Ensemble representation of uncertainty in Lagrangian satellite rainfall estimates

A new algorithm called Lagrangian Simulation (LSIM) has been developed that enables the interpolation uncertainty present in Lagrangian satellite rainfall algorithms such as the Climate Prediction Center (CPC) morphing technique (CMORPH) to be characterized using an ensemble product. The new algorithm generates ensemble sequences of rainfall fields conditioned on multiplatform multisensor microwave satellite data, demonstrating a conditional simulation approach that overcomes the problem of discontinuous uncertainty fields inherent in this type of product. Each ensemble member is consistent with the information present in the satellite data, while variation between members is indicative of uncertainty in the rainfall retrievals. LSIM is based on the combination of a Markov weather generator, conditioned on both previous and subsequent microwave measurements, and a global optimization procedure that uses simulated annealing to constrain the generated rainfall fields to display appropriate spatial structures. The new algorithm has been validated over a region of the continental United States and has been shown to provide reliable estimates of both point uncertainty distributions and wider spatiotemporal structures

Variation in the seston C:N ratio of the Arctic Ocean and pan-Arctic shelves

Studying more than 3600 observations of particulate organic carbon (POC) and particulate organic nitrogen (PON), we evaluate the applicability of the classic Redfield C:N ratio (6.6) and the recently proposed Sterner ratio (8.3) for the Arctic Ocean and pan-Arctic shelves. The confidence intervals for C:N ranged from 6.43 to 8.82, while the average C:N ratio for all observations was 7.4. In general, neither the Redfield or Sterner ratios were applicable, with the Redfield ratio being too low and the Sterner ratio too high. On a regional basis, all northern high latitude regions had a C:N ratio significantly higher than the Redfield ratio, except the Arctic Ocean (6.6), Chukchi (6.4) and East Siberian (6.5) Seas. The latter two regions were influenced by nutrient-rich Pacific waters, and had a high fraction of autotrophic (i.e. algal-derived) material. The C:N ratios of the Laptev (7.9) and Kara (7.5) Seas were high, and had larger contributions of terrigenous material. The highest C:N ratios were in the North Water (8.7) and Northeast Water (8.0) polynyas, and these regions were more similar to the Sterner ratio. The C:N ratio varied between regions, and was significantly different between the Atlantic (6.7) and Arctic (7.9) influenced regions of the Barents Sea, while the Atlantic dominated regions (Norwegian, Greenland and Atlantic Barents Seas) were similar (6.7–7). All observations combined, and most individual regions, showed a pattern of decreasing C:N ratios with increasing seston concentrations. This meta-analysis has important implications for ecosystem modelling, as it demonstrated the striking temporal and spatial variability in C:N ratios and challenges the common assumption of a constant C:N ratio. The non-constant stoichiometry was believed to be caused by variable contributions of autotrophs, heterotrophs and detritus to seston, and a significant decrease in C:N ratios with increasing Chlorophyll a concentrations supports this view. This study adds support to the use of a power function model, where the exponent is system-specific, but we suggest a general Arctic relationship, where POC = 7.4 PON0.89

Primary production during nutrient-induced blooms at elevated CO2 concentrations

Mesocosms experiments (PeECE II and PeECE III) were carried out in 9 transparent mesocosms. Prior to the experimental period, the seawater carbonate system was manipulated to achieve three different levels of CO2. At the onset of the experimental period, nutrients were added to all mesocosms in order to initiate phytoplankton blooms. Rates of primary production were measured by in-situ incubations using 14C-incorporation and oxygen production/consumption. Particulate primary production by 14C was also size fractionated and compared with phytoplankton species composition. Nutrient supply increased the primary production rates, and a net autotrophic phase with 14C-fixation rates up to 4 times higher than initial was observed midway through the 24 days experiment before net community production returned to near-zero and 14C-fixation rates relaxed back to lower than initial. We found a trend in the 14C-based measurements towards higher cumulative primary production at higher pCO2, consistent with recently published results for DIC removal (Riebesell et al., 2007). There where found differences to the size fractionated primary production response to CO2 treatments. The plankton composition changes throughout the bloom, however, resulted in no significant response until the final phase of the experiment where phytoplankton growth became nutrient limited, and phytoplankton community changed from diatom to flagellate dominance. This opens for the two alternative hypotheses that such an effect is associated with mineral nutrient limited growth, and/or with phytoplankton species composition. The lack of a clear net heterotrophic phase in the last part of the experiment supports the idea that a substantial part of production in the upper layer was not degraded locally, but either accumulated there or was exported vertically

An investigation into the relationship between an individual's level of hypnotic suggestibility and their ability to engage in ideomotor action

The relationship between hypnotic suggestibility and a propensity to engage in ideomotor action was investigated in 36 participants from the city of Plymouth, 24 of whom were psychology undergraduates from the University of Plymouth. Each participant carried out three hypnotic suggestibility tests before carrying out two computer-based ideomotor action tasks: a Brass finger-release task and an action-planning task. It was found that the higher a person’s hypnotic suggestibility, the faster they completed ideomotor tasks such as compatible trials in the Brass task (r = +.37, n = 27, p < .05) and the inverse action planning trials (r = +.35, n = 27, p <.05). This suggests that the reason why some people are more susceptible to hypnotic suggestion than others is because they are able to engage more readily in ideomotor action

Hydrological modelling using ensemble satellite rainfall estimates in a sparsely gauged river basin: The need for whole-ensemble calibration

The potential for satellite rainfall estimates to drive hydrological models has been long understood, but at the high spatial and temporal resolutions often required by these models the uncertainties in satellite rainfall inputs are both significant in magnitude and spatiotemporally autocorrelated. Conditional stochastic modelling of ensemble observed fields provides one possible approach to representing this uncertainty in a form suitable for hydrological modelling. Previous studies have concentrated on the uncertainty within the satellite rainfall estimates themselves, sometimes applying ensemble inputs to a pre-calibrated hydrological model. This approach does not account for the interaction between input uncertainty and model uncertainty and in particular the impact of input uncertainty on model calibration. Moreover, it may not be appropriate to use deterministic inputs to calibrate a model that is intended to be driven by using an ensemble. A novel whole-ensemble calibration approach has been developed to overcome some of these issues. This study used ensemble rainfall inputs produced by a conditional satellite-driven stochastic rainfall generator (TAMSIM) to drive a version of the Pitman rainfall-runoff model, calibrated using the whole-ensemble approach. Simulated ensemble discharge outputs were assessed using metrics adapted from ensemble forecast verification, showing that the ensemble outputs produced using the whole-ensemble calibrated Pitman model outperformed equivalent ensemble outputs created using a Pitman model calibrated against either the ensemble mean or a theoretical infinite-ensemble expected value. Overall, for the verification period the whole-ensemble calibration provided a mean RMSE of 61.7% of the mean wet season discharge, compared to 83.6% using a calibration based on the daily mean of the ensemble estimates. Using a Brier’s Skill Score to assess the performance of the ensemble against a climatic estimate, the whole-ensemble calibration provided a positive score for the main range of discharge events. The equivalent score for calibration against the ensemble mean was negative, indicating it showed no skill versus the climatic estimate

Approaches to Reconsider Literature on Physiological Effects of Environmental Change: Examples From Ocean Acidification Research

Understanding links between the abiotic environment and organism fitness and function is a central challenge of biology, and an issue of growing relevance due to anthropogenic environmental changes. To date, our understanding of these links has largely been based on the findings of isolated experimental studies. This command may, however, be enhanced where currently disparate data are synthesized. By outlining a range of approaches appropriate in bringing together the findings of studies considering ocean acidification effects, we hope to provide insight as to how they may be used in the future. Specifically, approaches discussed in this narrative literature review include established literature review methods, as well as emerging schemes structured around biological theories (i.e., dynamic energy budget, DEB; oxygen- and capacity-limited thermal tolerance, OCLTT; multiple performance-multiple optima, MPMO), and strategies developed in other disciplines (i.e., adverse outcome pathways, AOP). In the future approaches to use such frameworks in creative combinations may be developed. Here we discuss some of these potential combinations, specifically the use of: AOPs to identify key steps that can be explored in more detail through literature review frameworks; OCLTT and DEB frameworks to consider effects on both energy supply and allocation; MPMO frameworks to identify the performance curves of organisms whose interactions are considered in an ecosystem model. Regardless of the approach taken, synthesizing scientific literature represents a potentially powerful method to enhance understanding of the influence of the abiotic environment on whole organism fitness

REFAME: Rain Estimation Using Forward Adjusted-Advection of Microwave Estimates

Sensors flying on satellites provide the only practical means of estimating the precipitation that falls over the entire globe, particularly across the vast unpopulated expanses of Earth s oceans. The sensors that observe the Earth using microwave frequencies provide the best data, but currently these are mounted only on satellites flying in "low Earth orbit". Such satellites constantly move across the Earth s surface, providing snapshots of any given location every 12-36 hours. The entire constellation of low-orbit satellites numbers less than a dozen, and their orbits are not coordinated, so a location will frequently go two or more hours between snapshots. "Geosynchronous Earth orbit" (GEO) satellites continuously observe the same region of the globe, allowing them to provide very frequent pictures. For example, the "satellite movies" shown on television come from GEO satellites. However, the sensors available on GEO satellites cannot match the skill of the low-orbit microwave sensors in estimating precipitation. It is perhaps obvious that scientists should try to combine these very different kinds of data, taking advantage of the strengths of each, but this simple concept has proved to be a huge challenge. The scheme in this paper is "Lagrangian", meaning we follow the storm systems, rather than being tied to a fixed grid of boxes on the Earth s surface. Whenever a microwave snapshot occurs, we gladly use the resulting precipitation estimate. Then at all the times between the microwave snapshots we force the storm system to make a smooth transition from one snapshot s values to the next. We know that a lot more changes occur between the snapshots, but this smooth transition the best we can do with the microwave data alone. The key new contribution in this paper is that we also look at the relative variations in the GEO estimates during these in-between times and force the estimated changes in the precipitation to have similar variations. Preliminary testing shows that this approach has enough promise that it should be developed and studied

Phytoplankton-bacteria coupling under elevated CO₂ levels: a stable isotope labelling study

The potential impact of rising carbon dioxide (CO2) on carbon transfer from phytoplankton to bacteria was investigated during the 2005 PeECE III mesocosm study in Bergen, Norway. Sets of mesocosms, in which a phytoplankton bloom was induced by nutrient addition, were incubated under 1× (~350 μatm), 2× (~700 μatm), and 3× present day CO2 (~1050 μatm) initial seawater and sustained atmospheric CO2 levels for 3 weeks. 13C labelled bicarbonate was added to all mesocosms to follow the transfer of carbon from dissolved inorganic carbon (DIC) into phytoplankton and subsequently heterotrophic bacteria, and settling particles. Isotope ratios of polar-lipid-derived fatty acids (PLFA) were used to infer the biomass and production of phytoplankton and bacteria. Phytoplankton PLFA were enriched within one day after label addition, whilst it took another 3 days before bacteria showed substantial enrichment. Group-specific primary production measurements revealed that coccolithophores showed higher primary production than green algae and diatoms. Elevated CO2 had a significant positive effect on post-bloom biomass of green algae, diatoms, and bacteria. A simple model based on measured isotope ratios of phytoplankton and bacteria revealed that CO2 had no significant effect on the carbon transfer efficiency from phytoplankton to bacteria during the bloom. There was no indication of CO2 effects on enhanced settling based on isotope mixing models during the phytoplankton bloom, but this could not be determined in the post-bloom phase. Our results suggest that CO2 effects are most pronounced in the post-bloom phase, under nutrient limitation

The Nordic Seas carbon budget: Sources, sinks, and uncertainties

A carbon budget for the Nordic Seas is derived by combining recent inorganic carbon data from the CARINA database with relevant volume transports. Values of organic carbon in the Nordic Seas' water masses, the amount of carbon input from river runoff, and the removal through sediment burial are taken from the literature. The largest source of carbon to the Nordic Seas is the Atlantic Water that enters the area across the Greenland-Scotland Ridge; this is in particular true for the anthropogenic CO2. The dense overflows into the deep North Atlantic are the main sinks of carbon from the Nordic Seas. The budget show that presently 12.3 ± 1.4 Gt C yr−1 is transported into the Nordic Seas and that 12.5 ± 0.9 Gt C yr−1 is transported out, resulting in a net advective carbon transport out of the Nordic Seas of 0.17 ± 0.06 Gt C yr−1. Taking storage into account, this implies a net air-to-sea CO2 transfer of 0.19 ± 0.06 Gt C yr−1 into the Nordic Seas. The horizontal transport of carbon through the Nordic Seas is thus approximately two orders of magnitude larger than the CO2 uptake from the atmosphere. No difference in CO2 uptake was found between 2002 and the preindustrial period, but the net advective export of carbon from the Nordic Seas is smaller at present due to the accumulation of anthropogenic CO2