scholarly journals IWV observations in the Caribbean Arc from a network of ground-based GNSS receivers during EUREC<sup>4</sup>A

2021 ◽  
Author(s):  
Olivier Bock ◽  
Pierre Bosser ◽  
Cyrille Flamant ◽  
Erik Doerflinger ◽  
Friedhelm Jansen ◽  
...  
Keyword(s):  
Large Scale ◽  
Microwave Radiometer ◽  
Heavy Rain ◽  
Tropospheric Delay ◽  
Systematic Bias ◽  
Data Set ◽  
Radiosonde Station ◽  
The Caribbean ◽  
Cloud Patterns ◽  
Dry Bias

Abstract. Ground-based Global Navigation Satellite System (GNSS) measurements from nearly fifty stations distributed over the Caribbean Arc have been analysed for the period 1 January–29 February 2020 in the framework of the EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) field campaign. The aim of this effort is to deliver high-quality Integrated Water Vapour (IWV) estimates to investigate the moisture environment of mesoscale cloud patterns in the Tradewinds and their feedback on the large-scale circulation and energy budget. This paper describes the GNSS data processing procedures and assesses the quality of the GNSS IWV retrievals from four operational streams and one reprocessed research stream which is the main data set used for offline scientific applications. The uncertainties associated with each of the data sets, including the zenith tropospheric delay (ZTD) to IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the Barbados Cloud Observatory (BCO) and to the measurements from the operational radiosonde station at Grantley Adams international airport (GAIA). A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (−2.9 kg m−2) and the GNSS results (−1.2 kg m−2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg m−2) where the Vaisala RS41 measurements are moister than the GNSS retrievals. The IWV estimates from a colocated microwave radiometer agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to the soundings and to GNSS before that date. IWV estimates from the ECMWF fifth generation reanalysis (ERA5) are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the GNSS derived IWV peaks. Two successive peaks are observed on 22 January and 23/24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated. We classified the cloud organisation for five representative GNSS stations across the Caribbean Arc and found that the environment of Fish cloud patterns to be moister than that of Flowers cloud patterns which, in turn, is moister than the environment of Gravel cloud patterns. The differences in the IWV means between Fish and Gravel were assessed to be significant. Finally, the Gravel moisture environment was found to be similar to that of clear, cloud-free conditions. The moisture environment associated with the Sugar cloud pattern has not been assessed because it was hardly observed during the first two months of 2020. The reprocessed ZTD and IWV data set from 49 GNSS stations used in this study are available from the AERIS data center (https://doi.org/10.25326/79; Bock (2020b)).

IWV observations from a network of ground-based GNSS receivers during EUREC4A

2021 ◽  
Author(s):  
Olivier Bock ◽  
Pierre Bosser ◽  
Cyrille Flamant ◽  
Erik Doerflinger ◽  
Friedhelm Jansen ◽  
...  
Keyword(s):  
Large Scale ◽  
Microwave Radiometer ◽  
Heavy Rain ◽  
Satellite System ◽  
Atmospheric Environment ◽  
Tropospheric Delay ◽  
Systematic Bias ◽  
Data Set ◽  
Radiosonde Station ◽  
Dry Bias

&lt;p&gt;IWV data were retrieved from a network of nearly fifty Global Navigation Satellite System (GNSS) stations distributed over the Caribbean arc for the period 1 January-29 February 2020 encompassing the EUREC4A field campaign. Two of the stations had been installed at the Barbados Cloud Observatory (BCO) during fall 2019 in the framework of the project and are still running. All other stations are permanent stations operated routinely from various geodetic and geophysical organisations in the region. High spatial and temporal Integrated Water Vapour (IWV) observations will be used to investigate the atmospheric environment during the life cycle of convection and its feedback on the large-scale circulation and energy budget.&lt;/p&gt;&lt;p&gt;This paper describes the ground-based GNSS data processing details and assesses the quality of the GNSS IWV retrievals as well as the IWV estimates from radiosoundings, microwave radiometer measurements and ERA5 reanalysis.&lt;/p&gt;&lt;p&gt;The GNSS results from five different processing streams run by IGN and ENSTA-B/IPGP are first intercompared. Four of the streams were run operationally, among one was in near-real time, and one was run after the campaign in a reprocessing mode. The uncertainties associated with each of the data sets, including the zenith tropospheric delay to IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the BCO and to the measurements from the operational radiosonde station at Grantley Adams international airport (GAIA). A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (-2.9 kg/m2) and the GNSS results (-1.2 kg/m2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg/m2) where the Vaisala RS41 measurements are moister than the GNSS retrievals. The HATPRO IWV estimates agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to GNSS and BCO sondes before that date. ERA5 IWV estimates are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the IWV peaks. Two successive peaks are observed on 22 January and 23/24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated.&lt;/p&gt;

scholarly journals Integrated water vapour observations in the Caribbean arc from a network of ground-based GNSS receivers during EUREC<sup>4</sup>A

2021 ◽  
Vol 13 (5) ◽  
pp. 2407-2436
Author(s):  
Olivier Bock ◽  
Pierre Bosser ◽  
Cyrille Flamant ◽  
Erik Doerflinger ◽  
Friedhelm Jansen ◽  
...  
Keyword(s):  
Water Vapour ◽  
Tropospheric Delay ◽  
Data Sets ◽  
Systematic Bias ◽  
Data Set ◽  
Radiosonde Station ◽  
Integrated Water Vapour ◽  
The Caribbean ◽  
Cloud Patterns ◽  
Dry Bias

Abstract. Ground-based Global Navigation Satellite System (GNSS) measurements from nearly 50 stations distributed over the Caribbean arc have been analysed for the period 1 January–29 February 2020 in the framework of the EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) field campaign. The aim of this effort is to deliver high-quality integrated water vapour (IWV) estimates to investigate the moisture environment of mesoscale cloud patterns in the trade winds and their feedback on the large-scale circulation and energy budget. This paper describes the GNSS data processing procedures and assesses the quality of the GNSS IWV retrievals from four operational streams and one reprocessed research stream which is the main data set used for offline scientific applications. The uncertainties associated with each of the data sets, including the zenith tropospheric delay (ZTD)-to-IWV conversion methods and auxiliary data, are quantified and discussed. The IWV estimates from the reprocessed data set are compared to the Vaisala RS41 radiosonde measurements operated from the Barbados Cloud Observatory (BCO) and to the measurements from the operational radiosonde station at Grantley Adams International Airport (GAIA), Bridgetown, Barbados. A significant dry bias is found in the GAIA humidity observations with respect to the BCO sondes (−2.9 kg m−2) and the GNSS results (−1.2 kg m−2). A systematic bias between the BCO sondes and GNSS is also observed (1.7 kg m−2), where the Vaisala RS41 measurements are moister than the GNSS retrievals. The IWV estimates from a collocated microwave radiometer agree with the BCO soundings after an instrumental update on 27 January, while they exhibit a dry bias compared to the soundings and to GNSS before that date. IWV estimates from the ECMWF fifth-generation reanalysis (ERA5) are overall close to the GAIA observations, probably due to the assimilation of these observations in the reanalysis. However, during several events where strong peaks in IWV occurred, ERA5 is shown to significantly underestimate the GNSS-derived IWV peaks. Two successive peaks are observed on 22 January and 23–24 January which were associated with heavy rain and deep moist layers extending from the surface up to altitudes of 3.5 and 5 km, respectively. ERA5 significantly underestimates the moisture content in the upper part of these layers. The origins of the various moisture biases are currently being investigated. We classified the cloud organization for five representative GNSS stations across the Caribbean arc using visible satellite images. A statistically significant link was found between the cloud patterns and the local IWV observations from the GNSS sites as well as the larger-scale IWV patterns from the ECMWF ERA5 reanalysis. The reprocessed ZTD and IWV data sets from 49 GNSS stations used in this study are available from the French data and service centre for atmosphere (AERIS) (https://doi.org/10.25326/79; Bock, 2020b).

scholarly journals Potential Impacts of Assimilating All-Sky Satellite Infrared Radiances on Convection-Permitting Analysis and Prediction of Tropical Convection

2020 ◽  
Vol 148 (8) ◽  
pp. 3203-3224
Author(s):  
Man-Yau Chan ◽  
Fuqing Zhang ◽  
Xingchao Chen ◽  
L. Ruby Leung
Keyword(s):  
Data Assimilation ◽  
Brightness Temperature ◽  
Large Scale ◽  
Spatial Scales ◽  
Tropical Convection ◽  
Tropical Oceans ◽  
Geostationary Meteorological Satellite ◽  
Infrared Radiances ◽  
Cloud Patterns ◽  
Dry Bias

Abstract Geostationary infrared satellite observations are spatially dense [&gt;1/(20 km)2] and temporally frequent (&gt;1 h−1). These suggest the possibility of using these observations to constrain subsynoptic features over data-sparse regions, such as tropical oceans. In this study, the potential impacts of assimilating water vapor channel brightness temperature (WV-BT) observations from the geostationary Meteorological Satellite 7 (Meteosat-7) on tropical convection analysis and prediction were systematically examined through a series of ensemble data assimilation experiments. WV-BT observations were assimilated hourly into convection-permitting ensembles using Penn State’s ensemble square root filter (EnSRF). Comparisons against the independently observed Meteosat-7 window channel brightness temperature (Window-BT) show that the assimilation of WV-BT generally improved the intensities and locations of large-scale cloud patterns at spatial scales larger than 100 km. However, comparisons against independent soundings indicate that the EnSRF analysis produced a much stronger dry bias than the no data assimilation experiment. This strong dry bias is associated with the use of the simulated WV-BT from the prior mean during the EnSRF analysis step. A stochastic variant of the ensemble Kalman filter (NoMeanSF) is proposed. The NoMeanSF algorithm was able to assimilate the WV-BT without causing such a strong dry bias and the quality of the analyses’ horizontal cloud pattern is similar to EnSRF’s analyses. Finally, deterministic forecasts initiated from the NoMeanSF analyses possess better horizontal cloud patterns above 500 km than those of the EnSRF. These results suggest that it might be better to assimilate all-sky WV-BT through the NoMeanSF algorithm than the EnSRF algorithm.

scholarly journals Kinematic Zenith Tropospheric Delay Estimation with GNSS PPP in Mountainous Areas

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5709
Author(s):  
Paul Gratton ◽  
Simon Banville ◽  
Gérard Lachapelle ◽  
Kyle O’Keefe
Keyword(s):  
Ambiguity Resolution ◽  
Large Scale ◽  
Field Experiments ◽  
Integer Ambiguity Resolution ◽  
Global Navigation Satellite Systems ◽  
Integer Ambiguity ◽  
Tropospheric Delay ◽  
Mountainous Areas ◽  
Data Set ◽  
Zenith Tropospheric Delay

The use of global navigation satellite systems (GNSS) precise point positioning (PPP) to estimate zenith tropospheric delay (ZTD) profiles in kinematic vehicular mode in mountainous areas is investigated. Car-mounted multi-constellation GNSS receivers are employed. The Natural Resources Canada Canadian Spatial Reference System PPP (CSRS-PPP) online service that currently processes dual-frequency global positioning system (GPS) and Global’naya Navigatsionnaya Sputnikovaya Sistema (GLONASS) measurements and is now capable of GPS integer ambiguity resolution is used. An offline version that can process the above and Galileo measurements simultaneously, including Galileo integer ambiguity resolution is also tested to evaluate the advantage of three constellations. A multi-day static data set observed under open sky is first tested to determine performance under ideal conditions. Two long road profile tests conducted in kinematic mode are then analyzed to assess the capability of the approach. The challenges of ZTD kinematic profiling are numerous, namely shorter data sets, signal shading due to topography and forests of conifers along roads, and frequent losses of phase lock requiring numerous but not always successful integer ambiguity re-initialization. ZTD profiles are therefore often only available with float ambiguities, reducing system observability. Occasional total interruption of measurement availability results in profile discontinuities. CSRS-PPP outputs separately the zenith hydrostatic or dry delay (ZHD) and water vapour content or zenith wet delay (ZWD). The two delays are analyzed separately, with emphasis on the more unpredictable and highly variable ZWD, especially in mountainous areas. The estimated delays are compared with the Vienna Mapping Function 1 (VMF1), which proves to be highly effective to model the large-scale profile variations in the Canadian Rockies, the main contribution of GNSS PPP being the estimation of higher frequency ZWD components. Of the many conclusions drawn from the field experiments, it is estimated that kinematic profiles are generally determined with accuracy of 10 to 20 mm, depending on the signal harshness of the environment.

scholarly journals Experience of Activation of the J-SPEED(MDS) in Japan

2019 ◽  
Vol 34 (s1) ◽  
pp. s130-s131
Author(s):  
Tatsuhiko Kubo ◽  
Joji Tomioka ◽  
Hisayoshi Kondo ◽  
Yuichi Koido
Keyword(s):  
Large Scale ◽  
Heavy Rain ◽  
Electronic System ◽  
Lessons Learned ◽  
World Health ◽  
Advisory Group ◽  
Data Set ◽  
National Education ◽  
Kumamoto Earthquake ◽  
Support Team

Introduction:The Emergency Medical Team (EMT) Strategic Advisory Group of the World Health Organization has endorsed the EMT Minimum Data Set (MDS) as the standard methodology for EMT daily report. The MDS had been developed on a similar methodology called J-SPEED which developed in Japan. Thus, lessons learned from the J-SPEED can be applied to the MDS.Aim:To review previous J-SPEED activations and to extract lessons learned.Methods:Cases of the J-SPEED activation at the Kumamoto earthquake in 2016, West Japan Heavy Rain in 2018, and Hokkaido Earthquake in 2018 were reviewed.Results:The first large-scale activation of the J-SPEED at the Kumamoto earthquake revealed a significant burden in aggregations of submitted paper forms at the EMT Coordination Cell (EMTCC). To strengthen this function of the EMTCC, electronic system and human capacity development have been identified as key issues. To fulfill this gap, a smartphone app so-called J-SPEED+ has been developed. Also, the J-SPEED offsite analysis support team, which is a team to support analysis of data from outside of an affected area has been established. These two functions contributed to significant improvement of J-SPEED data flow at the West Japan Heavy Rain and Hokkaido Earthquake. These two responses reinforced the necessity of strengthening the capacity of J-SPEED onsite coordinator working at the ETMCC, and national education and training for all EMTs.Discussion:In order to strengthen the mechanism to run the J-SPEED, nationwide training for all EMTs, onsite coordinators, and the off-site analysis support team have been established. The authors regard this structural approach as a requirement for other countries to run the MDS.

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.

scholarly journals Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

2020 ◽  
Vol 37 ◽  
Author(s):  
Lior Shamir
Keyword(s):  
Large Scale ◽  
Spiral Galaxies ◽  
Hubble Space Telescope ◽  
Gravitational Interaction ◽  
Large Data ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Dipole Axis ◽  
Data Set ◽  
The Asymmetry

Abstract Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of $\sim8.7\cdot10^3$ spiral galaxies imaged by Hubble Space Telescope (HST) is used to test and profile a possible asymmetry between galaxy spin directions. The asymmetry between galaxies with opposite spin directions is compared to the asymmetry of galaxies from the Sloan Digital Sky Survey. The two data sets contain different galaxies at different redshift ranges, and each data set was annotated using a different annotation method. The results show that both data sets show a similar asymmetry in the COSMOS field, which is covered by both telescopes. Fitting the asymmetry of the galaxies to cosine dependence shows a dipole axis with probabilities of $\sim2.8\sigma$ and $\sim7.38\sigma$ in HST and SDSS, respectively. The most likely dipole axis identified in the HST galaxies is at $(\alpha=78^{\rm o},\delta=47^{\rm o})$ and is well within the $1\sigma$ error range compared to the location of the most likely dipole axis in the SDSS galaxies with $z>0.15$ , identified at $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

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