Previous Forecasts Research Articles

Multicycle ensemble forecasting of sea surface temperature

AbstractA novel extension to time‐lagged ensemble forecasting called multicycle ensemble forecasting improves the independent sampling of forecast model errors. Multicycle is defined such that each forecast cycle is independent of the previous forecast cycle. For an M cycle system the background field for each cycle is from a model hindcast M cycles earlier. The model errors have a factor M longer period to grow compared with a sequential system; however, the increased independence in the forecast model errors provide weighted ensemble averages with greater skill and reliability over the 0 lag forecast and a good spread‐error relationship. This cost‐efficient technique is relevant to global ocean forecasting where an ensemble method is computationally prohibitive.

The impact of sectoral economic development on the energy efficiency and CO2 emissions of road freight transport

The branches of economy differ in the amount and characteristics of freight transport services they require and use. Thus, different branches also have different energy efficiencies and carbon dioxide emissions from transport. Previous research has highlighted a serious lack of data inhibiting the understanding of these issues.This research presents a new method for analysing the relations between economic activity, transport demand, energy efficiency and carbon dioxide emissions with a great level of detail in different economic sectors. This is done for Finland by using the statistics that are available in many countries and are gathered in a harmonised manner in the EU member states. Hence, the method is applicable in other countries and enables in-depth comparison between countries. Understanding these relations is essential when national and also international policy targets for energy efficiency and CO2 emissions are set and evaluated.The CO2 intensity of Finnish road freight transport has decreased significantly and this development is forecasted to continue. The decrease can largely be attributed to the shift of balance from transporting bulk goods to transporting parcelled goods. This shift has been driven by diminishing importance of forest cluster and growing importance of technology cluster and trade. Despite of the reduced CO2 intensity, the energy efficiency has remained at a relatively constant level and the total CO2 emissions of road freight transport have increased.This study updates a previous national forecast for the energy efficiency and CO2 emissions of Finnish road freight transport sector for the year 2016. The new national forecast makes the outlook less positive, as the CO2 emissions are forecasted to be 8% higher than in the previous forecast. This difference is mainly due to higher estimates for average fuel consumption in some sectors. Two new branch-level forecasts are also presented and these give 20% higher CO2 emission levels than the original forecast, because of projected greater economic growth.

Corporate strategy and the environment: fit through teleological approaches

Complexity-based approaches to corporate strategy are particularly important in times of extensive environmental uncertainty where previous corporate predictions and forecasts regarding environmental changes frequently turn out to be invalid. The purpose of the article is to develop a framework that integrates corporate strategy and complexity-based teleological approaches. The framework is accompanied by propositions that contribute to literature by showing what teleological approaches are consistent within different corporate strategies and environmental settings. The propositions represent ways of achieving a fit between the number of freedom degrees in corporate strategy formulation and the level of environmental uncertainty. The application of teleological approaches in the context of corporate strategy generates additional and valuable insights to both theory and practice.

QUARTERLY ANALYSIS: The Progress of Monetary, Banking and Payment System Quarter III – 2012

The domestic economy is still growing quite well despite a slight slowdown. Indonesia’s economic growth in the third quarter of 2012 grew by 6.2%, slightly lower than previous forecasts due to a continuing decline in the performance of the external sector. Although consumption and domestic-orientated investment demand remains high, falling exports have resulted in decreased production and export-oriented investment. Looking ahead, economic growth is expected to rise again, driven by domestic consumption and investment which remains strong. Exports are predicted to also improve in line with the improving economy with some major trading partners, though it will still be shadowed by uncertainties in the global economic conditions. With these developments in the Indonesian economy for the entire year of 2012, the economy in 2013 is forecasted to grow 6.3% in rising into the range of 6.3% -6.7%.

Adaptive Spatiotemporal Smoothing of Seismicity for Long-Term Earthquake Forecasts in California

We present new methods for time‐independent earthquake forecasting that employ space–time kernels to smooth seismicity. The major advantage of the methods is that they do not require prior declustering of the catalog, circumventing the relatively subjective choice of a declustering algorithm. Past earthquakes are smoothed in space and time using adaptive Gaussian kernels. The bandwidths in space and time associated with each event are a decreasing function of the seismicity rate at the time and location of each earthquake. This yields a better resolution in space–time volumes of intense seismicity and a smoother density in volumes of sparse seismicity. The long‐term rate in each spatial cell is then defined as the median value of the temporal history of the smoothed seismicity rate in this cell. To calibrate the model, the earthquake catalog is divided into two parts: the early part (the learning catalog) is used to estimate the model, and the latter one (the target catalog) is used to compute the likelihood of the model’s forecast. We optimize the model’s parameters by maximizing the likelihood of the target catalog. To estimate the kernel bandwidths in space and time, we compared two approaches: a coupled near‐neighbor method and an iterative method based on a pilot density. We applied these methods to Californian seismicity and compared the resulting forecasts with our previous method based on spatially smoothing a declustered catalog (Werner et al. , 2011). All models use small M ≥2 earthquakes to forecast the rate of larger earthquakes and use the same learning catalog. Our new preferred model slightly outperforms our previous forecast, providing a probability gain per earthquake of about 5 relative to a spatially uniform forecast.

At a Glance …

Our baseline forecast is for global growth of 3.7 per cent in 2012. Growth will accelerate to 4 per cent in 2013. These forecasts are little changed from our previous forecast.As in our previous forecast, we assume a delayed but ultimately successful resolution of the Euro Area crisis. Nevertheless, we expect a mild recession in the Euro Area as a whole, as well as in the UK. Downside risks to the Euro Area remain high. Fiscal austerity will weigh on growth in the short term, while medium to long term structural problems remain unresolved.We forecast growth of about 2 per cent in the US this year, while China and India, although slowing, will continue to drive world growth.

Sudden transitions and grand variations in the solar dynamo, past and future

The solar dynamo is the exotic dance of the sun’s two major magnetic field components, the poloidal and the toroidal, interacting in anti-phase. On the basis of new data on the geomagnetic aa index, we improve our previous forecast of the properties of the current Schwabe cycle #24. Its maximum will occur in 2013.5 and the maximum sunspot number Rmax will then be 62 ± 12, which is within the bounds of our earlier forecasts. The subsequent analysis, based on a phase diagram, which is a diagram showing the relation between maximum sunspot numbers and minimum geomagnetic aa index values leads to the conclusion that a new Grand Episode in solar activity has started in 2008. From the study of the natural oscillations in the sunspot number time series, as found by an analysis based on suitable wavelet base functions, we predict that this Grand Episode will be of the Regular Oscillations type, which is the kind of oscillations that also occurred between 1724 and 1924. Previous expectations of a Grand (Maunder-type) Minimum of solar activity cannot be supported. We stress the significance of the Hallstatt periodicity for determining the character of the forthcoming Grand Episodes. No Grand Minimum is expected to occur during the millennium that has just started.

Publish or patent: Bibliometric evidence for empirical trade‐offs in national funding strategies

AbstractMultivariate linear regression models suggest a trade‐off in allocations of national research and development (R&D). Government funding and spending in the higher education sector encourage publications as a long‐term research benefit. Conversely, other components such as industrial funding and spending in the business sector encourage patenting. Our results help explain why the United States trails the European Union in publications: The focus in the United States is on industrial funding—some 70% of its total R&D investment. Likewise, our results also help explain why the European Union trails the United States in patenting, since its focus on government funding is less effective than industrial funding in predicting triadic patenting. Government funding contributes negatively to patenting in a multiple regression, and this relationship is significant in the case of triadic patenting. We provide new forecasts about the relationships of the United States, the European Union, and China for publishing; these results suggest much later dates for changes than previous forecasts because Chinese growth has been slowing down since 2003. Models for individual countries might be more successful than regression models whose parameters are averaged over a set of countries because nations can be expected to differ historically in terms of the institutional arrangements and funding schemes.

Rainfall-Runoff Model(s) Performance in the Blue Nile River

This paper presents the performance of some tested rainfall-runoff models to forecast river flows of the Blue Nile catchment up to Eddeim. Flow forecasting is an important step in river basin management in particular and water resources management in general. River flow models are used as components in actual flow forecasting schemes. They are also used in providing for efficient operation of storage reservoirs. Usually, flow forecasts are obtained in real time by transforming the input into a discharge using models. These forecasts may subsequently be modified or updated in accordance with the errors observed in the previous forecasts up to the time of making the new forecast. The system analysis or black box approach depends on a prior assumption of flexible linear and time invariant relationship the expression of which can be obtained by the application of systems analysis approach to records. The conceptual model provides an alternative approach in which the input-output transformation goes through a series of steps. In this study, systems and conceptual modelling techniques are applied to the Blue Nile catchment up to Eddeim of the Ethiopian high lands. The models were applied in non-parametric and parametric forms. Parameter optimisation is carried out by ordinary least squares, Rosenbrock, Simplex and genetic algorithm. The areal rainfall which is the main input to these models was estimated using arithmetic mean. However, attempts to estimate the areal rainfall by the Thiesen polygon method was made but the improvement in the model performance can not justify the amount of work involved in making Thiesen’s estimate. It is shown that the simple assumption of linearity is not adequate in modelling the rainfall runoff transformation. However, in the Blue Nile catchment, which exhibits a marked seasonal behaviour, good results were obtained with Linear Perturbation Model (LPM) which involves the assumption of linearity between the departures from seasonal expectations in input and output series. The application of the GFFS (collection of systems and conceptual models) software proved to be possible with variable efficiencies. The LPM in non-parametric or parametric form, the LVGF model, the ANN and the SMAR model can be used to forecast (reproduce) Ed-deim flows with high performance. Within the range of the tested models LPM was found to be the best candidate model that can forecast the flows under a wide range of conditions of marked seasonality by accounting for more than 90% of the initial variance.

Reverse weekend effect, trading volume, and illiquidity

PurposeThe purpose of this paper is to examine whether the seasonal anomaly known as the reverse weekend effect detected at index level can also be observed at individual stock level.Design/methodology/approachThis paper's methodology is based on the model first developed by Connolly and then employed by Chang, Pinegar, and Ravichandran in which returns are regressed against the dummy variable for Monday. In addition, the conditional variance is also included into the mean equation following Engle, Lilien, and Robins. Given the increasing evidence that equity returns are conditionally heteroskedastic, the paper includes in the conditional variance the lag of the squared residual from the mean equation (i.e. autoregressive conditional heteroskedasticity term introduced by Engle) and the previous period's forecast variance (i.e. the generalized autoregressive conditional heteroskedasticity term introduced by Bollerslev). Also, the paper controls for the different impact of good and bad news on the conditional variance following Glosten, Jaganathan, and Runkle.FindingsIt is found that the anomaly is widely distributed among large firms, not just confined to a few firms. The finding suggests that the anomaly at the index level is not driven by the extreme returns of a few firms. The paper also finds that the anomaly at the firm level is not evenly distributed across the weeks of the month. Furthermore, trading volume and illiquidity of individual firms can only partially explain the seasonal anomaly.Originality/valueThis paper extends the study of the reverse weekend effect in individual firms.

Rainfall assimilation using a new four-dimensional variational method: A single-point observation experiment

Accurate forecast of rainstorms associated with the mei-yu front has been an important issue for the Chinese economy and society. In July 1998 a heavy rainstorm hit the Yangzi River valley and received widespread attention from the public because it caused catastrophic damage in China. Several numerical studies have shown that many forecast models, including Pennsylvania State University National Center for Atmospheric Research’s fifth-generation mesoscale model (MM5), failed to simulate the heavy precipitation over the Yangzi River valley. This study demonstrates that with the optimal initial conditions from the dimension-reduced projection four-dimensional variational data assimilation (DRP-4DVar) system, MM5 can successfully reproduce these observed rainfall amounts and can capture many important mesoscale features, including the southwestward shear line and the low-level jet stream. The study also indicates that the failure of previous forecasts can be mainly attributed to the lack of mesoscale details in the initial conditions of the models.

Soil Initialization Strategy for Use in Limited-Area Weather Prediction Systems

Abstract Three diverse methods of initializing soil moisture and temperature in limited-area numerical weather prediction models are compared and assessed through the use of nonstandard surface observations to identify the approach that best combines ease of implementation, improvement in forecast skill, and realistic estimations of soil parameters. The first method initializes the limited-area model soil prognostic variables by a simple interpolation from a parent global model that is used to provide the lateral boundary conditions for the forecasts, thus ensuring that the limited-area model’s soil field cannot evolve far from the host model. The second method uses the soil properties generated by a previous limited-area model forecast, allowing the soil moisture to evolve over time to a new equilibrium consistent with the regional model’s hydrological cycle. The third method implements a new local soil moisture variational analysis system that uses screen-level temperature to adjust the soil water content, allowing the use of high-resolution station data that may be available to a regional meteorological service. The methods are tested in a suite of short-term weather forecasts performed with the Consortium for Small Scale Modeling (COSMO) model over the period September–November 2008, using the ECMWF Integrated Forecast System (IFS) model to provide the lateral boundary conditions. Extensive comparisons to observations show that substantial improvements in forecast skills are achievable with improved soil temperature initialization while a smaller additional benefit in the prediction of surface fluxes is possible with the soil moisture analysis. The analysis suggests that keeping the model prognostic variables close to equilibrium with the soil state, especially for temperature, is more relevant than correcting the soil moisture initial values. In particular, if a local soil analysis system is not available, it seems preferable to adopt an “open loop” strategy rather than the interpolation from the host global model analysis. This appears to be especially true for the COSMO model in its current operational configuration since the soil–vegetation–atmosphere transfer (SVAT) scheme of the ECMWF global host model and that of COSMO are radically diverse.

Consumer Impacts of BC’s Harmonized Sales Tax: Tax Grab or Pass-Through?

Introduction of the harmonized sales tax has upset much of the BC public, particularly for its perceived impact on the cost of living. This study examines misconceptions over the coverage, operation, and consumer impacts of the HST relative to the retail sales tax that it replaced; the study explains their structural and operational differences. Previous forecasts of the consumer impacts are reviewed and tested by the first quantitative analysis for British Columbia based on data since the HST was implemented. The key finding is that the HST has raised BC’s cost of living by 0.5 to 0.6 percent, which is consistent with businesses having passed through to consumers all of their tax savings related to in-province sales. The study offers policy options for offsetting even the small consumer impact of the HST and improving its public acceptance.

Consumer Impacts of BC's Harmonized Sales Tax: Tax Grab or Pass-Through?

Introduction of the harmonized sales tax has upset much of the BC public, particularly for its perceived impact on the cost of living. This study examines misconceptions over the coverage, operation, and consumer impacts of the HST relative to the retail sales tax that it replaced; the study explains their structural and operational differences. Previous forecasts of the consumer impacts are reviewed and tested by the first quantitative analysis for British Columbia based on data since the HST was implemented. The key finding is that the HST has raised BC's cost of living by 0.5 to 0.6 percent, which is consistent with businesses having passed through to consumers all of their tax savings related to in-province sales. The study offers policy options for offsetting even the small consumer impact of the HST and improving its public acceptance.

A long-term earthquake forecast for the Kuril-Kamchatka arc for the period from September 2010 to August 2015 and the reliability of previous forecasts, as well as their applications

We describe results from the ongoing 2008–2010 work on long-term earthquake prediction for the Kuril-Kamchatka arc based on the patterns of seismic gaps and the seismic cycle. We provide a forecast for the next 5 years, September 2010 to August 2015, specified for all segments of the earthquake-generating Kuril-Kamchatka arc zone. For 20 segments we predict the phases of the seismic cycle, the normalized rate of small earthquakes (A10), the magnitudes of moderate earthquakes to be expected with probabilities of 0.8, 0.5, and 0.15, the maximum possible magnitudes, and the probabilities of great (M ≥ 7.7) earthquakes. It is shown that the forecast given for the previous 5 years, from September 2005 to September 2010, was found to be accurate. We report the measures that were taken for seismic safety and retrofitting based on these forecasts.

Global earthquake forecasts

SUMMARY We have constructed daily worldwide long- and short-term earthquake forecasts. These forecasts specify the earthquake rate per unit area, time and magnitude on a 0.5 degree grid for a global zone region between 75N and 75S latitude (301 by 720 grid cells). We use both the Global Centroid Moment Tensor (GCMT) and Preliminary Determinations of Epicenters (PDE) catalogues. Like our previous forecasts, the new forecasts are based largely on smoothed maps of past seismicity and assume spatial and temporal clustering. The forecast based on the GCMT catalogue, with the magnitude completeness threshold 5.8, includes an estimate of focal mechanisms of future earthquakes and of the mechanism uncertainty. The forecasted tensor focal mechanism makes it possible in principle to calculate an ensemble of seismograms for each point of interest on the Earth's surface. We also introduce a new approach that circumvents the need for focal mechanisms. This permits the use of the PDE catalogue that reliably documents many smaller quakes with a higher location accuracy. The result is a forecast at a higher spatial resolution and down to a magnitude threshold below 5.0. Such new forecasts can be prospectively tested within a relatively short time, such as a few years, because smaller events occur with greater frequency. The forecast's efficiency can be measured by its average probability gains per earthquake compared to the spatially or temporally uniform Poisson distribution. For the short-term forecast the gain is about 2.0 for the GCMT catalogue and 3.7 for the PDE catalogue relative to a temporally random but spatially localized null hypothesis. Preliminary tests indicate that for the long-term global spatial forecast the gain is of the order 20–25 compared to the uniform event distribution over the Earth's surface. We can also prospectively test the long-term forecast to check whether it can be improved.

Space- and Time-Dependent Probabilities for Earthquake Fault Systems from Numerical Simulations: Feasibility Study and First Results

In weather forecasting, current and past observational data are routinely assimilated into numerical simulations to produce ensemble forecasts of future events in a process termed “model steering”. Here we describe a similar approach that is motivated by analyses of previous forecasts of the Working Group on California Earthquake Probabilities (WGCEP). Our approach is adapted to the problem of earthquake forecasting using topologically realistic numerical simulations for the strike-slip fault system in California. By systematically comparing simulation data to observed paleoseismic data, a series of spatial probability density functions (PDFs) can be computed that describe the probable locations of future large earthquakes. We develop this approach and show examples of PDFs associated with magnitude M > 6.5 and M > 7.0 earthquakes in California.

Earthquake Forecasting in Diverse Tectonic Zones of the Globe

We present a simple method for long- and short-term earthquake forecasting (estimating earthquake rate per unit area, time, and magnitude). For illustration we apply the method to the Pacific plate boundary region and the Mediterranean area surrounding Italy and Greece. Our ultimate goal is to develop forecasting and testing methods to validate or falsify common assumptions regarding earthquake potential. Our immediate purpose is to extend the forecasts we made starting in 1999 for the northwest and southwest Pacific to include somewhat smaller earthquakes and then adapt the methods to apply in other areas. The previous forecasts used the CMT earthquake catalog to forecast magnitude 5.8 and larger earthquakes. Like our previous forecasts, the new ones here are based on smoothed maps of past seismicity and assume spatial clustering. Our short-term forecasts also assume temporal clustering. An important adaptation in the new forecasts is to abandon the use of tensor focal mechanisms. This permits use of earthquake catalogs that reliably report many smaller quakes with no such mechanism estimates. The result is that we can forecast earthquakes at higher spatial resolution and down to a magnitude threshold of 4.7. The new forecasts can be tested far more quickly because smaller events are considerably more frequent. Also, our previous method used the focal mechanisms of past earthquakes to estimate the preferred directions of earthquake clustering, however the method made assumptions that generally hold in subduction zones only. The new approach escapes those assumptions. In the northwest Pacific the new method gives estimated earthquake rate density very similar to that of the previous forecast.

A variational method for correcting non-systematic errors in numerical weather prediction

A variational method based on previous numerical forecasts is developed to estimate and correct non-systematic component of numerical weather forecast error. In the method, it is assumed that the error is linearly dependent on some combination of the forecast fields, and three types of forecast combination are applied to identifying the forecasting error: 1) the forecasts at the ending time, 2) thecombination of initial fields and the forecasts at the ending time, and 3) the combination of the forecasts at the ending time and the tendency of the forecast. The Single Value Decomposition (SVD) of the covariance matrix between the forecast and forecasting error is used to obtain the inverse mapping from flow space to the error space during the training period. The background covariance matrix is hereby reduced to a simple diagonal matrix. The method is tested with a shallow-water equation model by introducing two different model errors. The results of error correction for 6, 24 and 48 h forecasts show that the method is effective for improving the quality of the forecast when the forecasting error obviously exceeds the analysis error and it is optimal when the third type of forecast combinations is applied.

Peter Buerhaus Talks about the Nursing Shortage

Dr. Peter I. Buerhaus, senior associate dean for research and Valerie Pott er Professor of Nursing at Vanderbilt University School of Nursing, is a coauthor of " Nurse Staffing in Hospitals: Is There a Business Case for Quality? " published in Health Affairs, 25, no. 1 (2006): 204-211. In this excerpt from an interview with Marie Manthey, Dr. Buerhaus talks about his projections for the nursing profession in the near and long term. Marie Manthey: In the long run, where do you see the demand for nursing going? Peter Buerhaus: North. Straight north. In the short run, the demand for nurses is going to increase. But if the supply doesn ' t catch up with the demand, that demand will shift to other [roles]. What I would like to suggest is that there are no good substitutes. That ' s maybe not the best choice of words, but there are not good substitutes for nurses. Therefore the demand will continue to rise as more and more baby boomers are aging. They are now beginning to turn 65, but the really big wave will come in another 7 to 9 years. All through the next decade we are going to see this steady march of people. Marie: That ' s just the replacement factor, though, isn ' t it? Peter: No, this is on the demand side. All these people are turning older and consuming more health care, and the demand for health care and nursing will continue to rise. Not only are there large numbers of people gett ing older; they will be wealthier. They will have more income to spend on care, and the variety of ways for them to spend it is only increasing. Marie: That will increase the entrepreneurial opportunities for nurses to capitalize personally on that. Peter: Absolutely. Marie: Some of your latest work indicates that the shortage is not going to be as bad as we had been predicting-that the increases in supply have happened pretty quickly. Am I reading that correctly? Peter: Yes. The big story is that our previous forecasts, if we accepted the demand estimates as accurate, showed us facing a shortage of around 800,000 nurses by the year 2020. Our recent forecasts have reduced that figure to about 340,000. It's a significant improvement, but I would say that, instead of a category 5 hurricane, we now have a category 4, and it can still kill you. We still project that graduation rates would need to rise by 50% to meet the increased demand and make up for impending retirements. Marie: Are you as amazed as I am at the popularity of the postbaccalaureate programs that are growing up? The second and third career choices? Peter: Absolutely. There?s a combination of factors responsible for this upturn in interest in nursing. When 9/11 occurred, a lot of people paused and considered what they were doing: their careers, their jobs. …