The Effects of Ladder Training on Sprint and Change of Direction Performance

Topics in Exercise Science and Kinesiology Volume 3: Issue 1, Article 7, 2022. Ladder training is a form of multidirectional lower limb plyometric training utilized by coaches and athletes in a variety of sports. The purpose of this study was to examine the effects of ladder training (LT) on sprint (20-m) and change of direction (COD) (L-drill) kinematics. Fourteen NCAA D-2 Basketball players were matched on baseline performance rankings and randomly assigned to a LT (n = 7) or conventional training (CT) (n = 7) group. The LT group performed all the CT exercises with the addition of 25-35 minutes of LT performed 3 times per week, for 4 weeks. Within-group analyses showed significant improvements (p \u3c 0.001) in 20-m sprint performance from pretest to posttest in LT (+6.71%) and CT (+2.16%). No statistically significant difference was found in COD performance. Significant enhancements (p \u3c 0.005) were found in stride frequency from pretest to posttest for 20-m sprint and COD as a result of LT (+13.58%, and +12.26%) and CT (+0.97%, and -2.33%), respectively. LT resulted in substantially better results (between-group changes) in both the 20-m sprint (ES = 1.45) and COD test (ES = 0.97). Furthermore, LT resulted in substantially greater enhancements in stride frequency (ES = 2.43, 1.65), and ground contact time (ES = 1.82, 1.25) in the 20-m sprint and COD performance respectively. LT may be more effective than CT in improving performance and kinematics. LT should be implemented as a warm up or neural priming exercise to induce improvements in stride frequency and ground contact time

Observed Hemispheric Asymmetry in Stratospheric Transport Trends From 1994 to 2018

©2020. American Geophysical Union. All Rights Reserved. Total columns of the trace gases nitric acid (HNO3) and hydrogen chloride (HCl) are sensitive to variations in the lower stratospheric age of air, a quantity that describes transport time scales in the stratosphere. Analyses of HNO3 and HCl columns from the Network for the Detection of Atmospheric Composition Change panning 77°S to 79°N have detected changes in the extratropical stratospheric transport circulation from 1994 to 2018. The HNO3 and HCl analyses combined with the age of air from a simulation using the MERRA2 reanalysis show that the Southern Hemisphere lower stratosphere has become 1 month/decade younger relative to the Northern Hemisphere, largely driven by the Southern Hemisphere transport circulation. The analyses reveal multiyear anomalies with a 5- to 7-year period driven by interactions between the circulation and the quasi-biennial oscillation in tropical winds. This hitherto unrecognized variability is large relative to hemispheric transport trends and may bias ozone trend regressions

Anomalies of O3_3, CO, C2_2H2_2, H2_2CO, and C2_2H6_6 detected with multiple ground-based Fourier-transform infrared spectrometers and assessed with model simulation in 2020: COVID-19 lockdowns versus natural variability

Anomalies of tropospheric columns of ozone (O$_3$), carbon monoxide (CO), acetylene (C$_2$H$_2$), formaldehyde (H$_2$CO), and ethane (C$_2$H$_6$) are quantified during the 2020 stringent COVID-19 world-wide lockdown using multiple ground-based Fourier-transform infrared spectrometers covering urban and remote conditions. We applied an exponential smoothing forecasting approach to the data sets to estimate business-as-usual values for 2020, which are then contrasted with actual observations. The Community Atmosphere Model with chemistry (CAM-chem) is used to simulate the same gases using lockdown-adjusted and business-as-usual emissions. The role of meteorology, or natural variability, is assessed with additional CAM-chem simulations. The tropospheric column of O$_3$ declined between March and May 2020 for most sites with a mean decrease of 9.2% ± 4.7%. Simulations reproduce these anomalies, especially under background conditions where natural variability explains up to 80% of the decline for sites in the Northern Hemisphere. While urban sites show a reduction between 1% and 12% in tropospheric CO, the remote sites do not show a significant change. Overall, CAM-chem simulations capture the magnitude of the anomalies and in many cases natural variability and lockdowns have opposite effects. We further used the long-term record of the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument to capture global anomalies of CO. Reductions of CO vary highly across regions but North America and Europe registered lower values in March 2020. The absence of CO reduction in April and May, concomitant with reductions of anthropogenic emissions, is explained by a negative anomaly in the hydroxyl radical (OH) found with CAM-chem. The implications of these findings are discussed for methane (CH$_4$), which shows a positive lifetime anomaly during the COVID-19 lockdown period. The fossil fuel combustion by-product tracer C2H2 shows a mean drop of 13.6% ± 8.3% in urban Northern Hemisphere sites due to the reduction in emissions and in some sites exacerbated by natural variability. For some sites with anthropogenic influence there is a decrease in C$_2$H$_6$. The simulations capture the anomalies but the main cause may be related to natural variability. H$_2$CO declined during the stringent 2020 lockdown in all urban sites explained by reductions in emissions of precursors

Bias correction of OMI HCHO columns based on FTIR and aircraft measurements and impact on top-down emission estimates

Spaceborne formaldehyde (HCHO) measurements constitute an excellent proxy for the sources of non-methane volatile organic compounds (NMVOCs). Past studies suggested substantial overestimations of NMVOC emissions in state-of-the-art inventories over major source regions. Here, the QA4ECV (Quality Assurance for Essential Climate Variables) retrieval of HCHO columns from OMI (Ozone Monitoring Instrument) is evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide and (2) aircraft in situ HCHO concentration measurements from campaigns conducted over the USA during 2012–2013. Both validation exercises show that OMI underestimates high columns and overestimates low columns. The linear regression of OMI and aircraft-based columns gives Ω$_{OMI}$=0,651 Ω$_{airc}$+2,95 x 10$^{15}$, molec. cm$^{-2}$ , with Ω$_{OMI}$ and Ω$_{airc}$ the OMI and aircraft-derived vertical columns, whereas the regression of OMI and FTIR data gives Ω$_{OMI}$= 6,59 Ω$_{FTIR}$ + 2.02 x 10$^{15}$, molec. cm$^{-2}$ . Inverse modelling of NMVOC emissions with a global model based on OMI columns corrected for biases based on those relationships leads to much-improved agreement against FTIR data and HCHO concentrations from 11 aircraft campaigns. The optimized global isoprene emissions ($\sim$ 445 Tgyr$^{-1}$) are 25 % higher than those obtained without bias correction. The optimized isoprene emissions bear both striking similarities and differences with recently published emissions based on spaceborne isoprene columns from the CrIS (Cross-track Infrared Sounder) sensor. Although the interannual variability of OMI HCHO columns is well understood over regions where biogenic emissions are dominant, and the HCHO trends over China and India clearly reflect anthropogenic emission changes, the observed HCHO decline over the southeastern USA remains imperfectly elucidated

Characterization and potential for reducing optical resonances in Fourier transform infrared spectrometers of the Network for the Detection of Atmospheric Composition Change (NDACC)

Although optical components in Fourier transform infrared (FTIR) spectrometers are preferably wedged, in practice, infrared spectra typically suffer from the effects of optical resonances (“channeling”) affecting the retrieval of weakly absorbing gases. This study investigates the level of channeling of each FTIR spectrometer within the Network for the Detection of Atmospheric Composition Change (NDACC).Part of this work was supported by Ministerio de Economía y Competitividad from Spain (project INMENSE no. CGL2016-80688-P). The Altzomoni site UNAM (DGAPA (grant nos. IN111418 and IN107417)) was supported by the CONACYT (grant no. 290589) and PASPA. This work has been supported by the Federal Ministry of Education and Research (BMBF) Germany in the project TroStra (grant no. 01LG1904A)

TROPOMI–Sentinel-5 Precursor formaldehyde validation using an extensive network of ground-based Fourier-transform infrared stations

TROPOMI (the TROPOspheric Monitoring Instrument), on board the Sentinel-5 Precursor (S5P) satellite, has been monitoring the Earth\u27s atmosphere since October 2017 with an unprecedented horizontal resolution (initially 7 km$^{2}$×3.5 km$^{2}$, upgraded to 5.5 km$^{2}$×3.5 km$^{2}$ in August 2019). Monitoring air quality is one of the main objectives of TROPOMI; it obtains measurements of important pollutants such as nitrogen dioxide, carbon monoxide, and formaldehyde (HCHO). In this paper we assess the quality of the latest HCHO TROPOMI products versions 1.1.(5-7), using ground-based solar-absorption FTIR (Fourier-transform infrared) measurements of HCHO from 25 stations around the world, including high-, mid-, and low-latitude sites. Most of these stations are part of the Network for the Detection of Atmospheric Composition Change (NDACC), and they provide a wide range of observation conditions, from very clean remote sites to those with high HCHO levels from anthropogenic or biogenic emissions. The ground-based HCHO retrieval settings have been optimized and harmonized at all the stations, ensuring a consistent validation among the sites. In this validation work, we first assess the accuracy of TROPOMI HCHO tropospheric columns using the median of the relative differences between TROPOMI and FTIR ground-based data (BIAS). The pre-launch accuracy requirements of TROPOMI HCHO are 40 %–80 %. We observe that these requirements are well reached, with the BIAS found below 80 % at all the sites and below 40 % at 20 of the 25 sites. The provided TROPOMI systematic uncertainties are well in agreement with the observed biases at most of the stations except for the highest-HCHO-level site, where it is found to be underestimated. We find that while the BIAS has no latitudinal dependence, it is dependent on the HCHO concentration levels: an overestimation (+26±5 %) of TROPOMI is observed for very low HCHO levels (8.0×10$^{15}$ molec. cm$^{-2}$). This demonstrates the great value of such a harmonized network covering a wide range of concentration levels, the sites with high HCHO concentrations being crucial for the determination of the satellite bias in the regions of emissions and the clean sites allowing a small TROPOMI offset to be determined. The wide range of sampled HCHO levels within the network allows the robust determination of the significant constant and proportional TROPOMI HCHO biases (TROPOMI =+1.10±0.05 ×10$^{15}$+0.64±0.03 × FTIR; in molecules per square centimetre). Second, the precision of TROPOMI HCHO data is estimated by the median absolute deviation (MAD) of the relative differences between TROPOMI and FTIR ground-based data. The clean sites are especially useful for minimizing a possible additional collocation error. The precision requirement of 1.2×10$^{16}$ molec. cm$^{-2}$ for a single pixel is reached at most of the clean sites, where it is found that the TROPOMI precision can even be 2 times better (0.5–0.8×10$^{15}$ molec. cm$^{-2}$ for a single pixel). However, we find that the provided TROPOMI random uncertainties may be underestimated by a factor of 1.6 (for clean sites) to 2.3 (for high HCHO levels). The correlation is very good between TROPOMI and FTIR data (R=0.88 for 3 h mean coincidences; R=0.91 for monthly means coincidences). Using about 17 months of data (from May 2018 to September 2019), we show that the TROPOMI seasonal variability is in very good agreement at all of the FTIR sites. The FTIR network demonstrates the very good quality of the TROPOMI HCHO products, which is well within the pre-launch requirements for both accuracy and precision. This paper makes suggestions for the refinement of the TROPOMI random uncertainty budget and TROPOMI quality assurance values for a better filtering of the remaining outliers

NDACC harmonized formaldehyde time-series from 21 FTIR stations covering a wide range of column abundances

Among the more than 20 ground-based FTIR (Fourier transform infrared) stations currently operating around the globe, only a few have provided formaldehyde (HCHO) total column time series until now. Although several independent studies have shown that the FTIR measurements can provide formaldehyde total columns with good precision, the spatial coverage has not been optimal for providing good diagnostics for satellite or model validation. Furthermore, these past studies used different retrieval settings, and biases as large as 50 % can be observed in the HCHO total columns depending on these retrieval choices, which is also a weakness for validation studies combining data from different ground-based stations. For the present work, the HCHO retrieval settings have been optimized based on experience gained from past studies and have been applied consistently at the 21 participating stations. Most of them are either part of the Network for the Detection of Atmospheric Composition Change (NDACC) or under consideration for membership. We provide the harmonized settings and a characterization of the HCHO FTIR products. Depending on the station, the total systematic and random uncertainties of an individual HCHO total column measurement lie between 12 % and 27 % and between 1 and 11×1014 molec cm−2, respectively. The median values among all stations are 13 % and 2.9×1014 molec cm−2 for the total systematic and random uncertainties. This unprecedented harmonized formaldehyde data set from 21 ground-based FTIR stations is presented and its comparison with a global chemistry transport model shows consistency in absolute values as well as in seasonal cycles. The network covers very different concentration levels of formaldehyde, from very clean levels at the limit of detection (few 1013 molec cm−2) to highly polluted levels (7×1016 molec cm−2). Because the measurements can be made at any time during daylight, the diurnal cycle can be observed and is found to be significant at many stations. These HCHO time series, some of them starting in the 1990s, are crucial for past and present satellite validation and will be extended in the coming years for the next generation of satellite missions.This study has been supported by the ESA PRODEX project TROVA (2016–2018) funded by the Belgian Science Policy Office (Belspo)

NDACC harmonized formaldehyde time series from 21 FTIR stations covering a wide range of column abundances

Among the more than 20 ground-based FTIR (Fourier transform infrared) stations currently operating around the globe, only a few have provided formaldehyde (HCHO) total column time series until now. Although several independent studies have shown that the FTIR measurements can provide formaldehyde total columns with good precision, the spatial coverage has not been optimal for providing good diagnostics for satellite or model validation. Furthermore, these past studies used different retrieval settings, and biases as large as 50% can be observed in the HCHO total columns depending on these retrieval choices, which is also a weakness for validation studies combining data from different ground-based stations. For the present work, the HCHO retrieval settings have been optimized based on experience gained from past studies and have been applied consistently at the 21 participating stations. Most of them are either part of the Network for the Detection of Atmospheric Composition Change (NDACC) or under consideration for membership. We provide the harmonized settings and a characterization of the HCHO FTIR products. Depending on the station, the total systematic and random uncertainties of an individual HCHO total column measurement lie between 12% and 27% and between 1 and 11x1014 moleccm-2, respectively. The median values among all stations are 13% and 2.9x1014 moleccm-2 for the total systematic and random uncertainties. This unprecedented harmonized formaldehyde data set from 21 ground-based FTIR stations is presented and its comparison with a global chemistry transport model shows consistency in absolute values as well as in seasonal cycles. The network covers very different concentration levels of formaldehyde, from very clean levels at the limit of detection (few 1013moleccm-2) to highly polluted levels (7x1016moleccm-2). Because the measurements can be made at any time during daylight, the diurnal cycle can be observed and is found to be significant at many stations. These HCHO time series, some of them starting in the 1990s, are crucial for past and present satellite validation and will be extended in the coming years for the next generation of satellite missions

Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment

Nitrous oxide (N$_{2}$O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and a continuously increasing concentration due to human activities, making it an important gas to monitor. In this work, we present a new method to retrieve N$_{2}$O concentration profiles (with up to two degrees of freedom) from each cloud-free satellite observation by the Infrared Atmospheric Sounding Interferometer (IASI), using spectral micro-windows in the N$_{2}$O ν$_{3}$ band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N$_{2}$O profiles and integrated partial columns has been produced and validated with collocated ground-based Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) data. The importance of consistency in the ancillary data used for the retrieval for generating consistent time series has been demonstrated. The Nitrous Oxide Profiling from Infrared Radiances (NOPIR) N$_{2}$O partial columns are of very good quality, with a positive bias of 1.8 to 4% with respect to the ground-based data, which is less than the sum of uncertainties of the compared values. At high latitudes, the comparisons are a bit worse, due to either a known bias in the ground-based data, or to a higher uncertainty in both ground-based and satellite retrievals

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO