Role of the metric in forecast error growth: how chaotic is the weather?

The atmosphere is often cited as an archetypal example of a chaotic system, where prediction is limited by the model's sensitivity to initial conditions. Experiments have indeed shown that forecast errors, as measured in 500 hPa heights, can double in 1.5 d or less. Recent work, however, has shown that, when errors are measured in total energy, model error is the primary contributor to forecast inaccuracy. In this paper we attempt to reconcile these apparently conflicting sets of results by examining the role of the chosen metric. Using a simple medium-dimensional model for illustration, it is found that the metric has a strong effect, not just on apparent error growth, but on the perceived causes of error. If an insufficiently global metric is used, then it may appear that error is due to sensitivity to initial condition, when in fact it is caused by sensitivity to error in the other variables. If the goal is to diagnose the causes of error, a sufficiently global metric must be used. The simple model is used to predict the internal rate of growth of the ECMWF operational model, and preliminary results compared. It is found that both 500 hPa and total energy results are consistent with high model error and a relatively low internal rate of growth. Experiments are suggested to further verify the results for weather models.     

A geo-information system approach for forest fire likelihood based on causative and anti-causative factors

Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant.

The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time.     

Bayesian perspective of the unconventional approach for assimilating aliased radar radial velocities

The global minimization problem for directly assimilating aliased radial velocities is derived in terms of Bayesian estimation by folding the domain of the original Gaussian non-aliased observation probability density function (pdf) into the Nyquist interval. By truncating the folded tails of the observation pdf, the observation term in the costfunction recovers the aliased observation term formulated previously by an unconventional approach. This establishes the theoretical basis for the unconventional approach and quantifies the involved approximation. The alias-robust radar wind analysis developed based on the unconventional approach is also revisited from the Bayesian perspective.     

A skeleton design theory for spatial data infrastructure

In this paper, we look into the theory of designing geoservice systems, i.e., SDI networks and their constituent SDI nodes. As the field of SDI is strongly about bridging between geoservice systems, interoperability and harmonisation, it is not surprising that standardisation efforts are of crucial importance in it. These efforts have historically addressed abstract and concrete content models for data and metadata exchange, as well as abstract and concrete behavioural models for computational processes. The list of standards that are in use in the SDI field continues to expand, and reaches out to neighbouring fields such as sensor nets. We argue that given these trends, the resulting levels of standardisation in actual systems, and the complexity of geoservice systems in general, it appears only natural to look into the possibility to define a standardised design theory for SDI and its nodes, which addresses the function base and the communication base. Specifically, we provide an overview of those components that need to be designed, and what are their relationships. We do so in an abstract way, focussing on the concern of information content in this paper, and only hinting at an appropriate theory of realisation based on our skeleton theory.     

美国北加州吉塞尔斯诱发地震与热汽田特征的关系

吉塞尔斯地震活动可能是因蒸汽开发引起的.水在一个承受很高构造剪应力和应变的大范围破裂体中汽化为蒸汽。 汽田地震震源机制解与区域构造应变场几乎一致,并且在该区域范围内汽田地震与别的构造地震不易区分。观测中注意到地震活动与注液历史无关,这表明孔隙水压力增高与注液不可能是吉塞尔斯诱发地震的成因。 相反,所有证据都表明诱发地震与孔隙水压力及温度降低有关。形成机制有两种最大可能:其一,是裂隙排水(汽)导致局部剪应力增加所致,其二,是由稳定滑动转化为不稳定滑动(粘滑)。没有其它记载的诱发地震机制与吉塞尔斯汽田条件相符。     

Spectral surface albedo over Morocco and its impact on radiative forcing of Saharan dust

In May–June 2006, airborne and ground-based solar (0.3–2.2 μm) and thermal infrared (4–42 μm) radiation measurements have been performed in Morocco within the Saharan Mineral Dust Experiment (SAMUM). Upwelling and downwelling solar irradiances have been measured using the Spectral Modular Airborne Radiation Measurement System (SMART)-Albedometer. With these data, the areal spectral surface albedo for typical surface types in southeastern Morocco was derived from airborne measurements for the first time. The results are compared to the surface albedo retrieved from collocated satellite measurements, and partly considerable deviations are observed. Using measured surface and atmospheric properties, the spectral and broad-band dust radiative forcing at top-of-atmosphere (TOA) and at the surface has been estimated. The impact of the surface albedo on the solar radiative forcing of Saharan dust is quantified. In the SAMUM case of 19 May 2006, TOA solar radiative forcing varies by 12 W m⁻² per 0.1 surface-albedo change. For the thermal infrared component, values of up to +22 W m⁻² were derived. The net (solar plus thermal infrared) TOA radiative forcing varies between −19 and +24 W m⁻² for a broad-band solar surface albedo of 0.0 and 0.32, respectively. Over the bright surface of southeastern Morocco, the Saharan dust always has a net warming effect.     

A model for large glacial–interglacial climate-induced changes in dust and sea salt concentrations in deep ice cores (central Antarctica): palaeoclimatic implications and prospects for refining ice core chronologies

A semi-empirical model has been developed to reproduce glacial–interglacial changes of continental dust and marine sodium concentrations (factor of ∼50 and ∼5, respectively) observed in inland Antarctic ice cores. The model uses conceptual pathways of aerosols within the high troposphere; assumes the dry deposition of impurities on the Antarctic surface; uses estimates of aerosol transit times taken independent of climate; assumes a temperature-dependent removal process during aerosol pathways from the mid-latitudes. The model is fitted to the data over the last four climate cycles from Vostok and EPICA Dome C Antarctic sites. As temperature is cooling, the aerosol response suggests different modes of climate couplings between latitudes, which can be continuous or below temperature thresholds for sodium and dust, respectively. The model estimates a southern South America dust source activity two to three times higher for glacial periods than for the Holocene and a glacial temperature over the Southern Ocean 3–5 °C cooler. Both estimates appear consistent with independent observations. After removal of temperature effects, dust and sodium residuals for both sites show orbital frequencies in opposite phase at the precession timescale. Such long-term insolation-related modulation of terrestrial and marine aerosol input, could provide a chemical pacemaker useful for refining ice core chronologies.     

An efficient retrospective optimal interpolation algorithm compared with the fixed-lag Kalman smoother by assuming a perfect model

We developed an efficient retrospective optimal interpolation (ROI) algorithm by which we can avoid the overlap of model integration periods, which appears in the procedure of evolving a previous analysis error covariance. If the fixed-lag Kalman smoother (FLKS) is used to determine the analysis state at the beginning of the fixed analysis window as is done for ROI, the FLKS can be considered a suboptimal version of the efficient ROI when the involved model is non-linear and has no errors. We confirm that the efficient ROI analyses are more accurate than the FLKS analyses with the increase of the analysis window size. Nevertheless, the computation costs for implementing efficient ROI are almost the same as those for FLKS. Additionally, the reduced-rank version of the efficient ROI is developed based on the accuracy-saturation property.
From the experiments using Lorenz 3-variable model, it is confirmed that the non-linearity of numerical model, which becomes stronger with the increase of the analysis window size, makes the analysis of efficient ROI more accurate than that of FLKS. Our Lorenz 40-variable experiments show that the average analysis error of the efficient ROI is smaller than that of the FLKS for an analysis window size of up to 4 d. However, the efficient ROI and the FLKS requires almost the same costs for computation. From the results of Lorenz 40-variable model experiments, it is suggested that, by using the reduced-rank formulation of the efficient ROI, we can obtain the suboptimal analysis more cost-effectively rather than FLKS.     

The H2/CO ratio of emissions from combustion sources: comparison of top-down with bottom-up measurements in southwest Germany

The hydrogen-to-carbon monoxide (H₂/CO) emission ratio of anthropogenic combustion sources was determined from more than two years of quasi-continuous atmospheric observations in Heidelberg (49°24' N, 8°42' E), located in the polluted Rhein-Neckar region. Evaluating concurrent mixing ratio changes of H₂ and CO during morning rush hours yielded mean molar H₂/CO ratios of 0.40 ± 0.06, while respective results inferred from synoptic pollution events gave a mean value of 0.31 ± 0.05 mole H₂/mole CO. After correction for the influence of the H₂ soil sink on the measured ratios, mean values of 0.46 ± 0.07 resp. 0.48 ± 0.07 mole H₂/mole CO were obtained, which are in excellent agreement with direct source studies of traffic emissions in the Heidelberg/Mannheim region (0.448 ± 0.003 mole H₂/mole CO). Including results from other European studies, our best estimate of the mean H₂/CO emission ratio from anthropogenic combustion sources (mainly traffic) ranges from 0.45 to 0.48 mole H₂/mole CO, which is about 20% smaller than the value of 0.59 mole H₂/mole CO which is frequently used as the basis to calculate global H₂ emissions from anthropogenic combustion sources.