LOWER EXTREMITY KINEMATICS DURING HIGH SPEED TREADMILL SPRINTING OVER A RANGE OF VELOCITIES

A kinematic analysis of selected variables was completed during high speed treadmill sprinting over a range of velocities. Six power/speed athletes experienced at sprinting on a treadmill performed trials at 60%, 70%, 80%, 90%, and 95% of their previous individual maximum velocity, with video data collected in the sagittal plane at 60 Hz. The results indicated that there were significant differences among the variables studied, particularly at slower velocities. Peak hip extension and peak knee flexion showed no differences across test conditions. As the treadmill velocity approached a maximum, mechanical breakdown was seen in a decreased maximum hip flexion angle and peak hip flexion angular velocity, suggesting that velocities greater than 90% velocity should be used selectively during treadmill training

Derivation of tropospheric methane from TCCON CH₄ and HF total column observations

The Total Carbon Column Observing Network (TCCON) is a global ground-based network of Fourier transform spectrometers that produce precise measurements of column-averaged dry-air mole fractions of atmospheric methane (CH₄). Temporal variability in the total column of CH₄ due to stratospheric dynamics obscures fluctuations and trends driven by tropospheric transport and local surface fluxes that are critical for understanding CH₄ sources and sinks. We reduce the contribution of stratospheric variability from the total column average by subtracting an estimate of the stratospheric CH₄ derived from simultaneous measurements of hydrogen fluoride (HF). HF provides a proxy for stratospheric CH₄ because it is strongly correlated to CH₄ in the stratosphere, has an accurately known tropospheric abundance (of zero), and is measured at most TCCON stations. The stratospheric partial column of CH₄ is calculated as a function of the zonal and annual trends in the relationship between CH₄ and HF in the stratosphere, which we determine from ACE-FTS satellite data. We also explicitly take into account the CH₄ column averaging kernel to estimate the contribution of stratospheric CH₄ to the total column. The resulting tropospheric CH₄ columns are consistent with in situ aircraft measurements and augment existing observations in the troposphere

Arctic stratospheric dehydration – Part 2: Microphysical modeling

Large areas of synoptic-scale ice PSCs (polar stratospheric clouds) distinguished the Arctic winter 2009/2010 from other years and revealed unprecedented evidence of water redistribution in the stratosphere. A unique snapshot of water vapor repartitioning into ice particles was obtained under extremely cold Arctic conditions with temperatures around 183 K. Balloon-borne, aircraft and satellite-based measurements suggest that synoptic-scale ice PSCs and concurrent reductions and enhancements in water vapor are tightly linked with the observed de- and rehydration signatures, respectively. In a companion paper (Part 1), water vapor and aerosol backscatter measurements from the RECONCILE (Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions) and LAPBIAT-II (Lapland Atmosphere–Biosphere Facility) field campaigns have been analyzed in detail. This paper uses a column version of the Zurich Optical and Microphysical box Model (ZOMM) including newly developed NAT (nitric acid trihydrate) and ice nucleation parameterizations. Particle sedimentation is calculated in order to simulate the vertical redistribution of chemical species such as water and nitric acid. Despite limitations given by wind shear and uncertainties in the initial water vapor profile, the column modeling unequivocally shows that (1) accounting for small-scale temperature fluctuations along the trajectories is essential in order to reach agreement between simulated optical cloud properties and observations, and (2) the use of recently developed heterogeneous ice nucleation parameterizations allows the reproduction of the observed signatures of de- and rehydration. Conversely, the vertical redistribution of water measured cannot be explained in terms of homogeneous nucleation of ice clouds, whose particle radii remain too small to cause significant dehydration

The imprint of stratospheric transport on column-averaged methane

Model simulations of column-averaged methane mixing ratios (XCH4) are extensively used for inverse estimates of methane (CH4) emissions from atmospheric measurements. Our study shows that virtually all chemical transport models (CTM) used for this purpose are affected by stratospheric model-transport errors. We quantify the impact of such model transport errors on the simulation of stratospheric CH4 concentrations via an a posteriori correction method. This approach compares measurements of the mean age of air with modeled age and expresses the difference in terms of a correction to modeled stratospheric CH4 mixing ratios. We find age differences up to ~ 3 years yield to a bias in simulated CH4 of up to 250 parts per billion (ppb). Comparisons between model simulations and ground-based XCH4 observations from the Total Carbon Column Network (TCCON) reveal that stratospheric model-transport errors cause biases in XCH4 of ~ 20 ppb in the midlatitudes and ~ 27 ppb in the arctic region. Improved overall as well as seasonal model-observation agreement in XCH4 suggests that the proposed, age-of-air-based stratospheric correction is reasonable. The latitudinal model bias in XCH4 is supposed to reduce the accuracy of inverse estimates using satellite-derived XCH4 data. Therefore, we provide an estimate of the impact of stratospheric model-transport errors in terms of CH4 flux errors. Using a one-box approximation, we show that average model errors in stratospheric transport correspond to an overestimation of CH4 emissions by ~ 40 % (~ 7 Tg yr−1) for the arctic, ~ 5 % (~ 7 Tg yr−1) for the northern, and ~ 60 % (~ 7 Tg yr−1) for the southern hemispheric mid-latitude region. We conclude that an improved modeling of stratospheric transport is highly desirable for the joint use with atmospheric XCH4 observations in atmospheric inversions

Derivation of tropospheric methane from TCCON CH₄ and HF total column observations

The Total Carbon Column Observing Network (TCCON) is a global ground-based network of Fourier transform spectrometers that produce precise measurements of column-averaged dry-air mole fractions of atmospheric methane (CH₄). Temporal variability in the total column of CH₄ due to stratospheric dynamics obscures fluctuations and trends driven by tropospheric transport and local surface fluxes that are critical for understanding CH₄ sources and sinks. We reduce the contribution of stratospheric variability from the total column average by subtracting an estimate of the stratospheric CH₄ derived from simultaneous measurements of hydrogen fluoride (HF). HF provides a proxy for stratospheric CH₄ because it is strongly correlated to CH₄ in the stratosphere, has an accurately known tropospheric abundance (of zero), and is measured at most TCCON stations. The stratospheric partial column of CH₄ is calculated as a function of the zonal and annual trends in the relationship between CH₄ and HF in the stratosphere, which we determine from ACE-FTS satellite data. We also explicitly take into account the CH₄ column averaging kernel to estimate the contribution of stratospheric CH₄ to the total column. The resulting tropospheric CH₄ columns are consistent with in situ aircraft measurements and augment existing observations in the troposphere

Forecasting global atmospheric CO_2

A new global atmospheric carbon dioxide (CO_2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO_2 forecasting system is that the land surface, including vegetation CO_2 fluxes, is modelled online within the IFS. Other CO_2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO_2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO_2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO_2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO_2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO_2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO_2 fluxes also lead to accumulating errors in the CO_2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO_2 fluxes compared to total optimized fluxes and the atmospheric CO_2 compared to observations. The largest biases in the atmospheric CO_2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO_2 analyses based on the assimilation of CO_2 products retrieved from satellite measurements and CO_2 in situ observations, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO_2 forecast will be reduced. Improvements in the CO_2 forecast are also expected with the continuous developments in the operational IFS

Spatial distributions of XCO2seasonal cycle amplitude and phase over northern high-latitude regions

Satellite-based observations of atmospheric carbon dioxide (CO$_{2}$) provide measurements in remote regions, such as the biologically sensitive but undersampled northern high latitudes, and are progressing toward true global data coverage. Recent improvements in satellite retrievals of total column-averaged dry air mole fractions of CO$_{2}$ (X$_{CO_{2}}$) from the NASA Orbiting Carbon Observatory 2 (OCO-2) have allowed for unprecedented data coverage of northern high-latitude regions, while maintaining acceptable accuracy and consistency relative to ground-based observations, and finally providing sufficient data in spring and autumn for analysis of satellite-observed X$_{CO_{2}}$ seasonal cycles across a majority of terrestrial northern high-latitude regions. Here, we present an analysis of X$_{CO_{2}}$ seasonal cycles calculated from OCO-2 data for temperate, boreal, and tundra regions, subdivided into 5∘ latitude by 20∘ longitude zones. We quantify the seasonal cycle amplitudes (SCAs) and the annual half drawdown day (HDD). OCO-2 SCAs are in good agreement with ground-based observations at five high-latitude sites, and OCO-2 SCAs show very close agreement with SCAs calculated for model estimates of X$_{CO_{2}}$ from the Copernicus Atmosphere Monitoring Services (CAMS) global inversion-optimized greenhouse gas flux model v19r1 and the CarbonTracker2019 model (CT2019B). Model estimates of X$_{CO_{2}}$ from the GEOS-Chem CO$_{2}$ simulation version 12.7.2 with underlying biospheric fluxes from CarbonTracker2019 (GC-CT2019) yield SCAs of larger magnitude and spread over a larger range than those from CAMS, CT2019B, or OCO-2; however, GC-CT2019 SCAs still exhibit a very similar spatial distribution across northern high-latitude regions to that from CAMS, CT2019B, and OCO-2. Zones in the Asian boreal forest were found to have exceptionally large SCA and early HDD, and both OCO-2 data and model estimates yield a distinct longitudinal gradient of increasing SCA from west to east across the Eurasian continent. In northern high-latitude regions, spanning latitudes from 47 to 72∘ N, longitudinal gradients in both SCA and HDD are at least as pronounced as latitudinal gradients, suggesting a role for global atmospheric transport patterns in defining spatial distributions of X$_{CO_{2}}$ seasonality across these regions. GEOS-Chem surface contact tracers show that the largest X$_{CO_{2}}$ SCAs occur in areas with the greatest contact with land surfaces, integrated over 15–30 d. The correlation of XCO2 SCA with these land surface contact tracers is stronger than the correlation of X$_{CO_{2}}$ SCA with the SCA of CO$_{2}$ fluxes or the total annual CO$_{2}$ flux within each 5∘ latitude by 20∘ longitude zone. This indicates that accumulation of terrestrial CO$_{2}$ flux during atmospheric transport is a major driver of regional variations in X$_{CO_{2}}$ SCA

Nitric acid trihydrate nucleation and denitrification in the Arctic stratosphere

Nitric acid trihydrate (NAT) particles in the polar stratosphere have been shown to be responsible for vertical redistribution of reactive nitrogen (NO_y). Recent observations by Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the CALIPSO satellite have been explained in terms of heterogeneous nucleation of NAT on foreign nuclei, revealing this to be an important formation pathway for the NAT particles. In state of the art global- or regional-scale models, heterogeneous NAT nucleation is currently simulated in a very coarse manner using a constant, saturation-independent nucleation rate. Here we present first simulations for the Arctic winter 2009/2010 applying a new saturation-dependent parametrisation of heterogeneous NAT nucleation rates within the Chemical Lagrangian Model of the Stratosphere (CLaMS). The simulation shows good agreement of chemical trace species with in situ and remote sensing observations. The simulated polar stratospheric cloud (PSC) optical properties agree much better with CALIOP observations than those simulated with a constant nucleation rate model. A comparison of the simulated particle size distributions with observations made using the Forward Scattering Spectrometer Probe (FSSP) aboard the high altitude research aircraft Geophysica, shows that the model reproduces the observed size distribution, except for the very largest particles above 15 μm diameter. The vertical NO_y redistribution caused by the sedimentation of the NAT particles, in particular the denitrification and nitrification signals observed by the ACE-FTS satellite instrument and the in situ SIOUX instrument aboard the Geophysica, are reproduced by the improved model, and a small improvement with respect to the constant nucleation rate model is found

Use of automatic radiosonde launchers to measure temperature and humidity profiles from the GRUAN perspective

In the last two decades, technological progress has not only seen improvements to the quality of atmospheric upper-air observations but also provided the opportunity to design and implement automated systems able to replace measurement procedures typically performed manually. Radiosoundings, which remain one of the primary data sources for weather and climate applications, are still largely performed around the world manually, although increasingly fully automated upper-air observations are used, from urban areas to the remotest locations, which minimize operating costs and challenges in performing radiosounding launches. This analysis presents a first step to demonstrating the reliability of the automatic radiosonde launchers (ARLs) provided by Vaisala, Meteomodem and Meisei. The metadata and datasets collected by a few existing ARLs operated by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) certified or candidate sites (Sodankylä, Payerne, Trappes, Potenza) have been investigated and a comparative analysis of the technical performance (i.e. manual versus ARL) is reported. The performance of ARLs is evaluated as being similar or superior to those achieved with the traditional manual launches in terms of percentage of successful launches, balloon burst and ascent speed. For both temperature and relative humidity, the ground-check comparisons showed a negative bias of a few tenths of a degree and % RH, respectively. Two datasets of parallel soundings between manual and ARL-based measurements, using identical sonde models, provided by Sodankylä and Faa'a stations, showed mean differences between the ARL and manual launches smaller than ±0.2 K up to 10 hPa for the temperature profiles. For relative humidity, differences were smaller than 1 % RH for the Sodankylä dataset up to 300 hPa, while they were smaller than 0.7 % RH for Faa'a station. Finally, the observation-minus-background (O–B) mean and root mean square (rms) statistics for German RS92 and RS41 stations, which operate a mix of manual and ARL launch protocols, calculated using the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model, are very similar, although RS41 shows larger rms(O–B) differences for ARL stations, in particular for temperature and wind. A discussion of the potential next steps proposed by GRUAN community and other parties is provided, with the aim to lay the basis for the elaboration of a strategy to fully demonstrate the value of ARLs and guarantee that the provided products are traceable and suitable for the creation of GRUAN data products