The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model.

1. There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6. Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

Excess open solar magnetic flux from satellite data: 1. Analysis of the third perihelion Ulysses pass

We use the third perihelion pass by the Ulysses spacecraft to illustrate and investigate the “flux excess” effect, whereby open solar flux estimates from spacecraft increase with increasing heliocentric distance. We analyze the potential effects of small-scale structure in the heliospheric field (giving fluctuations in the radial component on timescales smaller than 1 h) and kinematic time-of-flight effects of longitudinal structure in the solar wind flow. We show that the flux excess is explained by neither very small-scale structure (timescales < 1 h) nor by the kinematic “bunching effect” on spacecraft sampling. The observed flux excesses is, however, well explained by the kinematic effect of larger-scale (>1 day) solar wind speed variations on the frozen-in heliospheric field. We show that averaging over an interval T (that is long enough to eliminate structure originating in the heliosphere yet small enough to avoid cancelling opposite polarity radial field that originates from genuine sector structure in the coronal source field) is only an approximately valid way of allowing for these effects and does not adequately explain or account for differences between the streamer belt and the polar coronal holes.

Excess open solar magnetic flux from satellite data: 2. A survey of kinematic effects

We investigate the “flux excess” effect, whereby open solar flux estimates from spacecraft increase with increasing heliocentric distance. We analyze the kinematic effect on these open solar flux estimates of large-scale longitudinal structure in the solar wind flow, with particular emphasis on correcting estimates made using data from near-Earth satellites. We show that scatter, but no net bias, is introduced by the kinematic “bunching effect” on sampling and that this is true for both compression and rarefaction regions. The observed flux excesses, as a function of heliocentric distance, are shown to be consistent with open solar flux estimates from solar magnetograms made using the potential field source surface method and are well explained by the kinematic effect of solar wind speed variations on the frozen-in heliospheric field. Applying this kinematic correction to the Omni-2 interplanetary data set shows that the open solar flux at solar minimum fell from an annual mean of 3.82 × 1016 Wb in 1987 to close to half that value (1.98 × 1016 Wb) in 2007, making the fall in the minimum value over the last two solar cycles considerably faster than the rise inferred from geomagnetic activity observations over four solar cycles in the first half of the 20th century.

Current changes in tropical precipitation

Current changes in tropical precipitation from satellite data and climate models are assessed. Wet and dry regions of the tropics are defined as the highest 30% and lowest 70% of monthly precipitation values. Observed tropical ocean trends in the wet regime (1.8%/decade) and the dry regions (−2.6%/decade) according to the Global Precipitation Climatology Project (GPCP) over the period including Special Sensor Microwave Imager (SSM/I) data (1988–2008), where GPCP is believed to be more reliable, are of smaller magnitude than when including the entire time series (1979–2008) and closer to model simulations than previous comparisons. Analysing changes in extreme precipitation using daily data within the wet regions, an increase in the frequency of the heaviest 6% of events with warming for the SSM/I observations and model ensemble mean is identified. The SSM/I data indicate an increased frequency of the heaviest events with warming, several times larger than the expected Clausius–Clapeyron scaling and at the upper limit of the substantial range in responses in the model simulations.

Forest fire plumes over the North Atlantic: p-TOMCAT model simulations with aircraft and satellite measurements from the ITOP/ICARTT campaign

Intercontinental Transport of Ozone and Precursors (ITOP) (part of International Consortium for Atmospheric Research on Transport and Transformation (ICARTT)) was an intense research effort to measure long-range transport of pollution across the North Atlantic and its impact on O3 production. During the aircraft campaign plumes were encountered containing large concentrations of CO plus other tracers and aerosols from forest fires in Alaska and Canada. A chemical transport model, p-TOMCAT, and new biomass burning emissions inventories are used to study the emissions long-range transport and their impact on the troposphere O3 budget. The fire plume structure is modeled well over long distances until it encounters convection over Europe. The CO values within the simulated plumes closely match aircraft measurements near North America and over the Atlantic and have good agreement with MOPITT CO data. O3 and NOx values were initially too great in the model plumes. However, by including additional vertical mixing of O3 above the fires, and using a lower NO2/CO emission ratio (0.008) for boreal fires, O3 concentrations are reduced closer to aircraft measurements, with NO2 closer to SCIAMACHY data. Too little PAN is produced within the simulated plumes, and our VOC scheme's simplicity may be another reason for O3 and NOx model-data discrepancies. In the p-TOMCAT simulations the fire emissions lead to increased tropospheric O3 over North America, the north Atlantic and western Europe from photochemical production and transport. The increased O3 over the Northern Hemisphere in the simulations reaches a peak in July 2004 in the range 2.0 to 6.2 Tg over a baseline of about 150 Tg.

Calibrating flood inundation models: identifying and addressing uncertainty in satellite observed flood extents

Improvements in the resolution of satellite imagery have enabled extraction of water surface elevations at the margins of the flood. Comparison between modelled and observed water surface elevations provides a new means for calibrating and validating flood inundation models, however the uncertainty in this observed data has yet to be addressed. Here a flood inundation model is calibrated using a probabilistic treatment of the observed data. A LiDAR guided snake algorithm is used to determine an outline of a flood event in 2006 on the River Dee, North Wales, UK, using a 12.5m ERS-1 image. Points at approximately 100m intervals along this outline are selected, and the water surface elevation recorded as the LiDAR DEM elevation at each point. With a planar water surface from the gauged upstream to downstream water elevations as an approximation, the water surface elevations at points along this flooded extent are compared to their ‘expected’ value. The pattern of errors between the two show a roughly normal distribution, however when plotted against coordinates there is obvious spatial autocorrelation. The source of this spatial dependency is investigated by comparing errors to the slope gradient and aspect of the LiDAR DEM. A LISFLOOD-FP model of the flood event is set-up to investigate the effect of observed data uncertainty on the calibration of flood inundation models. Multiple simulations are run using different combinations of friction parameters, from which the optimum parameter set will be selected. For each simulation a T-test is used to quantify the fit between modelled and observed water surface elevations. The points chosen for use in this T-test are selected based on their error. The criteria for selection enables evaluation of the sensitivity of the choice of optimum parameter set to uncertainty in the observed data. This work explores the observed data in detail and highlights possible causes of error. The identification of significant error (RMSE = 0.8m) between approximate expected and actual observed elevations from the remotely sensed data emphasises the limitations of using this data in a deterministic manner within the calibration process. These limitations are addressed by developing a new probabilistic approach to using the observed data.

Microwave spectrum of CHD2CN and CHD2NC, and the harmonic force field and rz structure of methyl cyanide and isocyanide

The microwave spectra of CHD2CN and CHD2NC have been measured from 18 to 40 GHz; about 20 type A and 30 type C transitions have been observed for each molecule. These have been fitted to a Hamiltonian using 3 rotational constants, and 5 quartic and 4 sextic distortion constants, in the IrS reduction of Watson [in “Vibrational spectra and structure” Vol. 6 (1977)]; the standard error of the fit is 26 kHz. For methyl cyanide the 5 quartic distortion constants have been used to further refine the recent harmonic force field of Duncan et al. [J. Mol. Spectrosc. 69, 123 (1978)], but the changes are small. Finally, for both molecules, the harmonic force field has been used to determine zero point average moments of inertia Iz from the ground state rotational constants for many isotopic species, and these have been used to determine an rz structure. The results are compared with rs structure calculations.