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Satellite Measurements (satellite + measurement)

Distribution by Scientific Domains

Earth and Environmental Science	60%

Selected Abstracts

Spatio-temporal statistical modelling of significant wave height

ENVIRONMETRICS, Issue 1 2009
A. Baxevani
Abstract In this paper, we construct a homogeneous spatio-temporal model to describe the variability of significant wave height over small regions of the sea and over short periods of time. Then, the model is extended to a non-homogeneous one that is valid over larger areas of the sea and for time periods of up to 10 h. To validate the proposed model, we reconstruct the significant wave height surface under different scenarios and then compare it to satellite measurements and the C-ERA-40 field. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Iterative generalized cross-validation for fusing heteroscedastic data of inverse ill-posed problems

GEOPHYSICAL JOURNAL INTERNATIONAL, Issue 1 2009
Peiliang Xu
SUMMARY The method of generalized cross-validation (GCV) has been widely used to determine the regularization parameter, because the criterion minimizes the average predicted residuals of measured data and depends solely on data. The data-driven advantage is valid only if the variance,covariance matrix of the data can be represented as the product of a given positive definite matrix and a scalar unknown noise variance. In practice, important geophysical inverse ill-posed problems have often been solved by combining different types of data. The stochastic model of measurements in this case contains a number of different unknown variance components. Although the weighting factors, or equivalently the variance components, have been shown to significantly affect joint inversion results of geophysical ill-posed problems, they have been either assumed to be known or empirically chosen. No solid statistical foundation is available yet to correctly determine the weighting factors of different types of data in joint geophysical inversion. We extend the GCV method to accommodate both the regularization parameter and the variance components. The extended version of GCV essentially consists of two steps, one to estimate the variance components by fixing the regularization parameter and the other to determine the regularization parameter by using the GCV method and by fixing the variance components. We simulate two examples: a purely mathematical integral equation of the first kind modified from the first example of Phillips (1962) and a typical geophysical example of downward continuation to recover the gravity anomalies on the surface of the Earth from satellite measurements. Based on the two simulated examples, we extensively compare the iterative GCV method with existing methods, which have shown that the method works well to correctly recover the unknown variance components and determine the regularization parameter. In other words, our method lets data speak for themselves, decide the correct weighting factors of different types of geophysical data, and determine the regularization parameter. In addition, we derive an unbiased estimator of the noise variance by correcting the biases of the regularized residuals. A simplified formula to save the time of computation is also given. The two new estimators of the noise variance are compared with six existing methods through numerical simulations. The simulation results have shown that the two new estimators perform as well as Wahba's estimator for highly ill-posed problems and outperform any existing methods for moderately ill-posed problems. [source]

Net primary productivity mapped for Canada at 1-km resolution

GLOBAL ECOLOGY, Issue 2 2002
J Liu
Abstract Aim To map net primary productivity (NPP) over the Canadian landmass at 1-km resolution. Location Canada. Methods A simulation model, the Boreal Ecosystem Productivity Simulator (BEPS), has been developed. The model uses a sunlit and shaded leaf separation strategy and a daily integration scheme in order to implement an instantaneous leaf-level photosynthesis model over large areas. Two key driving variables, leaf area index (every 10 days) and land cover type (annual), are derived from satellite measurements of the Advanced Very High Resolution Radiometer (AVHRR). Other spatially explicit input data are also prepared, including daily meteorological data (radiation, precipitation, temperature, and humidity), available soil water holding capacity (AWC) and forest biomass. The model outputs are compared with ground plot data to ensure that no significant systematic biases are created. Results The simulation results show that Canada's annual net primary production was 1.22 Gt C year,1 in 1994, 78% attributed to forests, mainly the boreal forest, without considering the contribution of the understorey. The NPP averaged over the entire landmass was ~140 g C m,2 year,1 in 1994. Geographically, NPP varied greatly among ecozones and provinces/territories. The seasonality of NPP is characterized by strong summer photosynthesis capacities and a short growing season in northern ecosystems. Conclusions This study is the first attempt to simulate Canada-wide NPP with a process-based model at 1-km resolution and using a daily step. The statistics of NPP are therefore expected to be more accurate than previous analyses at coarser spatial or temporal resolutions. The use of remote sensing data makes such simulations possible. BEPS is capable of integrating the effects of climate, vegetation, and soil on plant growth at a regional scale. BEPS and its parameterization scheme and products can be a basis for future studies of the carbon cycle in mid-high latitude ecosystems. [source]

Assimilation of SEVIRI infrared radiances with HIRLAM 4D-Var

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 645 2009
M. Stengel
Abstract Four-dimensional variational data assimilation (4D-Var) systems are ideally suited to obtain the best possible initial model state by utilizing information about the dynamical evolution of the atmospheric state from observations, such as satellite measurements, distributed over a certain period of time. In recent years, 4D-Var systems have been developed for several global and limited-area models. At the same time, spatially and temporally highly resolved satellite observations, as for example performed by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board the Meteosat Second Generation satellites, have become available. Here we demonstrate the benefit of a regional NWP model's analyses and forecasts gained by the assimilation of those radiances. The 4D-Var system of the HIgh Resolution Limited Area Model (HIRLAM) has been adjusted to utilize three of SEVIRI's infrared channels (located around 6.2 µm, 7.3 µm, and 13.4 µm, respectively) under clear-sky and low-level cloud conditions. Extended assimilation and forecast experiments show that the main direct impact of assimilated SEVIRI radiances on the atmospheric analysis were additional tropospheric humidity and wind increments. Forecast verification reveals a positive impact for almost all upper-air variables throughout the troposphere. Largest improvements are found for humidity and geopotential height in the middle troposphere. The observations in regions of low-level clouds provide especially beneficial information to the NWP system, which highlights the importance of satellite observations in cloudy areas for further improvements in the accuracy of weather forecasts. Copyright © 2009 Royal Meteorological Society [source]

The impact of urban areas on weather

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 614 2006
C. G. Collier
Abstract The industrial revolution led to a rapid development of urban areas. This has continued unremittingly over the last 200 years or so. In most urban areas the surface properties are heterogeneous, which has significant implications for energy budgets, water budgets and weather phenomena within the part of the earth's atmosphere that humans live. In this paper I discuss the structure of the planetary boundary layer, confining our analysis to the region above the rooftops (canopy layer) up to around the level where clouds form. It is in this part of the atmosphere that most of the weather impacting our lives occurs, and where the buildings of our cities impact the weather. In this review, observations of the structure of the urban atmospheric boundary layer are discussed. In particular the use of Doppler lidar provides measurements above the canopy layer. The impact of high-rise buildings is considered. Urban morphology impacts energy fluxes and airflow leading to phenomena such as the urban heat island and convective rainfall initiation. I discuss in situ surface-based remote sensing and satellite measurements of these effects. Measurements have been used with simple and complex numerical models to understand the complexity and balance of the interactions involved. Cities have been found to be sometimes up to 10 degC warmer than the surrounding rural areas, and to cause large increases in rainfall amounts. However, there are situations in which urban aerosol may suppress precipitation. Although much progress has been made in understanding these impacts, our knowledge remains incomplete. These limitations are identified. As city living becomes even more the norm for large numbers of people, it is imperative that we ensure that urban effects on the weather are included in development plans for the built environment of the future. Copyright © 2006 Royal Meteorological Society [source]