Online modeling with tunable RBF network

In this paper, we propose a novel online modeling algorithm for nonlinear and nonstationary systems using a radial basis function (RBF) neural network with a fixed number of hidden nodes. Each of the RBF basis functions has a tunable center vector and an adjustable diagonal covariance matrix. A multi-innovation recursive least square (MRLS) algorithm is applied to update the weights of RBF online, while the modeling performance is monitored. When the modeling residual of the RBF network becomes large in spite of the weight adaptation, a node identified as insignificant is replaced with a new node, for which the tunable center vector and diagonal covariance matrix are optimized using the quantum particle swarm optimization (QPSO) algorithm. The major contribution is to combine the MRLS weight adaptation and QPSO node structure optimization in an innovative way so that it can track well the local characteristic in the nonstationary system with a very sparse model. Simulation results show that the proposed algorithm has significantly better performance than existing approaches.

Atlantic meridional heat transports in two ocean reanalyes evaluated against the RAPID array

The Atlantic meridional overturning circulation in two versions of the NEMO ¼° global ocean model has been compared with the RAPID transport array at 26oN. Both model versions reproduce the mean MOC strength well although the Florida Straits flows differ because the pathway of the Gulf Stream is not strongly constrained at this resolution. Both models however have a mean meridional heat transport of 1.07PW, much lower than the 1.35PW from RAPID observations in Apr04-Oct07. Much of the heat transport discrepancy is due to lower transports in summer across the MidOcean (Bahamas-Africa) section, due to stronger southward geostrophic flows in the top 100m where the water is warmest. Seasonal thermocline changes increase temperature differences across the basin driving stronger geostrophic shear, but this effect is much weaker in the top 100m of the RAPID velocity data. The effect accounts for a reduction of 1.1Sv in MOC and 0.1PW in heat transports. The rest of the discrepancy comes from lower Ekman transports from using ERAInterim winds instead of QuikSCAT, a smaller zonally-varying “Eddy” heat transport component, estimated from repeat XBT sections in the observations, and the southward throughflow in the model. Other differences in depth structure of the model MOC and RAPID observations are described but have much less impact on heat transports.

Crossbred cow adoption and milk market participation in a multivariate count data framework

Cross-bred cow adoption is an important and potent policy variable precipitating subsistence household entry into emerging milk markets. This paper focuses on the problem of designing policies that encourage and sustain milkmarket expansion among a sample of subsistence households in the Ethiopian highlands. In this context it is desirable to measure households’ ‘proximity’ to market in terms of the level of deficiency of essential inputs. This problem is compounded by four factors. One is the existence of cross-bred cow numbers (count data) as an important, endogenous decision by the household; second is the lack of a multivariate generalization of the Poisson regression model; third is the censored nature of the milk sales data (sales from non-participating households are, essentially, censored at zero); and fourth is an important simultaneity that exists between the decision to adopt a cross-bred cow, the decision about how much milk to produce, the decision about how much milk to consume and the decision to market that milk which is produced but not consumed internally by the household. Routine application of Gibbs sampling and data augmentation overcome these problems in a relatively straightforward manner. We model the count data from two sites close to Addis Ababa in a latent, categorical-variable setting with known bin boundaries. The single-equation model is then extended to a multivariate system that accommodates the covariance between crossbred-cow adoption, milk-output, and milk-sales equations. The latent-variable procedure proves tractable in extension to the multivariate setting and provides important information for policy formation in emerging-market settings

Climate change projections and stratosphere–troposphere interaction

Climate change is expected to increase winter rainfall and flooding in many extratropical regions as evaporation and precipitation rates increase, storms become more intense and storm tracks move polewards. Here, we show how changes in stratospheric circulation could play a significant role in future climate change in the extratropics through an additional shift in the tropospheric circulation. This shift in the circulation alters climate change in regional winter rainfall by an amount large enough to significantly alter regional climate change projections. The changes are consistent with changes in stratospheric winds inducing a change in the baroclinic eddy growth rate across the depth of the troposphere. A change in mean wind structure and an equatorward shift of the tropospheric storm tracks relative to models with poor stratospheric resolution allows coupling with surface climate. Using the Atlantic storm track as an example, we show how this can double the predicted increase in extreme winter rainfall over Western and Central Europe compared to other current climate projections

Impact of global warming on the Asian winter monsoon in a coupled GCM

The Asian winter monsoon (AWM) response to the global warming was investigated through a long-term integration of the transient greenhouse warming with the ECHAM4/OPYC3 CGCM. The physics of the response was studied through analyses of the impact of the global warming on the variations of the ocean and land contrast near the ground in the Asian and western Pacific region and the east Asian trough and jet stream in the middle and upper troposphere. Forcing of transient eddy activity on the zonal circulation over the Asian and western Pacific region was also analyzed. It is found that in the global warming scenario the winter northeasterlies along the Pacific coast of the Eurasian continent weaken systematically and significantly, and intensity of the AWM reduces evidently, but the AWM variances on the interannual and interdecadal scales are not affected much by the global warming. It is suggested that the global warming makes the climate over the most part of Asia to be milder with enhanced moisture in winter. In the global warming scenario the contrasts of the sea level pressure and the near-surface temperature between the Asian continent and the Pacific Ocean become significantly smaller, northward and eastward shifts and weakening of the east Asian trough and jet stream in the middle and upper troposphere are found. As a consequence, the cold air in the AWM originating from the east Asian trough and high latitudes is less powerful. In addition, feedback of the transient activity also makes a considerable contribution to the higher-latitude shift of the jet stream over the North Pacific in the global warming scenario.

A low-order model investigation of the analysis of gravity waves in the ensemble Kalman filter.

The behavior of the ensemble Kalman filter (EnKF) is examined in the context of a model that exhibits a nonlinear chaotic (slow) vortical mode coupled to a linear (fast) gravity wave of a given amplitude and frequency. It is shown that accurate recovery of both modes is enhanced when covariances between fast and slow normal-mode variables (which reflect the slaving relations inherent in balanced dynamics) are modeled correctly. More ensemble members are needed to recover the fast, linear gravity wave than the slow, vortical motion. Although the EnKF tends to diverge in the analysis of the gravity wave, the filter divergence is stable and does not lead to a great loss of accuracy. Consequently, provided the ensemble is large enough and observations are made that reflect both time scales, the EnKF is able to recover both time scales more accurately than optimal interpolation (OI), which uses a static error covariance matrix. For OI it is also found to be problematic to observe the state at a frequency that is a subharmonic of the gravity wave frequency, a problem that is in part overcome by the EnKF.However, error in themodeled gravity wave parameters can be detrimental to the performance of the EnKF and remove its implied advantages, suggesting that a modified algorithm or a method for accounting for model error is needed.

Four-dimensional data assimilation and balanced dynamics

The problem of spurious excitation of gravity waves in the context of four-dimensional data assimilation is investigated using a simple model of balanced dynamics. The model admits a chaotic vortical mode coupled to a comparatively fast gravity wave mode, and can be initialized such that the model evolves on a so-called slow manifold, where the fast motion is suppressed. Identical twin assimilation experiments are performed, comparing the extended and ensemble Kalman filters (EKF and EnKF, respectively). The EKF uses a tangent linear model (TLM) to estimate the evolution of forecast error statistics in time, whereas the EnKF uses the statistics of an ensemble of nonlinear model integrations. Specifically, the case is examined where the true state is balanced, but observation errors project onto all degrees of freedom, including the fast modes. It is shown that the EKF and EnKF will assimilate observations in a balanced way only if certain assumptions hold, and that, outside of ideal cases (i.e., with very frequent observations), dynamical balance can easily be lost in the assimilation. For the EKF, the repeated adjustment of the covariances by the assimilation of observations can easily unbalance the TLM, and destroy the assumptions on which balanced assimilation rests. It is shown that an important factor is the choice of initial forecast error covariance matrix. A balance-constrained EKF is described and compared to the standard EKF, and shown to offer significant improvement for observation frequencies where balance in the standard EKF is lost. The EnKF is advantageous in that balance in the error covariances relies only on a balanced forecast ensemble, and that the analysis step is an ensemble-mean operation. Numerical experiments show that the EnKF may be preferable to the EKF in terms of balance, though its validity is limited by ensemble size. It is also found that overobserving can lead to a more unbalanced forecast ensemble and thus to an unbalanced analysis.

Flow-dependent predictability of the North Atlantic Jet

The North Atlantic eddy-driven jet is a major component of the large-scale flow in the northern hemisphere. Here we present evidence from reanalysis and ensemble forecast data for systematic flow-dependent predictability of the jet during northern hemisphere winter (DJF). It is found that when the jet is weakened or split it is both less persistent and less predictable. The lack of predictability manifests itself as the onset of an anomalously large instantaneous rate of spread of ensemble forecast members as the jet becomes weakened. This suggests that as the jet weakens or splits it enters into a state more sensitive to small differences between ensemble forecast members, rather like the sensitive region between the wings of the Lorenz attractor.

A unified neurofuzzy model for classification

This work proposes a unified neurofuzzy modelling scheme. To begin with, the initial fuzzy base construction method is based on fuzzy clustering utilising a Gaussian mixture model (GMM) combined with the analysis of covariance (ANOVA) decomposition in order to obtain more compact univariate and bivariate membership functions over the subspaces of the input features. The mean and covariance of the Gaussian membership functions are found by the expectation maximisation (EM) algorithm with the merit of revealing the underlying density distribution of system inputs. The resultant set of membership functions forms the basis of the generalised fuzzy model (GFM) inference engine. The model structure and parameters of this neurofuzzy model are identified via the supervised subspace orthogonal least square (OLS) learning. Finally, instead of providing deterministic class label as model output by convention, a logistic regression model is applied to present the classifier’s output, in which the sigmoid type of logistic transfer function scales the outputs of the neurofuzzy model to the class probability. Experimental validation results are presented to demonstrate the effectiveness of the proposed neurofuzzy modelling scheme.

Tropical Atlantic variability modes (1979–2002). Part I: Time-evolving SST modes related to West African rainfall

This work presents a description of the 1979–2002 tropical Atlantic (TA) SST variability modes coupled to the anomalous West African (WA) rainfall during the monsoon season. The time-evolving SST patterns, with an impact on WA rainfall variability, are analyzed using a new methodology based on maximum covariance analysis. The enhanced Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) dataset, which includes measures over the ocean, gives a complete picture of the interannual WA rainfall patterns for the Sahel dry period. The leading TA SST pattern, related to the Atlantic El Niño, is coupled to anomalous precipitation over the coast of the Gulf of Guinea, which corresponds to the second WA rainfall principal component. The thermodynamics and dynamics involved in the generation, development, and damping of this mode are studied and compared with previous works. The SST mode starts at the Angola/Benguela region and is caused by alongshore wind anomalies. It then propagates westward via Rossby waves and damps because of latent heat flux anomalies and Kelvin wave eastward propagation from an off-equatorial forcing. The second SST mode includes the Mediterranean and the Atlantic Ocean, showing how the Mediterranean SST anomalies are those that are directly associated with the Sahelian rainfall. The global signature of the TA SST patterns is analyzed, adding new insights about the Pacific– Atlantic link in relation to WA rainfall during this period. Also, this global picture suggests that the Mediterranean SST anomalies are a fingerprint of large-scale forcing. This work updates the results given by other authors, whose studies are based on different datasets dating back to the 1950s, including both the wet and the dry Sahel periods.

Data assimilation with correlated observation errors: experiments with a 1-D shallow water model

Remote sensing observations often have correlated errors, but the correlations are typically ignored in data assimilation for numerical weather prediction. The assumption of zero correlations is often used with data thinning methods, resulting in a loss of information. As operational centres move towards higher-resolution forecasting, there is a requirement to retain data providing detail on appropriate scales. Thus an alternative approach to dealing with observation error correlations is needed. In this article, we consider several approaches to approximating observation error correlation matrices: diagonal approximations, eigendecomposition approximations and Markov matrices. These approximations are applied in incremental variational assimilation experiments with a 1-D shallow water model using synthetic observations. Our experiments quantify analysis accuracy in comparison with a reference or ‘truth’ trajectory, as well as with analyses using the ‘true’ observation error covariance matrix. We show that it is often better to include an approximate correlation structure in the observation error covariance matrix than to incorrectly assume error independence. Furthermore, by choosing a suitable matrix approximation, it is feasible and computationally cheap to include error correlation structure in a variational data assimilation algorithm.

Rossby wave-breaking analysis of explosive cyclones in the Euro-Atlantic sector

The two-way relationship between Rossby Wave-Breaking (RWB) and intensification of extra tropical cyclones is analysed over the Euro-Atlantic sector. In particular, the timing, intensity and location of cyclone development are related to RWB occurrences. For this purpose, two potential-temperature based indices are used to detect and classify anticyclonic and cyclonic RWB episodes from ERA-40 Re-Analysis data. Results show that explosive cyclogenesis over the North Atlantic (NA) is fostered by enhanced occurrence of RWB on days prior to the cyclone’s maximum intensification. Under such conditions, the eddy-driven jet stream is accelerated over the NA, thus enhancing conditions for cyclogenesis. For explosive cyclogenesis over the eastern NA, enhanced cyclonic RWB over eastern Greenland and anticyclonic RWB over the sub-tropical NA are observed. Typically only one of these is present in any given case, with the RWB over eastern Greenland being more frequent than its southern counterpart. This leads to an intensification of the jet over the eastern NA and enhanced probability of windstorms reaching Western Europe. Explosive cyclones evolving under simultaneous RWB on both sides of the jet feature a higher mean intensity and deepening rates than cyclones preceded by a single RWB event. Explosive developments over the western NA are typically linked to a single area of enhanced cyclonic RWB over western Greenland. Here, the eddy-driven jet is accelerated over the western NA. Enhanced occurrence of cyclonic RWB over southern Greenland and anticyclonic RWB over Europe is also observed after explosive cyclogenesis, potentially leading to the onset of Scandinavian Blocking. However, only very intense developments have a considerable influence on the large-scale atmospheric flow. Non-explosive cyclones depict no sign of enhanced RWB over the whole NA area. We conclude that the links between RWB and cyclogenesis over the Euro-Atlantic sector are sensitive to the cyclone’s maximum intensity, deepening rate and location.

Are the winters 2010 and 2012 archetypes exhibiting extreme opposite behavior of the North Atlantic jet stream?

The atmospheric circulation over the North Atlantic-European sector experienced exceptional but highly contrasting conditions in the recent 2010 and 2012 winters (November-March; with the year dated by the relevant January). Evidence is given for the remarkably different locations of the eddy-driven westerly jet over the North Atlantic. In the 2010 winter the maximum of the jet stream was systematically between 30ºN and 40ºN (in the ‘south jet regime’), while in the 2012 winter it was predominantly located around 55ºN (north jet regime). These jet features underline the occurrence of either weak flow (2010) or strong and persistent ridges throughout the troposphere (2012). This is confirmed by the very different occurrence of blocking systems over the North Atlantic, associated with episodes of strong cyclonic (anticyclonic) Rossby wave breaking in 2010 (2012) winters. These dynamical features underlie strong precipitation and temperature anomalies over parts of Europe, with detrimental impacts on many socioeconomic sectors. Despite the highly contrasting atmospheric states, mid and high-latitude boundary conditions do not reveal strong differences in these two winters. The two winters were associated with opposite ENSO phases, but there is no causal evidence of a remote forcing from the Pacific sea surface temperatures. Finally, the exceptionality of the two winters is demonstrated in relation to the last 140 years. It is suggested that these winters may be seen as archetypes of North Atlantic jet variability under current climate conditions.

Dynamical evolution of North Atlantic ridges and poleward Jet Stream displacements

The development of a particular wintertime atmospheric circulation regime over the North Atlantic, comprising a northward shift of the North Atlantic eddy-driven jet stream and an associated strong and persistent ridge in the subtropics, is investigated. Several different methods of analysis are combined to describe the temporal evolution of the events and relate it to shifts in the phase of the North Atlantic Oscillation and East Atlantic pattern. First, the authors identify a close relationship between northward shifts of the eddy-driven jet, the establishment and maintenance of strong and persistent ridges in the subtropics, and the occurrence of upper-tropospheric anticyclonic Rossby wave breaking over Iberia. Clear tropospheric precursors are evident prior to the development of the regime, suggesting a preconditioning of the Atlantic jet stream and an upstream influence via a large-scale Rossby wave train from the North Pacific. Transient (2–6 days) eddy forcing plays a dual role, contributing to both the initiation and then the maintenance of the circulation anomalies. During the regime there is enhanced occurrence of anticyclonic Rossby wave breaking, which may be described as low-latitude blocking-like events over the southeastern North Atlantic. A strong ridge is already established at the time of wave-breaking onset, suggesting that the role of wave-breaking events is to amplify the circulation anomalies rather than to initiate them. Wave breaking also seems to enhance the persistence, since it is unlikely that a persistent ridge event occurs without being also accompanied by wave breaking.

The Empirical Forcing Function as a tool for the diagnosis of large-scale atmospheric anomalies

The time-mean quasi-geostrophic potential vorticity equation of the atmospheric flow on isobaric surfaces can explicitly include an atmospheric (internal) forcing term of the stationary-eddy flow. In fact, neglecting some non-linear terms in this equation, this forcing can be mathematically expressed as a single function, called Empirical Forcing Function (EFF), which is equal to the material derivative of the time-mean potential vorticity. Furthermore, the EFF can be decomposed as a sum of seven components, each one representing a forcing mechanism of different nature. These mechanisms include diabatic components associated with the radiative forcing, latent heat release and frictional dissipation, and components related to transient eddy transports of heat and momentum. All these factors quantify the role of the transient eddies in forcing the atmospheric circulation. In order to assess the relevance of the EFF in diagnosing large-scale anomalies in the atmospheric circulation, the relationship between the EFF and the occurrence of strong North Atlantic ridges over the Eastern North Atlantic is analyzed, which are often precursors of severe droughts over Western Iberia. For such events, the EFF pattern depicts a clear dipolar structure over the North Atlantic; cyclonic (anticyclonic) forcing of potential vorticity is found upstream (downstream) of the anomalously strong ridges. Results also show that the most significant components are related to the diabatic processes. Lastly, these results highlight the relevance of the EFF in diagnosing large-scale anomalies, also providing some insight into their interaction with different physical mechanisms.