The TOPEX/Poseidon andERS-1/2satellites have now been observing sea level anomalies for a continuous time span of more than 6 yr. These sea level observations are first compared with tide gauge data ...and then assimilated into an ocean model that is used to initialize coupled ocean–atmosphere forecasts with a lead time of 6 months. Ocean analyses in which altimeter data are assimilated are compared with those from a no-assimilation experiment and with analyses in which subsurface temperature observations are assimilated. Analyses with altimeter data show variations of upper-ocean heat content similar to analyses using subsurface observations, whereas the ocean model has large errors when no data are assimilated. However, obtaining good results from the assimilation of altimeter data is not straightforward: it is essential to add a good mean sea level to the observed anomalies, to filter the sea level observations appropriately, to start the analyses from realistic initial temperature and salinity fields, and to assign appropriate weights for the analyzed increments.
To assess the impact of altimeter data assimilation on the coupled system, ensemble hindcasts are initialized from ocean analyses in which either no data, subsurface temperatures, or sea level observations were assimilated. For each kind of ocean analysis, a five-member ensemble is started every 3 months from January 1993 to October 1997, adding up to 100 forecasts for each type. The predicted SST anomalies for the equatorial Pacific are intercompared between the experiments and against observations. The predicted anomalies are on average closer to observed values when forecasts are initialized from the ocean analysis using altimeter data than when initialized from the no-assimilation ocean analysis, and forecast errors appear to be only slightly larger than for forecasts initialized from ocean analyses using subsurface temperatures. However, even based on 100 coupled forecasts, the distinction between the two experiments that benefit from data assimilation is barely statistically significant. The verification should still be considered preliminary, because the period covered by the forecasts is only 5 yr, which is too short properly to sample ENSO variability. It is, nonetheless, encouraging that altimeter assimilation can improve the forecast skill to a level comparable to that obtained from using Tropical Ocean Atmosphere–expendable bathythermograph data.
Seasonal forecasts are subject to various types of errors: amplification of errors in oceanic initial conditions, errors due to the unpredictable nature of the synoptic atmospheric variability, and ...coupled model error. Ensemble forecasting is usually used in an attempt to sample some or all of these various sources of error. How to build an ensemble forecasting system in the seasonal range remains a largely unexplored area. In this paper, various ensemble generation methodologies for the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system are compared. A series of experiments using wind perturbations (applied when generating the oceanic initial conditions), sea surface temperature (SST) perturbations to those initial conditions, and random perturbation to the atmosphere during the forecast, individually and collectively, is presented and compared with the more usual lagged-average approach. SST perturbations are important during the first 2 months of the forecast to ensure a spread at least equal to the uncertainty level on the SST measure. From month 3 onward, all methods give a similar spread. This spread is significantly smaller than the rms error of the forecasts. There is also no clear link between the spread of the ensemble and the ensemble mean forecast error. These two facts suggest that factors not presently sampled in the ensemble, such as model error, act to limit the forecast skill. Methods that allow sampling of model error, such as multimodel ensembles, should be beneficial to seasonal forecasting.
The purpose of this study is to present a hypothesis to explain the aetiology of bovine spongiform encephalopathy (BSE) which is more credible than any at present available, and to increase its ...credibility by varying the hypothesis to supply explanations for Alzheimer’s disease, Parkinson’s disease and certain other conditions.
The method used has been to utilize material from biochemical textbooks and similar sources.
It has been concluded that BSE is caused by the failure to synthesize sufficient cyclic guanosine monophosphate (cGMP), with the result that neurons die because they are no longer able to prevent the entry of toxic quantities of calcium ions into their cytoplasm. Several causes for the failure to synthesize sufficient cGMP have been identified; these involve selenium and folate deficiencies, and problems with the availability of nicotinamide adenosine dinucleotide (NAD). It is proposed that BSE is initiated by a combination of selenium deficiency and the destruction of NAD by a bacterial toxin of the same type as causes cholera, that folate deficiency is the predominant cause of Alzheimer’s disease, and that the failure to synthesize sufficient tetrahydrobiopterin and cGMP from guanosine triphosphate results in Parkinson’s disease.
Nothing stimulates thought and innovation more than the discovery that the knowledge and skills that are needed to achieve a desired end are unavailable: nothing prevents progress more than the ...dogmatic application of flawed hypotheses which have never been adequately tested. This paper is based upon practical experience and upon the contents of the 10th edition of Soil Conditions and Plant Growth by E.W. Russell which was published in 1973. The scientific principles which should underlie soil management practices have been known for many years but have not attracted the attention they deserve by modern agricultural scientists. Resorting to an old textbook in this situation is fully justified. (Original abstract)
This paper is an evaluation of the role of salinity in the framework of temperature data assimilation in a global ocean model that is used to initialize seasonal climate forecasts. It is shown that ...the univariate assimilation of temperature profiles, without attempting to correct salinity, can induce first-order errors in the subsurface temperature and salinity fields. A recently developed scheme by A. Troccoli and K. Haines is used to improve the salinity field. In this scheme, salinity increments are derived from the observed temperature, by using the model temperature and salinity profiles, assuming that the temperature-salinity relationship in the model profiles is preserved. In addition, the temperature and salinity fields are matched below the observed temperature profile by vertically displacing the original model profiles. Two data assimilation experiments were performed for the 6-yr period 1993-98. These show that the salinity scheme is effective at maintaining the haline and thermal structures at and below thermocline level, especially in tropical regions, by avoiding spurious convection. In addition to improvements in the mean state, the scheme allows more temporal variability than simply controlling the salinity field by relaxation to climatological data. Some comparisons with sparse salinity observations are also made, which suggest that the subsurface salinity variability in the western Pacific is better reproduced in the experiment in which the salinity scheme is used. The salinity analyses might be improved further by use of altimeter sea level or sea surface salinity observations from satellite.
In this paper, the combined assimilation of satellite observed sea level anomalies and in situ temperature data into a global ocean model, which is used to initialize a coupled ocean–atmosphere ...forecast system, is described. The altimeter data are first used to create synthetic temperature observations, which are then combined with the directly observed temperature profiles in an optimum interpolation scheme. In addition to temperature, salinity is corrected based on a preservation of the model’s local temperature–salinity relationship. Coupled forecasts with a lead time of up to 6 months are initialized from the ocean analyses and the impact of the data assimilation on both the ocean analysis and the coupled forecasts is investigated. It is shown that forecasts of sea surface temperature anomalies in the Niño-3 area can be improved by initializing the coupled forecast model with the ocean analysis in which temperature and altimeter data are assimilated in combination. The results further imply that a good simulation of the salinity field is required to make optimum use of the altimeter data.
There is widespread confusion over the causes of obesity and late onset diabetes. Suggests that obesity, diabetes and most of the other diseases of civilisation are manifestations of selenium ...deficiency in association with one or more other problems. In general, the worse the quality of the diet that it consumed, the more refined carbohydrate and saturated fat it contains and the more has to be swallowed to supply the vitamins and minerals the body needs. But even when diets containing recommended quantities of fruit and vegetables are being consumed, obesity and ill health can develop when the intake of selenium is insufficient. (Quotes from original text)
In this paper the performance of the global coupled general circulation model (CGCM) ECHO-2, which was integrated for 10 years without the application of flux correction, is described. Although the ...integration is rather short, strong and weak points of this CGCM can be clearly identified, especially in view of the model's performance of the annual cycle in the tropical Pacific. The latter is simulated with more success relative to the earlier version, ECHO-1. A better representation of the low-level stratus clouds in the atmosphere model associated with a reduction in the shortwave radiative flux at the air-sea interface improved the coupled model's performance in the southeastern tropical oceans, with a strongly reduced warm bias in these regions. Modifications in the atmospheric convection scheme also eliminated the AGCM's tendency to simulate a double ITCZ, and this behavior is maintained in the CGCM simulation. Finally, a new numerical scheme for active tracer advection in the ocean model strongly reduced the numerical mixing, which seems to enhance considerably the level of interannual variability in the equatorial Pacific. One weak point is an overall cold bias in the Tropics and midlatitudes, which typically amounts to 1 degrees C in open ocean regions. Another weak point is the still too strong equatorial cold tongue, which penetrates too far into the western equatorial Pacific. Although this model deficiency is not as pronounced as in ECHO-1, the too strong cold tongue reduces the level of interannual rainfall variability in the western and central equatorial Pacific. Finally, the interannual fluctuations in equatorial Pacific sea surface temperatures (SSTs) are too equatorially trapped, a problem that is also found in ``ocean-only'' simulations. Overall, however, the authors believe that the ECHO-2 CGCM has been considerably improved relative to ECHO-1.
We analyze the stratospheric waves in models participating in phase 1 of the Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi‐Biennial Oscillation initiative (QBOi). All ...models have robust Kelvin and mixed Rossby‐gravity wave modes in winds and temperatures at 50 hPa and represent them better than most of the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. There is still some spread among the models, especially concerning the mixed Rossby‐gravity waves. We attribute the variability in equatorial waves among the QBOi models in part to the varying horizontal and vertical resolutions, to systematic biases in zonal winds, and to the considerable variability in convectively coupled waves in the troposphere among the models: only roughly half of the QBOi models have realistic convectively coupled Kelvin waves and only a few models have convectively coupled mixed Rossby‐gravity waves. The models with stronger convectively coupled waves tend to produce larger zonal mean forcing due to resolved waves in the QBO region. Finally we evaluate the Eliassen–Palm (EP) flux and EP flux divergence of the resolved waves in the QBOi models. We find that there is a large spread in the forcing from resolved waves in the QBO region, and the resolved wave forcing has a robust correlation with model vertical resolution.
The QBOi models vary widely in their ability to simulate equatorial waves and in the magnitude of resolved wave‐forcing contributing to the driving of the model QBO. In the QBOi models, despite the varying set‐ups, vertical resolution emerged as a clear factor controlling the degree of wave forcing in the eastward QBO shear zones. This figure shows how the wave forcing due to resolved large‐scale eastward propagating waves relates to model vertical and horizontal resolution.
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