two GASP airliners along the same flight route, and the comparison with independent observations from the literature, including ozonesondes and aircraft campaigns, indicate that the ozone measurements are of high quality. The UT/LS climatology of the GASP data set is in general agreement with that derived from MOZAIC in the 1990s in regions covered by both programmes. GASP provides unique large-scale climatological information on UT/LS ozone above the northern hemisphere Pacific region, which is not covered by MOZAIC. There, the GASP climatology confirms several characteristic features derived from individual research aircraft campaigns and from ozone soundings. In particular, summertime ozone in the UT over the midlatitude eastern Pacific Ocean was significantly lower in the 1970s than over the American continent. The generally lower ozone concentrations in the tropics near the dateline as compared to farther east are indicative of convective uplifting of ozone poor air from the marine boundary layer.

scholarly journals Detecting regional variability in sources and sinks of carbon dioxide: a synthesis

2009 ◽  
Vol 6 (6) ◽  
pp. 1015-1026 ◽  
Author(s):  
A. J. Dolman ◽  
C. Gerbig ◽  
J. Noilhan ◽  
C. Sarrat ◽  
F. Miglietta
Keyword(s):  
Boundary Layer ◽  
Large Scale ◽  
Carbon Fluxes ◽  
Considerable Effort ◽  
Regional Variability ◽  
Data Set ◽  
Mesoscale Models ◽  
Boundary Layer Height ◽  
Inverse Models ◽  
Flux Measurements

Abstract. The current paper reviews the experimental setup of the CarboEurope Experimental Strategy (CERES) campaigns with the aim of providing an overview of the instrumentation used, the data-set and associated modelling. It then assesses progress in the field of regional observation and modelling of carbon fluxes, bringing the papers of this special issue into a somewhat broader context of analysis. Instrumental progress has been obtained in the field of remotely monitoring from tall towers and the experimental planning. Flux measurements from aircraft are now capable, within some constraints, to provide regular regional observations of fluxes of CO2, latent and sensible heat. Considerable effort still needs to be put into calibrating the surface schemes of models, as they have direct impact on the input of energy, moisture and carbon fluxes in the boundary layer. Overall, the mesoscale models appear to be capable of simulating the large scale dynamics of the region, but in the fine detail, like the precise horizontal and vertical CO2 field differences between the models still exist. These errors translate directly into transport uncertainty, when the forward simulations are used in inverse mode. Quantification of this uncertainty, including that of inadequate boundary layer height modelling, still remains a major challenge for state of the art mesoscale models. Progress in inverse models has been slow, but has shown that it is possible to estimate some of the errors involved, and that using the combination of observations. Overall, the capability to produce regional, high-resolution estimates of carbon exchange, exist in potential, but the routine application will require considerable effort, both in the experimental as in the modelling domain.

scholarly journals The CAMELS data set: catchment attributes and meteorology for large-sample studies

2017 ◽  
Vol 21 (10) ◽  
pp. 5293-5313 ◽  
Author(s):  
Nans Addor ◽  
Andrew J. Newman ◽  
Naoki Mizukami ◽  
Martyn P. Clark
Keyword(s):  
Time Series ◽  
Data Sets ◽  
Catchment Scale ◽  
Data Set ◽  
Meteorological Forcing ◽  
Large Sample ◽  
Source Data ◽  
Daily Time Series ◽  
Comparative Hydrology ◽  
Daily Time

Abstract. We present a new data set of attributes for 671 catchments in the contiguous United States (CONUS) minimally impacted by human activities. This complements the daily time series of meteorological forcing and streamflow provided by Newman et al. (2015b). To produce this extension, we synthesized diverse and complementary data sets to describe six main classes of attributes at the catchment scale: topography, climate, streamflow, land cover, soil, and geology. The spatial variations among basins over the CONUS are discussed and compared using a series of maps. The large number of catchments, combined with the diversity of the attributes we extracted, makes this new data set well suited for large-sample studies and comparative hydrology. In comparison to the similar Model Parameter Estimation Experiment (MOPEX) data set, this data set relies on more recent data, it covers a wider range of attributes, and its catchments are more evenly distributed across the CONUS. This study also involves assessments of the limitations of the source data sets used to compute catchment attributes, as well as detailed descriptions of how the attributes were computed. The hydrometeorological time series provided by Newman et al. (2015b, https://doi.org/10.5065/D6MW2F4D) together with the catchment attributes introduced in this paper (https://doi.org/10.5065/D6G73C3Q) constitute the freely available CAMELS data set, which stands for Catchment Attributes and MEteorology for Large-sample Studies.

scholarly journals The CAMELS data set: catchment attributes and meteorology for large-sample studies

2017 ◽  
Author(s):  
Nans Addor ◽  
Andrew J. Newman ◽  
Naoki Mizukami ◽  
Martyn P. Clark
Keyword(s):  
Time Series ◽  
Essential Feature ◽  
Data Sets ◽  
Catchment Scale ◽  
Data Set ◽  
Large Sample ◽  
Quantitative Estimates ◽  
Comparative Hydrology ◽  
Vegetation Characteristics ◽  
Landscape Attributes

Abstract. We present a new data set of attributes for 671 catchments in the contiguous USA (CONUS). This complements the daily hydrometeorological time series provided by Newman et al. (2015b) and opens new opportunities to explore how the interplay between landscape attributes shapes hydrological processes and catchment behavior. To produce this extension, we synthesized diverse and complementary data sets to describe topography, climate, hydrology, soil and vegetation characteristics at the catchment scale. The spatial variations among basins over the CONUS are discussed and compared using a series of maps. The large number of catchments, combined with the diversity of their geophysical characteristics, makes this new data well suited for large-sample studies and comparative hydrology. An essential feature, that differentiates this data set from similar ones, is that it both provides quantitative estimates of diverse catchment attributes, and involves assessments of the limitations of the data and methods used to compute those attributes. This data set will be publicly available and we encourage the community to further extend it. The hydrometeorological time series provided by Newman et al. (2015b) together with the catchment attributes introduced in this paper constitute the CAMELS data set: Catchment Attributes and MEteorology for Large-sample Studies.

ProGen:Provenance database generator for large-scale data set

2009 ◽  
Vol 28 (11) ◽  
pp. 2737-2740
Author(s):  
Xiao ZHANG ◽  
Shan WANG ◽  
Na LIAN
Keyword(s):  
Large Scale ◽  
Data Set ◽  
Large Scale Data ◽  
Scale Data

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

scholarly journals Relationship between large-scale ionospheric field-aligned currents and electron/ion precipitations: DMSP observations

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Chao Xiong ◽  
Claudia Stolle ◽  
Patrick Alken ◽  
Jan Rauberg
Keyword(s):  
Time Distribution ◽  
Large Scale ◽  
Particle Flux ◽  
Particle Energy ◽  
Lower Latitude ◽  
Particle Precipitation ◽  
Data Set ◽  
The Mean ◽  
Two Parameters ◽  
Meteorological Satellite

Abstract In this study, we have derived field-aligned currents (FACs) from magnetometers onboard the Defense Meteorological Satellite Project (DMSP) satellites. The magnetic latitude versus local time distribution of FACs from DMSP shows comparable dependences with previous findings on the intensity and orientation of interplanetary magnetic field (IMF) By and Bz components, which confirms the reliability of DMSP FAC data set. With simultaneous measurements of precipitating particles from DMSP, we further investigate the relation between large-scale FACs and precipitating particles. Our result shows that precipitation electron and ion fluxes both increase in magnitude and extend to lower latitude for enhanced southward IMF Bz, which is similar to the behavior of FACs. Under weak northward and southward Bz conditions, the locations of the R2 current maxima, at both dusk and dawn sides and in both hemispheres, are found to be close to the maxima of the particle energy fluxes; while for the same IMF conditions, R1 currents are displaced further to the respective particle flux peaks. Largest displacement (about 3.5°) is found between the downward R1 current and ion flux peak at the dawn side. Our results suggest that there exists systematic differences in locations of electron/ion precipitation and large-scale upward/downward FACs. As outlined by the statistical mean of these two parameters, the FAC peaks enclose the particle energy flux peaks in an auroral band at both dusk and dawn sides. Our comparisons also found that particle precipitation at dawn and dusk and in both hemispheres maximizes near the mean R2 current peaks. The particle precipitation flux maxima closer to the R1 current peaks are lower in magnitude. This is opposite to the known feature that R1 currents are on average stronger than R2 currents.

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