SPARC Data Initiative: climatology uncertainty assessment

The SPARC Data Initiative aims to produce trace gas climatologies for a number of species from a number of instruments. In order to properly compare these climatologies, and interpret differences between them, it is necessary to know the uncertainty in each calculated climatological mean field. The inhomogeneous and finite temporal-spatial sampling pattern of each instrument can lead to biases and uncertainties in the mean climatologies. Sampling which is unevenly weighted in time and space leads to biases between a data set's climatology and the truth. Furthermore, the systematic sampling patterns of some instruments may mean that uncertainties in mean fields calculated through traditional methods that assume random sampling may be inappropriate. We aim to address these issues through an exercise wherein high resolution chemical fields from a coupled Chemistry Climate Model are sub-sampled based on the sampling pattern of each instrument. Climatologies based on the sub-sampled data can be compared to those calculated with the full data set, in order to assess sampling biases. Furthermore, investigating the ensemble variability of climatologies based on subsampled fields will allow us to assess the proper methodology for estimating the uncertainty in climatological mean fields

Factors affecting symbolic and use adoption of local foods for consumers in Black Hawk County, Iowa

A local food system may be an alternative to the increasingly globalized and concentrated food market and a means to augment the availability of fresh foods, create economically viable options for farmers and enhance the health of local ecosystems. Consumers are a vital component of these systems. Insight into the decision-making process surrounding the purchase of local foods can aid in efforts to build thriving local food systems. Studies on consumer attitudes show that, in general, consumers are aware and supportive of local foods. Abstract or civic factors, such as concern for the environment or food safety, are often identified as predictive characteristics. Results conflict, however, as to the influence of traditional demographic factors. This study analyzed telephone survey data of consumers in Black Hawk County, Iowa. Causative factors are evaluated within the context of a two-phase decision-making model, which distinguishes symbolic adoption, the acceptance of an idea, from use adoption, the behavioral practice of the idea. Testable variables are grouped as either sociological/civic or expediency factors. Sociological/civic factors include social demographic variables in addition to civic concerns. Expediency factors include measures of time constraints and economic variables. It is hypothesized that sociological/civic factors are relatively more important than expediency factors in symbolic adoption of local foods, and these factors must interact positively with expediency factors for use adoption to occur. Final multivariate regression models are derived. A two-stage least squares approach is used to incorporate the final prediction model for symbolic adoption into that for use adoption. Results show that sociological/civic factors are relatively more important to symbolic adoption than expediency factors, particularly the civic factors of having concerns about food safety, following environmental issues and knowing a farmer. Use adoption is more likely if appropriate interactions with the expediency variables of price-consciousness and income take place. For symbolic adopters, lower price-consciousness and lower incomes lead to an increased tendency to buy local foods. For those not indicating symbolic adoption, opposite effects occur. For both groups, a complementary interplay with the sociological factors of educational level and knowing a farmer also influences use adoption

Spatial and temporal pulse shaping for lateral and depth resolved two-photon excited fluorescence contrast

We report combined temporal and spatial laser pulse shaping to perform lateral and depth dependent two-photon excited fluorescence of dyes. For generating the specific spatially and temporally phase tailored pulses a temporal pulse shaper and a subsequent spatial pulse shaper are employed. Simultaneous spatial and temporal shaping is presented for two-photon excited fluorescence by applying temporal third order phase functions on spatially different light field components. Moreover, the prospects of spatial shaping are demonstrated by applying various lateral two-photon fluorescence pattern. In particular, a depth dependent excitation of different dyes is performed which leads to a high axially resolved fluorescence contrast. The introduced spatial and temporal shaping technique provides new perspectives for biophotonic imaging applications

Community Supported Agriculture (CSA) in the Midwest United States: A regional characterization

This report analyzes information from a survey of nearly 150 CSAs in nine Midwestern states

Combined temporal and spatial laser pulse shaping for two-photon excited fluorescence contrast improvement

We report on combined simultaneous temporal and spatial laser pulse shaping by utilizing light polarization properties. Thereto, a setup comprising a temporal pulse shaper, a waveplate, and a spatial shaper was developed and characterized by comparison with simulations. This enables to simultaneously shape one polarization component temporally and spatially while the perpendicular polarization component is modified temporally. The spatially and temporally modulated light fields were recorded and visualized by suitable contour plots, which was particularly demonstrated for cylindrically symmetric pulse profiles. Moreover, temporally and spatially shaped pulses were applied for two-photon excited fluorescence of dyes. These measurements were conducted by scanning third order phase functions for specific spatial pulse components which yields an enhanced contrast difference between fluorescing dyes. The presented temporal and spatial shaping method of ultrashort laser pulses has a high potential for biophotonic applications

Modelling marine emissions and atmospheric distributions of halocarbons and dimethyl sulfide: the influence of prescribed water concentration vs. prescribed emissions

Marine-produced short-lived trace gases such as dibromomethane (CH2Br2), bromoform (CHBr3), methyliodide (CH3I) and dimethyl sulfide (DMS) significantly impact tropospheric and stratospheric chemistry. Describing their marine emissions in atmospheric chemistry models as accurately as possible is necessary to quantify their impact on ozone depletion and Earth's radiative budget. So far, marine emissions of trace gases have mainly been prescribed from emission climatologies, thus lacking the interaction between the actual state of the atmosphere and the ocean. Here we present simulations with the chemistry climate model EMAC (ECHAM5/MESSy Atmospheric Chemistry) with online calculation of emissions based on surface water concentrations, in contrast to directly prescribed emissions. Considering the actual state of the model atmosphere results in a concentration gradient consistent with model real-time conditions at the ocean surface and in the atmosphere, which determine the direction and magnitude of the computed flux. This method has a number of conceptual and practical benefits, as the modelled emission can respond consistently to changes in sea surface temperature, surface wind speed, sea ice cover and especially atmospheric mixing ratio. This online calculation could enhance, dampen or even invert the fluxes (i.e. deposition instead of emissions) of very short-lived substances (VSLS). We show that differences between prescribing emissions and prescribing concentrations (−28 % for CH2Br2 to +11 % for CHBr3) result mainly from consideration of the actual, time-varying state of the atmosphere. The absolute magnitude of the differences depends mainly on the surface ocean saturation of each particular gas. Comparison to observations from aircraft, ships and ground stations reveals that computing the air–sea flux interactively leads in most of the cases to more accurate atmospheric mixing ratios in the model compared to the computation from prescribed emissions. Calculating emissions online also enables effective testing of different air–sea transfer velocity (k) parameterizations, which was performed here for eight different parameterizations. The testing of these different k values is of special interest for DMS, as recently published parameterizations derived by direct flux measurements using eddy covariance measurements suggest decreasing k values at high wind speeds or a linear relationship with wind speed. Implementing these parameterizations reduces discrepancies in modelled DMS atmospheric mixing ratios and observations by a factor of 1.5 compared to parameterizations with a quadratic or cubic relationship to wind spee

Variability and long-term changes in tropical cold-point temperature and water vapor

The tropical tropopause layer (TTL) is the main gateway for air transiting from the troposphere to the stratosphere and therefore impacts the chemical composition of the stratosphere. In particular, the cold-point tropopause, where air parcels encounter their final dehydration, effectively controls the water vapor content of the lower stratosphere. Given the important role of stratospheric water vapor for the global energy budget, it is crucial to understand the long-term changes in cold-point temperature and their impact on water vapor trends. Our study uses Global Navigation Satellite System – Radio Occultation (GNSS-RO) data to show that there has been no overall cooling trend of the TTL over the past 2 decades, in contrast to observations prior to 2000. Instead, the cold point is warming, with the strongest trends of up to 0.7 K per decade during boreal winter and spring. The cold-point warming shows longitudinal asymmetries, with the smallest warming over the central Pacific and the largest warming over the Atlantic. These asymmetries are anticorrelated with patterns of tropospheric temperature trends, and regions of strongest cold-point warming are found to show slight cooling trends in the upper troposphere. Overall, the here-identified warming of the cold point is consistent with model predictions under global climate change, which attribute the warming trends to radiative effects. The seasonal signals and zonal asymmetries of the cold-point temperature and height trends might be related to dynamical responses to enhanced upper-tropospheric heating, changing convection, or trends in the stratospheric circulation. Water vapor observations in the TTL show mostly positive trends consistent with cold-point warming for 2004–2021. We find a decrease in the amplitude of the cold-point temperature seasonal cycle by ∼ 7 % driving a reduction in the seasonal cycle in 100 hPa water vapor by 5 %–6 %. Our analysis shows that this reduction in the seasonal cycle is transported upwards together with the seasonal anomalies and has reduced the amplitude of the well-known tape recorder over the last 2 decades.</p

Retrieving wind statistics from average spectrum of continuous-wave lidar

The aim of this study is to experimentally demonstrate that the time-average Doppler spectrum of a continuous-wave (cw) lidar is proportional to the probability density function of the line-of-sight velocities. This would open the possibility of using cw lidars for the determination of the second-order atmospheric turbulence statistics. An atmospheric field campaign and a wind tunnel experiment are carried out to show that the use of an average Doppler spectrum instead of a time series of velocities determined from individual Doppler spectra significantly reduces the differences with the standard deviation measured using ordinary anemometers, such as ultra-sonic anemometers or hotwires. The proposed method essentially removes the spatial averaging effect intrinsic to the cw lidar systems