利用遥感技术建立墨西哥热带地上生物量模型(英文)

Spatially-explicit estimation of aboveground biomass(AGB) plays an important role to generate action policies focused in climate change mitigation,since carbon(C) retained in the biomass is vital for regulating Earth’s temperature.This work estimates AGB using both chlorophyll(red,near infrared) and moisture(middle infrared) based normalized vegetation indices constructed with MCD43A4 MODerate-resolution Imaging Spectroradiometer(MODIS) and MOD44B vegetation continuous fields(VCF) data.The study area is located in San Luis Potosí,Mexico,a region that comprises a part of the upper limit of the intertropical zone.AGB estimations were made using both individual tree data from the National Forest Inventory of Mexico and allometric equations reported in scientific literature.Linear and nonlinear(expo-nential) models were fitted to find their predictive potential when using satellite spectral data as explanatory variables.Highly-significant correlations(p = 0.01) were found between all the explaining variables tested.NDVI62,linked to chlorophyll content and moisture stress,showed the highest correlation.The best model(nonlinear) showed an index of fit(Pseudo-r2) equal to 0.77 and a root mean square error equal to 26.00 Mg/ha using NDVI62 and VCF as explanatory variables.Validation correlation coefficients were similar for both models:lin-ear(r = 0.87**) and nonlinear(r = 0.86**).     

The influence of hurricane risk on tourist destination choice in the Caribbean

Climate change could have major implications for the global tourism industry if changing environmental conditions alter the attractiveness of holiday destinations. Countries with economies dependent on tourism and with tourism industries reliant on vulnerable natural resources are likely to be particularly at risk. We investigate the implications that climate-induced variations in Atlantic hurricane activity may have for the tourism-dependent Caribbean island of Anguilla. Three hundred tourists completed standardised questionnaires and participated in a choice experiment to determine the influence hurricane risk has on their risk perceptions and decisions regarding holiday preferences. The hurricane season had been considered by 40?% of respondents when making their holiday choice, and the beaches, climate and tranquility of the island were more important than coral reef-based recreational activities in determining holiday destination choice. Choice models demonstrated that respondents were significantly less likely to choose holiday options where hurricane risk is perceived to increase, and significantly more likely to choose options that offered financial compensation for increased risk. However, these choices and decisions varied among demographic groups, with older visitors, Americans, and people who prioritize beach-based activities tending to be most concerned about hurricanes. These groups comprise a significant component of the island’s current clientele, suggesting that perceived increases in hurricane risk may have important implications for the tourism economy of Anguilla and similar destinations. Improved protection of key environmental features (e.g. beaches) may be necessary to enhance resilience to potential future climate impacts.     

A seasonal study of the atmospheric dynamics over the Iberian Peninsula based on circulation types

A seasonal analysis of the atmospheric circulation over the Iberian Peninsula (IP) based on circulation types (CTs) obtained from sea level pressure and 500-hPa geopotential height is presented. The study covers the period of 1958–2008, when a high variability and important changes in winter and spring precipitation and temperature have been reported. Frequency, persistence, and the most probable transitions of the circulation types are analyzed. Among the clustering methods available in the literature, two of the most reliable classification methods have been tested, K-means and simulated annealing and diversified randomization. A comparison of both methods over the IP is presented for winter (DJF). The quality of the circulation types obtained through both methods as well as the better stability achieved by K-means suggest this method as more appropriated for our target area. Twelve CTs were obtained for each season and were analyzed. The patterns obtained were regrouped in five general situations: anticyclonic, cyclonic, zonal, summertime, and hybrid-mixed. The analysis of frequencies of these situations offers a similar characterization of the atmospheric circulation that others previously obtained by subjective methods. The analysis of the trends in frequency and persistence for each CT shows few significant trends, mainly in winter and spring with a general decrease of the cyclonic patterns and an increase of the anticyclonic situations. This can be related to the negative precipitation trends reported by other authors. Regarding the persistence, an interesting result is that there is a high interannual variability of the persistence in autumn and spring, when patterns can persist longer than in other seasons. An analysis of the most probable transitions between the CTs has been performed, revealing the existence of cyclic sequences in all seasons. These sequences are related to the high frequency of certain patterns such as the anticyclonic situations in winter. Finally, a clear seasonal dependence of the transitions between cyclonic situations associated with extratropical disturbances was found. This dependence suggests that the transitions of low-pressure systems towards the south of the IP are more likely in spring and autumn than in winter.     

Strategies to mitigate aliasing of loading signals while estimating GPS frame parameters

Although GNSS techniques are theoretically sensitive to the Earth center of mass, it is often preferable to remove intrinsic origin and scale information from the estimated station positions since they are known to be affected by systematic errors. This is usually done by estimating the parameters of a linearized similarity transformation which relates the quasi-instantaneous frames to a long-term frame such as the International Terrestrial Reference Frame (ITRF). It is well known that non-linear station motions can partially alias into these parameters. We discuss in this paper some procedures that may allow reducing these aliasing effects in the case of the GPS techniques. The options include the use of well-distributed sub-networks for the frame transformation estimation, the use of site loading corrections, a modification of the stochastic model by downweighting heights, or the joint estimation of the low degrees of the deformation field. We confirm that the standard approach consisting of estimating the transformation over the whole network is particularly harmful for the loading signals if the network is not well distributed. Downweighting the height component, using a uniform sub-network, or estimating the deformation field perform similarly in drastically reducing the amplitude of the aliasing effect. The application of these methods to reprocessed GPS terrestrial frames permits an assessment of the level of agreement between GPS and our loading model, which is found to be about 1.5 mm WRMS in height and 0.8 mm WRMS in the horizontal at the annual frequency. Aliased loading signals are not the main source of discrepancies between loading displacement models and GPS position time series.     

A lunar cryptomare dome near Mee H and Drebbel F

In this study, we examine the lunar mare dome Mee 1 situated near the craters Mee H and Drebbel F in a region showing evidence of ancient (pre-Orientale) mare volcanism and cryptomare deposits. Regional stratigraphic relations indicate that Mee 1 was formed prior to the Orientale impact at the beginning of the Imbrian period. Based on a combined photoclinometry and shape from shading technique applied to telescopic CCD images of the dome acquired under oblique illumination, we determined a diameter of Mee 1 of 25 km, a height of 250 m, a flank slope of 1.15^°, and a volume of . Based on rheologic modelling of the dome and a viscoelastic model of the feeder dike, we obtained a magma viscosity of , an effusion rate of , a duration of the effusion process of 1.6 years, a magma rise speed of , a width of the feeder dike of 32 m, and a horizontal dike length of 144 km. A comparison of Mee 1 with domes with similar morphometric properties, which are located near Milichius and inside the crater Petavius, reveals strong similarities with respect to the viscosity of the dome-forming magma and the feeder dike geometry, while the effusion rate and magma rise speed of Mee 1 are somewhat higher. The pronounced morphometric differences between Mee 1 and a smaller dome situated close to the crater Doppelmayer and characterised by a similar magma viscosity suggest that the growth of that dome was limited by exhaustion of the magma reservoir, while Mee 1 and the other larger domes display morphometric properties presumably coming closer to the cooling limit. The comparison of the ancient dome Mee 1 with the younger (Eratosthenian) edifices near Milichius and Doppelmayer suggests that the conditions in the upper mantle and the crust favoured high eruption volumes, effusion rates, and magma rise speeds, implying the occurrence of large magma reservoirs preventing the limitation of dome growth by magma exhaustion. On the other hand, we observe similar general morphometric, rheologic, and feeder dike characteristics and, thus, conclude that the formation conditions of lunar mare domes did not change fundamentally during the Imbrian period.     

Assessing the hydrological and geomorphic behaviour of a landscape evolution model within a limits-of-acceptability uncertainty analysis framework

Landscape evolution models (LEMs) have the capability to characterize key aspects of geomorphological and hydrological processes. However, their usefulness is hindered by model equifinality and paucity of available calibration data. Estimating uncertainty in the parameter space and resultant model predictions is rarely achieved as this is computationally intensive and the uncertainties inherent in the observed data are large. Therefore, a limits-of-acceptability (LoA) uncertainty analysis approach was adopted in this study to assess the value of uncertain hydrological and geomorphic data. These were used to constrain simulations of catchment responses and to explore the parameter uncertainty in model predictions. We applied this approach to the River Derwent and Cocker catchments in the UK using a LEM CAESAR-Lisflood. Results show that the model was generally able to produce behavioural simulations within the uncertainty limits of the streamflow. Reliability metrics ranged from 24.4% to 41.2% and captured the high-magnitude low-frequency sediment events. Since different sets of behavioural simulations were found across different parts of the catchment, evaluating LEM performance, in quantifying and assessing both at-a-point behaviour and spatial catchment response, remains a challenge. Our results show that evaluating LEMs within uncertainty analyses framework while taking into account the varying quality of different observations constrains behavioural simulations and parameter distributions and is a step towards a full-ensemble uncertainty evaluation of such models. We believe that this approach will have benefits for reflecting uncertainties in flooding events where channel morphological changes are occurring and various diverse (and yet often sparse) data have been collected over such events.     

Long-term observations of the group structure of surface waves in ice

Ocean Dynamics - Several years of surface wave observations in the Chukchi Sea reveal wave groups are a common feature in open water and ice-covered conditions. The strength of the groupiness, here...