scholarly journals An examination of the effect of the TESS extended mission on southern hemisphere monotransits

2019 ◽  
Vol 631 ◽  
pp. A83 ◽  
Author(s):  
Benjamin F. Cooke ◽  
Don Pollacco ◽  
Daniel Bayliss
Keyword(s):  
Southern Hemisphere ◽  
Large Time ◽  
First Year ◽  
Data Sets ◽  
Data Set ◽  
Window Functions ◽  
Time Gap ◽  
Initial Survey

Context. NASA recently announced an extended mission for TESS. As a result it is expected that the southern ecliptic hemisphere will be re-observed approximately two years after the initial survey. Aims. We aim to explore how TESS re-observing the southern ecliptic hemisphere will impact the number and distribution of monotransits discovered during the first year of observations. This simulation will be able to be scaled to any future TESS re-observations. Methods. We carry out an updated simulation of TESS detections in the southern ecliptic hemisphere. This simulation includes realistic Sector window-functions based on the first 11 sectors of SPOC 2 min SAP lightcurves. We then extend this simulation to cover the expected Year 4 of the mission when TESS will re-observe the southern ecliptic fields. For recovered monotransits we also look at the possibility of predicting the period based on the coverage in the TESS data. Results. We find an updated prediction of 339 monotransits from the TESS Year 1 southern ecliptic hemisphere, and that approximately 80% of these systems (266/339) will transit again in the Year 4 observations. The Year 4 observations will also contribute new monotransits not seen in Year 1, resulting in a total of 149 monotransits from the combined Year 1 and Year 4 data sets. We find that 75% (189/266) of recovered Year 1 monotransits will only transit once in the Year 4 data set. For these systems we will be able to constrain possible periods, but period aliasing due to the large time gap between Year 1 and Year 4 observations means that the true period will remain unknown without further spectroscopic or photometric follow-up.

scholarly journals Matching Dendrochronological Dates with the Southern Hemisphere 14C Bomb Curve to Confirm Annual Tree Rings in Pseudolmedia rigida from Bolivia

Radiocarbon ◽  
2015 ◽  
Vol 57 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Laia Andreu-Hayles ◽  
Guaciara M Santos ◽  
David A Herrera-Ramírez ◽  
Javier Martin-Fernández ◽  
Daniel Ruiz-Carrascal ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Tree Rings ◽  
Geographic Location ◽  
Data Sets ◽  
Atmospheric Concentration ◽  
Concentration Data ◽  
Data Set ◽  
Dendrochronological Analysis ◽  
Before And After ◽  
Ring Analysis

This study used high-precision radiocarbon bomb-pulse dating of selected wood rings to provide an independent validation of the tree growth periodicity of Pseudolmedia rigida (Klotzsch & H. Karst) Cuatrec. from the Moraceae family, collected in the Madidi National Park in Bolivia. 14C content was measured by accelerator mass spectrometry (AMS) in 10 samples from a single tree covering over 70 yr from 1939 to 2011. These preliminary calendar dates were determined by dendrochronological techniques and were also used to select the samples for 14C AMS. In order to validate these preliminary dates using the established Southern Hemisphere (SH) 14C atmospheric concentration data set, the targeted rings were selected to be formed during periods before and after the 14C bomb spike nuclear tests (i.e. 1950s–1960s). The excellent agreement of the dendrochronological dates and the 14C signatures in tree rings associated with the same dates provided by the bomb-pulse 14C atmospheric values for the SH (SHCal zone 1–2) confirms the annual periodicity of the observed growth layers, and thus the high potential of this species for tree-ring analysis. The lack of discrepancies between both data sets also suggests that there are no significant latitudinal differences between the 14C SHCal zone 1–2 curve and the 14C values obtained from the selected tree rings at this geographic location (14°33′S, 68°49′W) in South America. The annual resolution of P. rigida tree rings opens the possibility of broader applications of dendrochronological analysis for ecological and paleoclimatic studies in the Bolivian tropics, as well as the possibility of using wood samples from some tree species from this region to improve the quality of the bomb-pulse 14C SHCal curve at this latitude.

scholarly journals SCIAMACHY WFM-DOAS XCO<sub>2</sub>: comparison with CarbonTracker XCO<sub>2</sub> focusing on aerosols and thin clouds

2012 ◽  
Vol 5 (2) ◽  
pp. 2887-2931 ◽  
Author(s):  
J. Heymann ◽  
O. Schneising ◽  
M. Reuter ◽  
M. Buchwitz ◽  
V. V. Rozanov ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Temporal Correlation ◽  
Anthropogenic Activity ◽  
Data Sets ◽  
Spatial Correlations ◽  
Data Set ◽  
Cloud Data ◽  
Temporal Correlations ◽  
Retrieval Errors ◽  
The Difference

Abstract. Carbon dioxide (CO2) is the most important greenhouse gas whose atmospheric loading has been significantly increased by anthropogenic activity leading to global warming. Accurate measurements and models are needed in order to reliably predict our future climate. This, however, has challenging requirements. Errors in measurements and models need to be identified and minimised. In this context, we present a comparison between satellite-derived column-averaged dry air mole fractions of CO2, denoted XCO2, retrieved from SCIAMACHY/ENVISAT using the WFM-DOAS algorithm, and output from NOAA's global CO2 modelling and assimilation system CarbonTracker. We investigate to what extent differences between these two data sets are influenced by systematic retrieval errors due to aerosols and unaccounted clouds. We analyse seven years of SCIAMACHY WFM-DOAS version 2.1 retrievals (WFMDv2.1) using the latest version of CarbonTracker (version 2010). We investigate to what extent the difference between SCIAMACHY and CarbonTracker XCO2 are temporally and spatially correlated with global aerosol and cloud data sets. For this purpose, we use a global aerosol data set generated within the European GEMS project, which is based on assimilated MODIS satellite data. For clouds, we use a data set derived from CALIOP/CALIPSO. We find significant correlations of the SCIAMACHY minus CarbonTracker XCO2 difference with thin clouds over the Southern Hemisphere. The maximum temporal correlation we find for Darwin, Australia (r2 = 54%). Large temporal correlations with thin clouds are also observed over other regions of the Southern Hemisphere (e.g. 43% for South America and 31% for South Africa). Over the Northern Hemisphere the temporal correlations are typically much lower. An exception is India, where large temporal correlations with clouds and aerosols have also been found. For all other regions the temporal correlations with aerosol are typically low. For the spatial correlations the picture is less clear. They are typically low for both aerosols and clouds, but dependent on region and season, they may exceed 30% (the maximum value of 46% has been found for Darwin during September to November). Overall we find that the presence of thin clouds can potentially explain a significant fraction of the difference between SCIAMACHY WFMDv2.1 XCO2 and CarbonTracker over the Southern Hemisphere. Aerosols appear to be less of a problem. Our study indicates that the quality of the satellite derived XCO2 will significantly benefit from a reduction of scattering related retrieval errors at least for the Southern Hemisphere.

scholarly journals Exploring Alternative Designs using ‘Big’ Administrative Data

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Leslie Roos ◽  
Elizabeth Wall-Wieler ◽  
Mahmoud Torabi
Keyword(s):  
Administrative Data ◽  
Statistical Power ◽  
Clinical Epidemiology ◽  
Maternal Mental Health ◽  
Data Sets ◽  
Model Assessment ◽  
Data Set ◽  
Time Periods ◽  
Alternative Designs

IntroductionLarge population-based data sets present similar analytic issues across such fields as: population health, clinical epidemiology, education, justice, and children’s services. Step-wise approaches and generalized tools can bring together several pillars: big (typically administrative) data, programming, and study design/analysis. How can we improve efficiency and explore alternative designs? Objectives and ApproachLinked data sets typically contain: 1) files presenting longitudinal histories 2) substantive files noting various events (concussions, burns, loss of a loved one, public housing entry) and several possible covariates and outcomes. Step-wise approaches enable automating tasks by developing general tools (decreasing programmer input) and facilitating alternative designs. Macros improve upon the classic ‘one design, one data set’ perspective. Two case studies highlight tradeoffs in retrospective cohort studies (quasi-experiments) among sample size, length of follow-up, and the number of time periods. ResultsStudy 1: Step 1 calculated the number of mothers with a child placed in care during various index years. Taking 1 year before and after placement generated 5,991 eligible mothers; selecting 5 years before/after decreased the N to 2,281. Step 2 selected appropriate in-province residents. Step 3 handled missing covariates and outcomes, while Step 4 ran alternative designs. One example (of several) compared maternal mental health outcomes using 8 time periods (in 2 years) before/after the event with outcomes using 16 time periods (in 4 years) before/after. Besides showing increasing maternal problems, the 4-year follow-up sometimes produced different statistically significant periods than the 2-year follow-up. Study 2. Swedish/Canadian comparisons of mothers with children placed in foster care highlighted growing differences in maternal pharmaceutical use. Conclusion/ImplicationsPresenting design alternatives is straightforward and applicable across disciplines. Ongoing work is facilitating comparisons of ‘experimental’ and control groups. Literature-derived guidelines and simulation-based techniques should lead to better design decisions. Automated model assessment can help analyze robustness, statistical power, residuals, and bias, suggesting artificial intelligence approaches.

scholarly journals SHCal13 Southern Hemisphere Calibration, 0–50,000 Years cal BP

Radiocarbon ◽  
2013 ◽  
Vol 55 (4) ◽  
pp. 1889-1903 ◽  
Author(s):  
Alan G Hogg ◽  
Quan Hua ◽  
Paul G Blackwell ◽  
Mu Niu ◽  
Caitlin E Buck ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Calibration Curve ◽  
Younger Dryas ◽  
Autoregressive Process ◽  
Measured Data ◽  
Data Sets ◽  
Short Term ◽  
Data Set ◽  
Radiocarbon Calibration

The Southern Hemisphere SHCal04 radiocarbon calibration curve has been updated with the addition of new data sets extending measurements to 2145 cal BP and including the ANSTO Younger Dryas Huon pine data set. Outside the range of measured data, the curve is based upon the ern Hemisphere data sets as presented in IntCal13, with an interhemispheric offset averaging 43 ± 23 yr modeled by an autoregressive process to represent the short-term correlations in the offset.

scholarly journals Periodic Variation of Solar Flare Index for the Last Solar Cycle (Cycle 24)

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Atila Ozguc ◽  
Ali Kilcik ◽  
Volkan Sarp ◽  
Hülya Yeşilyaprak ◽  
Rıza Pektaş
Keyword(s):  
Solar Cycle ◽  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
Wavelet Transforms ◽  
Data Sets ◽  
Flare Activity ◽  
Data Set ◽  
Analysis Methods ◽  
Flare Index ◽  
Cycle 24

In this study, we used the flare index (FI) data taken from Kandilli Observatory for the period of 2009–2020. The data sets are analyzed in three categories as Northern Hemisphere, Southern Hemisphere, and total FI data sets. Total FI data set is obtained from the sum of Northern and Southern Hemispheric values. In this study, the periodic variations of abovementioned three categories FI data sets were investigated by using the MTM and Morlet wavelet analysis methods. The wavelet coherence (XWT) and cross wavelet (WTC) analysis methods were also performed between these data sets. As a result of our analysis, the following results were found: (1) long- and short-term periodicities ( 2048 ± 512 day and periodicities smaller than 62 days) exist in all data sets without any exception at least with 95 % confidence level; (2) all periodic variations were detected maximum during the solar cycle, while during the minima, no meaningful period is detected; (3) some periodicities have data preference that about 150 days Rieger period appears only in the whole data set and 682-, 204-, and 76.6-day periods appear only in the Northern Hemisphere data sets; (4) During the Solar Cycle 24, more flare activity is seen at the Southern Hemisphere, so the whole disk data periodicities are dominated by this hemisphere; (5) in general, there is a phase mixing between Northern and Southern Hemisphere FI data, except about 1024-day periodicity, and the best phase coherency is obtained between the Southern Hemisphere and total flare index data sets; (6) in case of the Northern and Southern Hemisphere FI data sets, there is no significant correlation between two continuous wavelet transforms, but the strongest correlation is obtained for the total FI and Southern Hemisphere data sets.

scholarly journals Extrapolation of Survival Curves Using Standard Parametric Models and Flexible Parametric Spline Models: Comparisons in Large Registry Cohorts with Advanced Cancer

2020 ◽  
pp. 0272989X2097895
Author(s):  
Jodi Gray ◽  
Thomas Sullivan ◽  
Nicholas R. Latimer ◽  
Amy Salter ◽  
Michael J. Sorich ◽  
...  
Keyword(s):  
Survival Data ◽  
Proportional Hazards ◽  
Small Cell ◽  
Parametric Models ◽  
Data Sets ◽  
Small Cell Lung ◽  
Data Set ◽  
Right Censored Data ◽  
Spline Models

Background It is often important to extrapolate survival estimates beyond the limited follow-up times of clinical trials. Extrapolated survival estimates can be highly sensitive to model choice; thus, appropriate model selection is crucial. Flexible parametric spline models have been suggested as an alternative to standard parametric models; however, their ability to extrapolate is not well understood. Aim To determine how well standard parametric and flexible parametric spline models predict survival when fitted to registry cohorts with artificially right-censored follow-up times. Methods Adults with advanced breast, colorectal, small cell lung, non–small cell lung, or pancreatic cancer with a potential follow-up time of 10 y were selected from the SEER 1973–2015 registry data set. Patients were classified into 15 cohorts by cancer and age group at diagnosis (18–59, 60–69, 70+ y). Follow-up times for each cohort were right censored at 20%, 35%, and 50% survival. Standard parametric models (exponential, Weibull, Gompertz, log-logistic, log-normal, generalized gamma) and spline models (proportional hazards, proportional odds, normal/probit) were fitted to the 10-y data set and the 3 right-censored data sets. Predicted 10-y restricted mean survival time and percentage surviving at 10 y were compared with the observed values. Results Across all data sets, the spline odds and spline normal models most frequently gave accurate predictions of 10-y survival outcomes. Visually, spline models tended to demonstrate better fit to the observed hazard functions than standard parametric models, both in the censored and 10-y data. Conclusions In these cohorts, where there was little uncertainty in the observed data, the spline models performed well when extrapolating beyond the observed data. Spline models should be routinely included in the set of models that are fitted when extrapolating cancer survival data.

scholarly journals Trends and emissions of six perfluorocarbons in the Northern Hemisphere and Southern Hemisphere

2020 ◽  
Vol 20 (8) ◽  
pp. 4787-4807 ◽  
Author(s):  
Elise S. Droste ◽  
Karina E. Adcock ◽  
Matthew J. Ashfold ◽  
Charles Chou ◽  
Zoë Fleming ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Hemisphere ◽  
Data Sets ◽  
Emission Rates ◽  
Data Set ◽  
Air Samples ◽  
Mixing Ratios ◽  
Co2 Equivalent ◽  
First Time ◽  
Cape Grim

Abstract. Perfluorocarbons (PFCs) are potent greenhouse gases with global warming potentials up to several thousand times greater than CO2 on a 100-year time horizon. The lack of any significant sinks for PFCs means that they have long atmospheric lifetimes of the order of thousands of years. Anthropogenic production is thought to be the only source for most PFCs. Here we report an update on the global atmospheric abundances of the following PFCs, most of which have for the first time been analytically separated according to their isomers: c-octafluorobutane (c-C4F8), n-decafluorobutane (n-C4F10), n-dodecafluoropentane (n-C5F12), n-tetradecafluorohexane (n-C6F14), and n-hexadecafluoroheptane (n-C7F16). Additionally, we report the first data set on the atmospheric mixing ratios of perfluoro-2-methylpentane (i-C6F14). The existence and significance of PFC isomers have not been reported before, due to the analytical challenges of separating them. The time series spans a period from 1978 to the present. Several data sets are used to investigate temporal and spatial trends of these PFCs: time series of air samples collected at Cape Grim, Australia, from 1978 to the start of 2018; a time series of air samples collected between July 2015 and April 2017 at Tacolneston, UK; and intensive campaign-based sampling collections from Taiwan. Although the remote “background” Southern Hemispheric Cape Grim time series indicates that recent growth rates of most of these PFCs are lower than in the 1990s, we continue to see significantly increasing mixing ratios that are between 6 % and 27 % higher by the end of 2017 compared to abundances measured in 2010. Air samples from Tacolneston show a positive offset in PFC mixing ratios compared to the Southern Hemisphere baseline. The highest mixing ratios and variability are seen in air samples from Taiwan, which is therefore likely situated much closer to PFC sources, confirming predominantly Northern Hemispheric emissions for most PFCs. Even though these PFCs occur in the atmosphere at levels of parts per trillion molar or less, their total cumulative global emissions translate into 833 million metric tonnes of CO2 equivalent by the end of 2017, 23 % of which has been emitted since 2010. Almost two-thirds of the CO2 equivalent emissions within the last decade are attributable to c-C4F8, which currently also has the highest emission rates that continue to grow. Sources of all PFCs covered in this work remain poorly constrained and reported emissions in global databases do not account for the abundances found in the atmosphere.

scholarly journals High-Precision Radiocarbon Measurements of Tree-Ring Dated Wood from New Zealand: 195 Bc–Ad 995

Radiocarbon ◽  
2011 ◽  
Vol 53 (3) ◽  
pp. 529-542 ◽  
Author(s):  
Alan Hogg ◽  
Jonathan Palmer ◽  
Gretel Boswijk ◽  
Chris Turney
Keyword(s):  
New Zealand ◽  
Southern Hemisphere ◽  
Calibration Curve ◽  
Geographic Location ◽  
Temporal Variations ◽  
Time Interval ◽  
Data Sets ◽  
Data Set ◽  
Data Points ◽  
Lagarostrobos Franklinii

The best means for correcting Southern Hemisphere (SH) radiocarbon measurements, which are significantly influenced by temporal variations in the interhemispheric offset, is by the construction of a SH-specific calibration curve from dendrochronologically dated wood. We present here decadal 14C measurements on dendrochronologically secure New Zealand kauri (Agathis australis), covering the period 195 BC–AD 995, extending the range of calibration measurements from New Zealand tree rings to more than 2 millennia.Recently published Tasmanian huon pine (Lagarostrobos franklinii) data for the interval 165 BC to AD 1095 measured at the Center for Accelerator Mass Spectrometry (CAMS) have underestimated standard errors, which need to be re-assessed before the data can be considered for a Southern Hemisphere calibration curve update. The CAMS huon data, unlike the Waikato kauri data presented here, show a significant reduction in the SH offset for the interval AD 775–855. Although these data points are being checked, it is unlikely this represents a temporal geographic location-dependent offset. With re-assessed errors, the huon data set from 165 BC to AD 995 closely matches the new kauri data, with the combined data sets producing a mean interhemispheric offset with IntCal09 of 44 ± 17 yr for the time interval 195 BC–AD 1845. This SH offset is lower than the modeled offset of 55–58 yr used in the construction of SHCal04, and we recommend the lower value be used in future SHCal updates. Although there is an apparent increase in higher frequency events in the SH offset (NZ kauri plus Tasmanian huon) from 200 BC–AD 1000, the reason for this remains unclear.

scholarly journals SCIAMACHY WFM-DOAS XCO<sub>2</sub>: comparison with CarbonTracker XCO<sub>2</sub> focusing on aerosols and thin clouds

2012 ◽  
Vol 5 (8) ◽  
pp. 1935-1952 ◽  
Author(s):  
J. Heymann ◽  
O. Schneising ◽  
M. Reuter ◽  
M. Buchwitz ◽  
V. V. Rozanov ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Weighting Function ◽  
Optical Absorption Spectroscopy ◽  
Anthropogenic Activity ◽  
Data Sets ◽  
Data Set ◽  
Cloud Data ◽  
Temporal Correlations ◽  
Retrieval Errors ◽  
The Difference

Abstract. Carbon dioxide (CO2) is the most important greenhouse gas whose atmospheric loading has been significantly increased by anthropogenic activity leading to global warming. Accurate measurements and models are needed in order to reliably predict our future climate. This, however, has challenging requirements. Errors in measurements and models need to be identified and minimised. In this context, we present a comparison between satellite-derived column-averaged dry air mole fractions of CO2, denoted XCO2, retrieved from SCIAMACHY/ENVISAT using the WFM-DOAS (weighting function modified differential optical absorption spectroscopy) algorithm, and output from NOAA's global CO2 modelling and assimilation system CarbonTracker. We investigate to what extent differences between these two data sets are influenced by systematic retrieval errors due to aerosols and unaccounted clouds. We analyse seven years of SCIAMACHY WFM-DOAS version 2.1 retrievals (WFMDv2.1) using CarbonTracker version 2010. We investigate to what extent the difference between SCIAMACHY and CarbonTracker XCO2 are temporally and spatially correlated with global aerosol and cloud data sets. For this purpose, we use a global aerosol data set generated within the European GEMS project, which is based on assimilated MODIS satellite data. For clouds, we use a data set derived from CALIOP/CALIPSO. We find significant correlations of the SCIAMACHY minus CarbonTracker XCO2 difference with thin clouds over the Southern Hemisphere. The maximum temporal correlation we find for Darwin, Australia (r2 = 54%). Large temporal correlations with thin clouds are also observed over other regions of the Southern Hemisphere (e.g. 43% for South America and 31% for South Africa). Over the Northern Hemisphere the temporal correlations are typically much lower. An exception is India, where large temporal correlations with clouds and aerosols have also been found. For all other regions the temporal correlations with aerosol are typically low. For the spatial correlations the picture is less clear. They are typically low for both aerosols and clouds, but depending on region and season, they may exceed 30% (the maximum value of 46% has been found for Darwin during September to November). Overall we find that the presence of thin clouds can potentially explain a significant fraction of the difference between SCIAMACHY WFMDv2.1 XCO2 and CarbonTracker over the Southern Hemisphere. Aerosols appear to be less of a problem. Our study indicates that the quality of the satellite derived XCO2 will significantly benefit from a reduction of scattering related retrieval errors at least for the Southern Hemisphere.

The First Year Experience of Ankara Child Follow up Center

2012 ◽  
Author(s):  
Fadime Yuksel ◽  
Safa Celik ◽  
Filiz Daskafa ◽  
Nilufer Keser ◽  
Elif Odabas ◽  
...  
Keyword(s):  
First Year Experience ◽  
First Year
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