The interpretation and use of biases in decadal climate predictions

Decadal climate predictions exhibit large biases, which are often subtracted and forgotten. However, understanding the causes of bias is essential to guide efforts to improve prediction systems, and may offer additional benefits. Here the origins of biases in decadal predictions are investigated, including whether analysis of these biases might provide useful information. The focus is especially on the lead-time-dependent bias tendency. A “toy” model of a prediction system is initially developed and used to show that there are several distinct contributions to bias tendency. Contributions from sampling of internal variability and a start-time-dependent forcing bias can be estimated and removed to obtain a much improved estimate of the true bias tendency, which can provide information about errors in the underlying model and/or errors in the specification of forcings. It is argued that the true bias tendency, not the total bias tendency, should be used to adjust decadal forecasts. The methods developed are applied to decadal hindcasts of global mean temperature made using the Hadley Centre Coupled Model, version 3 (HadCM3), climate model, and it is found that this model exhibits a small positive bias tendency in the ensemble mean. When considering different model versions, it is shown that the true bias tendency is very highly correlated with both the transient climate response (TCR) and non–greenhouse gas forcing trends, and can therefore be used to obtain observationally constrained estimates of these relevant physical quantities.

The carbon dioxide production rate assumption biases gastric emptying parameters in healthy adults

RATIONALE: An altered gastric emptying (GE) rate has been implicated in the aetiology of obesity. The (13)C-octanoic acid breath test (OBT) is frequently used to measure GE, and the cumulative percentage of (13)C recovered (cPDR) is a common outcome measure. However, true cPDR in breath is dependent on accurate measurement of carbon dioxide production rate (VCO(2)). The current study aimed to quantify differences in the (13)C OBT results obtained using directly measured VCO(2) (VCO(2DM)) compared with (i) predicted from resting VCO(2) (VCO(2PR)) and (ii) predicted from body surface area VCO(2) (VCO(2BSA)). METHODS: The GE rate of a high-fat test meal was assessed in 27 lean subjects using the OBT. Breath samples were gathered during the fasted state and at regular intervals throughout the 6-h postprandial period for determination of (13)C-isotopic enrichment by continuous-flow isotope-ratio mass spectrometry. The VCO(2) was measured directly from exhaled air samples and the PDR calculated by three methods. The bias and the limits of agreement were calculated using Bland-Altman plots. RESULTS: Compared with the VCO(2DM), the cPDR was underestimated by VCO(2PR) (4.8%; p = 0.0001) and VCO(2BSA) (2.7%; p = 0.02). The GE T(half) was underestimated by VCO(2PR) (13 min; p = 0.0001) and VCO(2BSA) (10 min; p = 0.01), compared with VCO(2DM). CONCLUSIONS: The findings highlight the importance of directly measuring VCO(2)production rates throughout the (13)C OBT and could partly explain the conflicting evidence regarding the effect of obesity on GE rates.

Do turning biases by the 7-spot ladybird, Coccinella septempunctata, increase their foraging efficiency?

The hypothesis that foraging male and female Coccinella septempunctata L. would exhibit a turning bias when walking along a branched linear wire in a Y-maze was tested. Individuals were placed repeatedly in the maze. Approximately 45% of all individuals tested displayed significant turning biases, with a similar number of individuals biased to the left and right. In the maze right-handed individuals turned right at 84.4% of turns and the left-handed individuals turned left at 80.2% of turns. A model of the searching efficiency of C. septempunctata in dichotomous branched environments showed that model coccinellids with greater turning biases discovered a higher proportion of the plant for a given number of searches than those with no bias. A modification of the model to investigate foraging efficiency, by calculating the mean time taken by individuals to find randomly distributed aphid patches, suggested that on four different sizes of plants, with a variety of aphid patch densities, implementing a turning bias was a significantly more efficient foraging strategy than no bias. In general the benefits to foraging of implementing a turning bias increased with the degree of the bias. It may be beneficial for individuals in highly complex branched environments to have a turning bias slightly lower than 100% in order to benefit from increased foraging efficiency without walking in circles. Foraging bias benefits increased with increasing plant size and decreasing aphid density. In comparisons of two different plant morphologies, one with a straight stem and side branches and one with a symmetrically branched morphology, there were few significant differences in the effects of turning biases on foraging efficiency between morphologies

Vertical structure and physical processes of the Madden-Julian oscillation: Biases and uncertainties at short range

An analysis of diabatic heating and moistening processes from 12-36 hour lead time forecasts from 12 Global Circulation Models are presented as part of the "Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)" project. A lead time of 12-36 hours is chosen to constrain the large scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up for the models as they adjust to being driven from the YOTC analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large scale dynamics is reasonably constrained, moistening and heating profiles have large inter-model spread. In particular, there are large spreads in convective heating and moistening at mid-levels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behaviour shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.

Exploring the impact of CMIP5 model biases on the simulation of North Atlantic decadal variability

Instrumental observations, palaeo-proxies, and climate models suggest significant decadal variability within the North Atlantic subpolar gyre (NASPG). However, a poorly sampled observational record and a diversity of model behaviours mean that the precise nature and mechanisms of this variability are unclear. Here, we analyse an exceptionally large multi-model ensemble of 42 present-generation climate models to test whether NASPG mean state biases systematically affect the representation of decadal variability. Temperature and salinity biases in the Labrador Sea co-vary and influence whether density variability is controlled by temperature or salinity variations. Ocean horizontal resolution is a good predictor of the biases and the location of the dominant dynamical feedbacks within the NASPG. However, we find no link to the spectral characteristics of the variability. Our results suggest that the mean state and mechanisms of variability within the NASPG are not independent. This represents an important caveat for decadal predictions using anomaly-assimilation methods.

Sea-breeze dynamics and convection initiation: the influence of convective parameterization in weather and climate model biases

There are some long-established biases in atmospheric models that originate from the representation of tropical convection. Previously, it has been difficult to separate cause and effect because errors are often the result of a number of interacting biases. Recently, researchers have gained the ability to run multiyear global climate model simulations with grid spacings small enough to switch the convective parameterization off, which permits the convection to develop explicitly. There are clear improvements to the initiation of convective storms and the diurnal cycle of rainfall in the convection-permitting simulations, which enables a new process-study approach to model bias identification. In this study, multiyear global atmosphere-only climate simulations with and without convective parameterization are undertaken with the Met Office Unified Model and are analyzed over the Maritime Continent region, where convergence from sea-breeze circulations is key for convection initiation. The analysis shows that, although the simulation with parameterized convection is able to reproduce the key rain-forming sea-breeze circulation, the parameterization is not able to respond realistically to the circulation. A feedback of errors also occurs: the convective parameterization causes rain to fall in the early morning, which cools and wets the boundary layer, reducing the land–sea temperature contrast and weakening the sea breeze. This is, however, an effect of the convective bias, rather than a cause of it. Improvements to how and when convection schemes trigger convection will improve both the timing and location of tropical rainfall and representation of sea-breeze circulations.

Southern Hemisphere jet latitude biases in CMIP5 models linked to shortwave cloud forcing

Substantial biases in shortwave cloud forcing (SWCF) of up to ±30 W m−2are found in the midlatitudes of the Southern Hemisphere in the historical simulations of 34 CMIP5 coupled general circulation models. The SWCF biases are shown to induce surface temperature anomalies localized in the midlatitudes, and are significantly correlated with the mean latitude of the eddy-driven jet, with a negative SWCF bias corresponding to an equatorward jet latitude bias. Aquaplanet model experiments are performed to demonstrate that the jet latitude biases are primarily induced by the midlatitude SWCF anomalies, such that the jet moves toward (away from) regions of enhanced (reduced) temperature gradients. The results underline the necessity of accurately representing cloud radiative forcings in state-of-the-art coupled models.

Effects of a multi-session Cognitive Bias Modification program on interpretative biases and social anxiety symptoms in a sample of Iranian socially-anxious students

This study examines the effects of a multi-session Cognitive Bias Modification (CBM) program on interpretative biases and social anxiety in an Iranian sample. Thirty-six volunteers with a high score on social anxiety measures were recruited from a student population and randomly allocated into the experimental and control groups. In the experimental group, participants received 4 sessions of positive CBM for interpretative biases (CBM-I) over 2 weeks in the laboratory. Participants in the control condition completed a neutral task matched the active CBM-I intervention in format and duration but did not encourage positive disambiguation of socially ambiguous scenarios. The results indicated that after training the positive CBM-I group exhibited more positive (and less negative) interpretations of ambiguous scenarios and less social anxiety symptoms relative to the control condition at both 1 week post-test and 7 weeks follow-up. It is suggested that clinical trials are required to establish the clinical efficacy of this intervention for social anxiety.

Clinical implications of cognitive bias modification for interpretative biases in social anxiety: an integrative literature review

Cognitive theories of social anxiety indicate that negative cognitive biases play a key role in causing and maintaining social anxiety. On the basis of these cognitive theories, laboratory-based research has shown that individuals with social anxiety exhibit negative interpretation biases of ambiguous social situations. Cognitive Bias Modification for interpretative biases (CBM-I) has emerged from this basic science research to modify negative interpretative biases in social anxiety and reduce emotional vulnerability and social anxiety symptoms. However, it is not yet clear if modifying interpretation biases via CBM will have any enduring effect on social anxiety symptoms or improve social functioning. The aim of this paper is to review the relevant literature on interpretation biases in social anxiety and discuss important implications of CBM-I method for clinical practice and research.

Understanding inter-satellite biases of microwave humidity sounders using global simultaneous nadir overpasses

Simultaneous nadir overpasses (SNOs) of polar-orbiting satellites are most frequent in polar areas but can occur at any latitude when the equatorial crossing times of the satellites become close owing to orbital drift. We use global SNOs of polar orbiting satellites to evaluate the intercalibration of microwave humidity sounders from the more frequent high-latitude SNOs. We have found based on sensitivity analyses that optimal distance and time thresholds for defining collocations are pixel centers less than 5 km apart and time differences less than 300 s. These stringent collocation criteria reduce the impact of highly variable surface or atmospheric conditions on the estimated biases. Uncertainties in the estimated biases are dominated by the combined radiometric noise of the instrument pair. The effects of frequency changes between different versions of the humidity sounders depend on the amount of water vapor in the atmosphere. There are significant scene radiance and thus latitude dependencies in the estimated biases and this has to taken into account while intercalibrating microwave humidity sounders. Therefore the results obtained using polar SNOs will not be representative for moist regions, necessitating the use of global collocations for reliable intercalibration.

Biases in comparative analyses of extinction risk: mind the gap

1. Comparative analyses are used to address the key question of what makes a species more prone to extinction by exploring the links between vulnerability and intrinsic species’ traits and/or extrinsic factors. This approach requires comprehensive species data but information is rarely available for all species of interest. As a result comparative analyses often rely on subsets of relatively few species that are assumed to be representative samples of the overall studied group. 2. Our study challenges this assumption and quantifies the taxonomic, spatial, and data type biases associated with the quantity of data available for 5415 mammalian species using the freely available life-history database PanTHERIA. 3. Moreover, we explore how existing biases influence results of comparative analyses of extinction risk by using subsets of data that attempt to correct for detected biases. In particular, we focus on links between four species’ traits commonly linked to vulnerability (distribution range area, adult body mass, population density and gestation length) and conduct univariate and multivariate analyses to understand how biases affect model predictions. 4. Our results show important biases in data availability with c.22% of mammals completely lacking data. Missing data, which appear to be not missing at random, occur frequently in all traits (14–99% of cases missing). Data availability is explained by intrinsic traits, with larger mammals occupying bigger range areas being the best studied. Importantly, we find that existing biases affect the results of comparative analyses by overestimating the risk of extinction and changing which traits are identified as important predictors. 5. Our results raise concerns over our ability to draw general conclusions regarding what makes a species more prone to extinction. Missing data represent a prevalent problem in comparative analyses, and unfortunately, because data are not missing at random, conventional approaches to fill data gaps, are not valid or present important challenges. These results show the importance of making appropriate inferences from comparative analyses by focusing on the subset of species for which data are available. Ultimately, addressing the data bias problem requires greater investment in data collection and dissemination, as well as the development of methodological approaches to effectively correct existing biases.

The impact of two coupled cirrus microphysics-radiation parameterizations on the temperature and specific humidity biases in the tropical tropopause layer in a climate model

The impact of two different coupled cirrus microphysics-radiation parameterizations on the zonally averaged temperature and humidity biases in the tropical tropopause layer (TTL) of a Met Office climate model configuration is assessed. One parameterization is based on a linear coupling between a model prognostic variable, the ice mass mixing ratio, qi, and the integral optical properties. The second is based on the integral optical properties being parameterized as functions of qi and temperature, Tc, where the mass coefficients (i.e. scattering and extinction) are parameterized as nonlinear functions of the ratio between qi and Tc. The cirrus microphysics parameterization is based on a moment estimation parameterization of the particle size distribution (PSD), which relates the mass moment (i.e. second moment if mass is proportional to size raised to the power of 2 ) of the PSD to all other PSD moments through the magnitude of the second moment and Tc. This same microphysics PSD parameterization is applied to calculate the integral optical properties used in both radiation parameterizations and, thus, ensures PSD and mass consistency between the cirrus microphysics and radiation schemes. In this paper, the temperature-non-dependent and temperature-dependent parameterizations are shown to increase and decrease the zonally averaged temperature biases in the TTL by about 1 K, respectively. The temperature-dependent radiation parameterization is further demonstrated to have a positive impact on the specific humidity biases in the TTL, as well as decreasing the shortwave and longwave biases in the cloudy radiative effect. The temperature-dependent radiation parameterization is shown to be more consistent with TTL and global radiation observations.

The role of media networks in compensating political biases: evidence from radio networks in Brazil

A central question in political economy is how to incentivize elected socials to allocate resources to those that need them the most. Research has shown that, while electoral incentives lead central governments to transfer fewer funds to non-aligned constituencies, media presence is instrumental in promoting a better allocation of resources. This study evaluates how these two phenomena interact by analyzing the role of media in compensating political biases. In particular, we analyze how media presence, connectivity and ownership affect the distribution of federal drought relief transfers to Brazilian municipalities. We find that municipalities that are not aligned with the federal government have a lower probability of receiving funds conditional on experiencing low precipitation. However, we show that the presence of radio stations compensates for this bias. This effect is driven by municipalities that have radio stations connected to a regional network rather than by the presence of local radio stations. In addition, the effect of network-connected radio stations increases with their network coverage. These findings suggests that the connection of a radio station to a network is important because it increases the salience of disasters, making it harder for the federal government to ignore non-allies. We show that our findings are not explained by the ownership and manipulation of media by politicians.