The first real-time worldwide ionospheric predictions network: an advance in support of spaceborne experimentation, on-line model validation, and space weather

We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.

Energy and pitch-angle dispersions of LLBL/cusp ions seen at middle altitudes: predictions by the open magnetosphere model

Numerical simulations are presented of the ion distribution functions seen by middle-altitude spacecraft in the low-latitude boundary layer (LLBL) and cusp regions when reconnection is, or has recently been, taking place at the equatorial magnetopause. From the evolution of the distribution function with time elapsed since the field line was opened, both the observed energy/observation-time and pitch-angle/energy dispersions are well reproduced. Distribution functions showing a mixture of magnetosheath and magnetospheric ions, often thought to be a signature of the LLBL, are found on newly opened field lines as a natural consequence of the magnetopause effects on the ions and their flight times. In addition, it is shown that the extent of the source region of the magnetosheath ions that are detected by a satellite is a function of the sensitivity of the ion instrument . If the instrument one-count level is high (and/or solar-wind densities are low), the cusp ion precipitation detected comes from a localised region of the mid-latitude magnetopause (around the magnetic cusp), even though the reconnection takes place at the equatorial magnetopause. However, if the instrument sensitivity is high enough, then ions injected from a large segment of the dayside magnetosphere (in the relevant hemisphere) will be detected in the cusp. Ion precipitation classed as LLBL is shown to arise from the low-latitude magnetopause, irrespective of the instrument sensitivity. Adoption of threshold flux definitions has the same effect as instrument sensitivity in artificially restricting the apparent source region.

Model predictions of the occurrence of non-Maxwellian plasmas, and analysis of their effects on EISCAT data

The recent identification of non-thermal plasmas using EISCAT data has been made possible by their occurrence during large, short-lived flow bursts. For steady, yet rapid, ion convection the only available signature is the shape of the spectrum, which is unreliable because it is open to distortion by noise and sampling uncertainty and can be mimicked by other phenomena. Nevertheless, spectral shape does give an indication of the presence of non-thermal plasma, and the characteristic shape has been observed for long periods (of the order of an hour or more) in some experiments. To evaluate this type of event properly one needs to compare it to what would be expected theoretically. Predictions have been made using the coupled thermosphere-ionosphere model developed at University College London and the University of Sheffield to show where and when non-Maxwellian plasmas would be expected in the auroral zone. Geometrical and other factors then govern whether these are detectable by radar. The results are applicable to any incoherent scatter radar in this area, but the work presented here concentrates on predictions with regard to experiments on the EISCAT facility.

Equipped to deal with uncertainty in climate and impacts predictions: lessons from internal peer review

The quantification of uncertainty is an increasingly popular topic, with clear importance for climate change policy. However, uncertainty assessments are open to a range of interpretations, each of which may lead to a different policy recommendation. In the EQUIP project researchers from the UK climate modelling, statistical modelling, and impacts communities worked together on ‘end-to-end’ uncertainty assessments of climate change and its impacts. Here, we use an experiment in peer review amongst project members to assess variation in the assessment of uncertainties between EQUIP researchers. We find overall agreement on key sources of uncertainty but a large variation in the assessment of the methods used for uncertainty assessment. Results show that communication aimed at specialists makes the methods used harder to assess. There is also evidence of individual bias, which is partially attributable to disciplinary backgrounds. However, varying views on the methods used to quantify uncertainty did not preclude consensus on the consequential results produced using those methods. Based on our analysis, we make recommendations for developing and presenting statements on climate and its impacts. These include the use of a common uncertainty reporting format in order to make assumptions clear; presentation of results in terms of processes and trade-offs rather than only numerical ranges; and reporting multiple assessments of uncertainty in order to elucidate a more complete picture of impacts and their uncertainties. This in turn implies research should be done by teams of people with a range of backgrounds and time for interaction and discussion, with fewer but more comprehensive outputs in which the range of opinions is recorded.

On judging the credibility of climate predictions

Incorporating a prediction into future planning and decision making is advisable only if we have judged the prediction’s credibility. This is notoriously difficult and controversial in the case of predictions of future climate. By reviewing epistemic arguments about climate model performance, we discuss how to make and justify judgments about the credibility of climate predictions. We propose a new bounding argument that justifies basing such judgments on the past performance of possibly dissimilar prediction problems. This encourages a more explicit use of data in making quantitative judgments about the credibility of future climate predictions, and in training users of climate predictions to become better judges of credibility. We illustrate the approach using decadal predictions of annual mean, global mean surface air temperature.

Investigation of the accuracy of historical irradiance products and interannual variability of solar irradiance using Met Office ground data

Met Office station data from 1980 to 2012 has been used to characterise the interannual variability of incident solar irradiance across the UK. The same data are used to evaluate four popular historical irradiance products to determine which are most suitable for use by the UK PV industry for site selection and system design. The study confirmed previous findings that interannual variability is typically 3–6% and weighted average probability of a particular percentage deviation from the mean at an average site in the UK was calculated. This weighted average showed that fewer than 2% of site-years could be expected to fall below 90% of the long-term site mean. The historical irradiance products were compared against Met Office station data from the input years of each product. This investigation has found that all products perform well. No products have a strong spatial trend. Meteonorm 7 is most conservative (MBE = −2.5%), CMSAF is most optimistic (MBE = +3.4%) and an average of all four products performs better than any one individual product (MBE = 0.3%)

Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions

The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. Weather forecasts using multiple NWPs from various weather centres implemented on catchment hydrology can provide significantly improved early flood warning. The availability of global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a new opportunity for the development of state-of-the-art early flood forecasting systems. This paper presents a case study using the TIGGE database for flood warning on a meso-scale catchment (4062 km2) located in the Midlands region of England. For the first time, a research attempt is made to set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE database. The study shows that precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial precipitation variability on such a comparatively small catchment, which indicates need to improve NWPs resolution and/or disaggregating techniques to narrow down the spatial gap between meteorology and hydrology. The spread of discharge forecasts varies from centre to centre, but it is generally large and implies a significant level of uncertainties. Nevertheless, the results show the TIGGE database is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation.

Validation of a priori CME arrival predictions made using real-time heliospheric imager observations

Between December 2010 and March 2013, volunteers for the Solar Stormwatch (SSW) Citizen Science project have identified and analyzed coronal mass ejections (CMEs) in the near real-time Solar Terrestrial Relations Observatory Heliospheric Imager observations, in order to make “Fearless Forecasts” of CME arrival times and speeds at Earth. Of the 60 predictions of Earth-directed CMEs, 20 resulted in an identifiable Interplanetary CME (ICME) at Earth within 1.5–6 days, with an average error in predicted transit time of 22 h, and average transit time of 82.3 h. The average error in predicting arrival speed is 151 km s−1, with an average arrival speed of 425km s−1. In the same time period, there were 44 CMEs for which there are no corresponding SSW predictions, and there were 600 days on which there was neither a CME predicted nor observed. A number of metrics show that the SSW predictions do have useful forecast skill; however, there is still much room for improvement. We investigate potential improvements by using SSW inputs in three models of ICME propagation: two of constant acceleration and one of aerodynamic drag. We find that taking account of interplanetary acceleration can improve the average errors of transit time to 19 h and arrival speed to 77 km s−1.

Assessing the reliability of probabilistic flood inundation model predictions

An ability to quantify the reliability of probabilistic flood inundation predictions is a requirement not only for guiding model development but also for their successful application. Probabilistic flood inundation predictions are usually produced by choosing a method of weighting the model parameter space, but previous study suggests that this choice leads to clear differences in inundation probabilities. This study aims to address the evaluation of the reliability of these probabilistic predictions. However, a lack of an adequate number of observations of flood inundation for a catchment limits the application of conventional methods of evaluating predictive reliability. Consequently, attempts have been made to assess the reliability of probabilistic predictions using multiple observations from a single flood event. Here, a LISFLOOD-FP hydraulic model of an extreme (>1 in 1000 years) flood event in Cockermouth, UK, is constructed and calibrated using multiple performance measures from both peak flood wrack mark data and aerial photography captured post-peak. These measures are used in weighting the parameter space to produce multiple probabilistic predictions for the event. Two methods of assessing the reliability of these probabilistic predictions using limited observations are utilized; an existing method assessing the binary pattern of flooding, and a method developed in this paper to assess predictions of water surface elevation. This study finds that the water surface elevation method has both a better diagnostic and discriminatory ability, but this result is likely to be sensitive to the unknown uncertainties in the upstream boundary condition

The Climate-system Historical Forecast Project: do stratosphere-resolving models make better seasonal climate predictions in boreal winter?

Using an international, multi-model suite of historical forecasts from the World Climate Research Programme (WCRP) Climate-system Historical Forecast Project (CHFP), we compare the seasonal prediction skill in boreal wintertime between models that resolve the stratosphere and its dynamics (“high-top”) and models that do not (“low-top”). We evaluate hindcasts that are initialized in November, and examine the model biases in the stratosphere and how they relate to boreal wintertime (Dec-Mar) seasonal forecast skill. We are unable to detect more skill in the high-top ensemble-mean than the low-top ensemble-mean in forecasting the wintertime North Atlantic Oscillation, but model performance varies widely. Increasing the ensemble size clearly increases the skill for a given model. We then examine two major processes involving stratosphere-troposphere interactions (the El Niño-Southern Oscillation/ENSO and the Quasi-biennial Oscillation/QBO) and how they relate to predictive skill on intra-seasonal to seasonal timescales, particularly over the North Atlantic and Eurasia regions. High-top models tend to have a more realistic stratospheric response to El Niño and the QBO compared to low-top models. Enhanced conditional wintertime skill over high-latitudes and the North Atlantic region during winters with El Niño conditions suggests a possible role for a stratospheric pathway.

Coming of age in L3 initial stages transfer models: deriving developmental predictions and looking towards the future

Aims: Over the past decade in particular, formal linguistic work within L3 acquisition has concentrated on hypothesizing and empirically determining the source of transfer from previous languages—L1, L2 or both—in L3 grammatical representations. In view of the progressive concern with more advanced stages, we aim to show that focusing on L3 initial stages should be one continued priority of the field, even—or especially—if the field is ready to shift towards modeling L3 development and ultimate attainment. Approach: We argue that L3 learnability is significantly impacted by initial stages transfer, as such forms the basis of the initial L3 interlanguage. To illustrate our point, the insights from studies using initial and intermediary stages L3 data are discussed in light of developmental predictions that derive from the initial stages models. Conclusions: Despite a shared desire to understand the process of L3 acquisition in whole, inclusive of offering developmental L3 theories, we argue that the field does not yet have—although is ever closer to—the data basis needed to effectively do so. Originality: This article seeks to convince the readership for the need of conservatism in L3 acquisition theory building, whereby offering a framework on how and why we can most effectively build on the accumulated knowledge of the L3 initial stages in order to make significant, steady progress. Significance: The arguments exposed here are meant to provide an epistemological base for a tenable framework of formal approaches to L3 interlanguage development and, eventually, ultimate attainment.

Decadal predictions with the HiGEM high resolution global coupled climate model: description and basic evaluation

This paper describes the development and basic evaluation of decadal predictions produced using the HiGEM coupled climate model. HiGEM is a higher resolution version of the HadGEM1 Met Office Unified Model. The horizontal resolution in HiGEM has been increased to 1.25◦ × 0.83◦ in longitude and latitude for the atmosphere, and 1/3◦ × 1/3◦ globally for the ocean. The HiGEM decadal predictions are initialised using an anomaly assimilation scheme that relaxes anomalies of ocean temperature and salinity to observed anomalies. 10 year hindcasts are produced for 10 start dates (1960, 1965,..., 2000, 2005). To determine the relative contributions to prediction skill from initial conditions and external forcing, the HiGEM decadal predictions are compared to uninitialised HiGEM transient experiments. The HiGEM decadal predictions have substantial skill for predictions of annual mean surface air temperature and 100 m upper ocean temperature. For lead times up to 10 years, anomaly correlations (ACC) over large areas of the North Atlantic Ocean, the Western Pacific Ocean and the Indian Ocean exceed values of 0.6. Initialisation of the HiGEM decadal predictions significantly increases skill over regions of the Atlantic Ocean,the Maritime Continent and regions of the subtropical North and South Pacific Ocean. In particular, HiGEM produces skillful predictions of the North Atlantic subpolar gyre for up to 4 years lead time (with ACC > 0.7), which are significantly larger than the uninitialised HiGEM transient experiments.

Downwelling solar irradiance in the biomass burning region of the southern Amazon: Dependence on aerosol intensive optical properties and role of water vapor

The sensitivity of solar irradiance at the surface to the variability of aerosol intensive optical properties is investigated for a site (Alta Floresta) in the southern portion of the Amazon basin using detailed comparisons between measured and modeled irradiances. Apart from aerosol intensive optical properties, specifically single scattering albedo (omega(o lambda)) and asymmetry parameter (g(lambda)), which were assumed constant, all other relevant input to the model were prescribed based on observation. For clean conditions, the differences between observed and modeled irradiances were consistent with instrumental uncertainty. For polluted conditions, the agreement was significantly worse, with a root mean square difference three times larger (23.5 Wm(-2)). Analysis revealed a noteworthy correlation between the irradiance differences (observed minus modeled) and the column water vapor (CWV) for polluted conditions. Positive differences occurred mostly in wet conditions, while the differences became more negative as the atmosphere dried. To explore the hypothesis that the irradiance differences might be linked to the modulation of omega(o lambda) and g(lambda) by humidity, AERONET retrievals of aerosol properties and CWV over the same site were analyzed. The results highlight the potential role of humidity in modifying omega(o lambda) and g(lambda) and suggest that to explain the relationship seen between irradiances differences via aerosols properties the focus has to be on humidity-dependent processes that affect particles chemical composition. Undoubtedly, there is a need to better understand the role of humidity in modifying the properties of smoke aerosols in the southern portion of the Amazon basin.

Life-history, thallus ontogeny, and the effects of temperature, irradiance and salinity on growth of the edible green seaweed Gayralia spp. (Chlorophyta) from Southern Brazil

Gayralia K.L. Vinogr. is a monostromatic green alga of commercial importance in the southern Brazil, and its cultivation is being considered. This paper reports some basic aspects of the biology of this poorly known genus. Two populations of Gayralia spp., from outer and inner sectors of Paranagua Bay, showed an asexual life history with a distinct pattern of thallus ontogeny. In one population (Gayralia sp. 1), zooids developed an expanded monostromatic blade directly, while in the other (Gayralia sp. 2) zooids produced an intermediate saccate stage, before giving rise to a monostromatic blade. Thalli of the two species differ in size and in cell diameter. The effects of temperature (16-30 degrees C), irradiance (50-100 mu mol photons m(-2) s(-1)), and salinity (5-40 psu) on the growth of both populations were assessed. Plantlets of Gayralia sp. 1 from in vitro cultures showed a broader tolerance to all salinity and irradiance levels tested, with the highest growth rate (GR; mean 17% day-1) at 21.5 degrees C and 100 mu mol photons m(-2) s(-1). Plantlets of Gayralia sp. 1 collected during the winter in the field showed higher GR, ranging from 5% day(-1) to 7.5% day(-1) in salinities from 20 to 40 psu, and 2.0% day(-1) and 4.3% day(-1) for plantlets collected during the summer. Gayralia sp. 2 from the field showed highest GR at salinity of 15 psu. These results suggest distinct physiological responses of the two species, in accordance with their distribution: Gayralia sp. 2 is limited to the inner areas of the estuary, while Gayralia sp. 1 grows in outer areas, where salinity values are higher than 20 psu. These data indicate that Gayralia sp. 1 has a higher potential for aquaculture than Gayralia sp. 2 due to its larger thalli, higher GR, and wider tolerance to environmental variations.