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991.
992.
Today, many real‐time geospatial applications (e.g. navigation and location‐based services) involve data‐ and/or compute‐intensive geoprocessing tasks where performance is of great importance. Cloud computing, a promising platform with a large pool of storage and computing resources, could be a practical solution for hosting vast amounts of data and for real‐time processing. In this article, we explored the feasibility of using Google App Engine (GAE), the cloud computing technology by Google, for a module in navigation services, called Integrated GNSS (iGNSS) QoS prediction. The objective of this module is to predict quality of iGNSS positioning solutions for prospective routes in advance. iGNSS QoS prediction involves the real‐time computation of large Triangulated Irregular Networks (TINs) generated from LiDAR data. We experimented with the Google App Engine (GAE) and stored a large TIN for two geoprocessing operations (proximity and bounding box) required for iGNSS QoS prediction. The experimental results revealed that while cloud computing can potentially be used for development and deployment of data‐ and/or compute‐intensive geospatial applications, current cloud platforms require improvements and special tools for handling real‐time geoprocessing, such as iGNSS QoS prediction, efficiently. The article also provides a set of general guidelines for future development of real‐time geoprocessing in clouds. 相似文献
993.
Yunjun Yao Shunlin Liang Qiming Qin Kaicun Wang Shaohua Zhao 《International Journal of Applied Earth Observation and Geoinformation》2011
The latent heat of evapotranspiration (ET) plays an important role in the assessment of drought severity as one sensitive indicator of land drought status. A simple and accurate method of estimating global ET for the monitoring of global land surface droughts from remote sensing data is essential. The objective of this research is to develop a hybrid ET model by introducing empirical coefficients based on a simple linear two-source land ET model, and to then use this model to calculate the Evaporative Drought Index (EDI) based on the actual estimated ET and the potential ET in order to characterize global surface drought conditions. This is done using the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) products, AVHRR-NDVI products from the Global Inventory Modeling and Mapping Studies (GIMMS) group, and National Centers for Environmental Prediction Reanalysis-2 (NCEP-2) datasets. We randomly divided 22 flux towers into two groups and performed a series of cross-validations using ground measurements collected from the corresponding flux towers. The validation results from the second group of flux towers using the data from the first group for calibration show that the daily bias varies from −6.72 W/m2 to 12.95 W/m2 and the average monthly bias is −1.73 W/m2. Similarly, the validation results of the first group of flux towers using data from second group for calibration show that the daily bias varies from −12.91 W/m2 to 10.26 W/m2 and the average monthly bias is −3.59 W/m2. To evaluate the reliability of the hybrid ET model on a global scale, we compared the estimated ET from the GEWEX, AVHRR-GIMMS-NDVI, and NECP-2 datasets with the latent heat flux from the Global Soil Wetness Project-2 (GSWP-2) datasets. We found both of them to be in good agreement, which further supports the validity of our model's global ET estimation. Significantly, the patterns of monthly EDI anomalies have a good spatial and temporal correlation with the Palmer Drought Severity Index (PDSI) anomalies from January 1984 to December 2002, which indicates that the method can be used to accurately monitor long-term global land surface drought. 相似文献
994.
Aircraft turbulence data from the Autonomous Ocean Sampling Network project were analyzed and compared to the Coupled Ocean–Atmosphere
Response Experiment (COARE) bulk parametrization of turbulent fluxes in an ocean area near the coast of California characterized
by complex atmospheric flow. Turbulent fluxes measured at about 35 m above the sea surface using the eddy-correlation method
were lower than bulk estimates under unstable and stable atmospheric stratification for all but light winds. Neutral turbulent
transfer coefficients were used in this comparison because they remove the effects of mean atmospheric conditions and atmospheric
stability. Spectral analysis suggested that kilometre-scale longitudinal rolls affect significantly turbulence measurements
even near the sea surface, depending on sampling direction. Cross-wind sampling tended to capture all the available turbulent
energy. Vertical soundings showed low boundary-layer depths and high flux divergence near the sea surface in the case of sensible
heat flux but minimal flux divergence for the momentum flux. Cross-wind sampling and flux divergence were found to explain
most of the observed discrepancies between the measured and bulk flux estimates. At low wind speeds the drag coefficient determined
with eddy correlation and an inertial dissipation method after corrections were applied still showed high values compared
to bulk estimates. This discrepancy correlated with the dominance of sea swell, which was a usually observed condition under
low wind speeds. Under stable atmospheric conditions measured sensible heat fluxes, which usually have low values over the
ocean, were possibly affected by measurement errors and deviated significantly from bulk estimates. 相似文献
995.
A Spatially-Analytical Scheme for Surface Temperatures and Conductive Heat Fluxes in Urban Canopy Models 总被引:1,自引:0,他引:1
In the urban environment, surface temperatures and conductive heat fluxes through solid media (roofs, walls, roads and vegetated
surfaces) are of paramount importance for the comfort of residents (indoors) and for microclimatic conditions (outdoors).
Fully discrete numerical methods are currently used to model heat transfer in these solid media in parametrisations of built
surfaces commonly used in weather prediction models. These discrete methods usually use finite difference schemes in both
space and time. We propose a spatially-analytical scheme where the temperature field and conductive heat fluxes are solved
analytically in space. Spurious numerical oscillations due to temperature discontinuities at the sublayer interfaces can be
avoided since the method does not involve spatial discretisation. The proposed method is compared to the fully discrete method
for a test case of one-dimensional heat conduction with sinusoidal forcing. Subsequently, the analytical scheme is incorporated
into the offline version of the current urban canopy model (UCM) used in the Weather Research and Forecasting model and the
new UCM is validated against field measurements using a wireless sensor network and other supporting measurements over a suburban
area under real-world conditions. Results of the comparison clearly show the advantage of the proposed scheme over the fully
discrete model, particularly for more complicated cases. 相似文献
996.
June-Yi Lee Bin Wang Q. Ding K.-J. Ha J.-B. Ahn A. Kumar B. Stern O. Alves 《Climate Dynamics》2011,37(5-6):1189-1203
The retrospective forecast skill of three coupled climate models (NCEP CFS, GFDL CM2.1, and CAWCR POAMA 1.5) and their multi-model ensemble (MME) is evaluated, focusing on the Northern Hemisphere (NH) summer upper-tropospheric circulation along with surface temperature and precipitation for the 25-year period of 1981–2005. The seasonal prediction skill for the NH 200-hPa geopotential height basically comes from the coupled models’ ability in predicting the first two empirical orthogonal function (EOF) modes of interannual variability, because the models cannot replicate the residual higher modes. The first two leading EOF modes of the summer 200-hPa circulation account for about 84% (35.4%) of the total variability over the NH tropics (extratropics) and offer a hint of realizable potential predictability. The MME is able to predict both spatial and temporal characteristics of the first EOF mode (EOF1) even at a 5-month lead (January initial condition) with a pattern correlation coefficient (PCC) skill of 0.96 and a temporal correlation coefficient (TCC) skill of 0.62. This long-lead predictability of the EOF1 comes mainly from the prolonged impacts of El Niño-Southern Oscillation (ENSO) as the EOF1 tends to occur during the summer after the mature phase of ENSO. The second EOF mode (EOF2), on the other hand, is related to the developing ENSO and also the interdecadal variability of the sea surface temperature over the North Pacific and North Atlantic Ocean. The MME also captures the EOF2 at a 5-month lead with a PCC skill of 0.87 and a TCC skill of 0.67, but these skills are mainly obtained from the zonally symmetric component of the EOF2, not the prominent wavelike structure, the so-called circumglobal teleconnection (CGT) pattern. In both observation and the 1-month lead MME prediction, the first two leading modes are accompanied by significant rainfall and surface air temperature anomalies in the continental regions of the NH extratropics. The MME’s success in predicting the EOF1 (EOF2) is likely to lead to a better prediction of JJA precipitation anomalies over East Asia and the North Pacific (central and southern Europe and western North America). 相似文献
997.
Lin-Lin Pan Shu-Hua Chen Dan Cayan Mei-Ying Lin Quinn Hart Ming-Hua Zhang Yubao Liu Jianzhong Wang 《Climate Dynamics》2011,37(9-10):2005-2020
In this study, the influence of climate change to California and Nevada regions was investigated through high-resolution (4-km grid spacing) dynamical downscaling using the WRF (Weather Research & Forecasting) model. The dynamical downscaling was performed to both the GFS (Global forecast model) reanalysis (called GFS-WRF runs) from 2000?C2006 and PCM (Parallel Climate Model) simulations (called PCM-WRF runs) from 1997?C2006 and 2047?C2056. The downscaling results were first validated by comparing current model outputs with the observational analysis PRISM (Parameter-elevation Regressions on Independent Slopes Model) dataset. In general, the dominant features from GFS-WRF runs and PCM-WRF runs were consistent with each other, as well as with PRISM results. The influences of climate change on the California and Nevada regions can be inferred from the model future runs. The averaged temperature showed a positive trend in the future, as in other studies. The temperature increases by around 1?C2°C under the assumption of business as usual over 50?years. This leads to an upward shifting of the freezing level (the contour line of 0°C temperature) and more rain instead of snow in winter (December, January, and February). More hot days (>32.2°C or 90°F) and extreme hot days (>37.8°C or 100°F) are predicted in the Sacramento Valley and the southern parts of California and Nevada during summer (June, July, and August). More precipitation is predicted in northern California but not in southern California. Rainfall frequency slightly increases in the coast regions, but not in the inland area. No obvious trend of the surface wind was indicated. The probability distribution functions (PDF) of daily temperature, wind and precipitation for California and Nevada showed no significant change in shape in either winter or summer. The spatial distributions of precipitation frequency from GFS-WRF and PCM-WRF were highly correlated (r?=?0.83). However, overall positive shifts were seen in the temperature field; increases of 2°C for California and 3°C for Nevada in summer and 2.5°C for California and 1.5°C for Nevada in winter. The PDFs predicted higher precipitation in winter and lower precipitation in the summer for both California and Nevada. 相似文献
998.
Li Shi Harry H. Hendon Oscar Alves Matthew C. Wheeler David Anderson Guomin Wang 《Climate Dynamics》2011,37(1-2):313-324
The importance of initializing atmospheric intra-seasonal (stochastic) variations for prediction of the onset of the 1997/1998 El Ni?o is examined using the Australian Bureau of Meteorology coupled seasonal forecast model. A suite of 9-month forecasts was initialized on the 1st December 1996. Observed ocean initial conditions were used together with five different atmospheric initial conditions that sample a range of possible initial states of intra-seasonal (stochastic) variability, especially the Madden-Julian Oscillation (MJO), which is considered the primary stochastic variability of relevance to El Ni?o evolution. The atmospheric initial states were generated from a suite of atmosphere-only integrations forced by observed sea surface temperatures (SST). To the extent that low frequency variability of the tropical atmosphere is forced by slow variations in SST, these atmospheric states should all represent realistic low frequency atmospheric variability that was present in December 1996. However, to the extent that intra-seasonal variability is not constrained by SST, they should capture a range of intra-seasonal states, especially variations in the activity, phase and amplitude of the MJO. For each of these five states, a 20-member ensemble of coupled model forecasts was generated by the addition of small random perturbations to the SST field at the initial time. The ensemble mean from all five sets of forecasts resulted in El Ni?o but three of the sets produced substantially greater warming by months 4?C5 in the NINO3.4 region compared to the other two. The warmer group stemmed from stronger intra-seasonal westerly wind anomalies associated with the MJO that propagated eastward into the central Pacific during the first 1?C2?months of the forecast. These were largely absent in the colder group; the weakest of the colder group developed strong easterly wind anomalies, relative to the grand ensemble mean, that propagated into the central Pacific early in the forecast, thereby generating significantly weaker downwelling Kelvin waves in comparison to the warmer group. The strong reduction in downwelling Kelvin waves in the weakest case acted to limit the warming in the eastern Pacific, resulting in a ??Modoki?? type El Ni?o that is more focused in the central Pacific. Our results suggest that the intra-seasonal stochastic component of the atmospheric initial condition has an important and potentially predictable impact on the forecasts of the initial warming and flavour of the 1997/1998 El Ni?o. However, to the extent that atmospheric intra-seasonal variability is not predictable beyond a month or two, these results imply a limit to the accuracy with which the strength and perhaps the spatial distribution of an El Ni?o can ultimately be predicted. These results do not preclude a predictable role of the MJO and other intra-seasonal stochastic variability at longer lead times if some aspects of the stochastic variability are preconditioned by the evolving state of El Ni?o or other low frequency boundary forcing. 相似文献
999.
Wanqiu Wang Pingping Xie Soo-Hyun Yoo Yan Xue Arun Kumar Xingren Wu 《Climate Dynamics》2011,37(7-8):1601-1620
This paper analyzes surface climate variability in the climate forecast system reanalysis (CFSR) recently completed at the National Centers for Environmental Prediction (NCEP). The CFSR represents a new generation of reanalysis effort with first guess from a coupled atmosphere?Cocean?Csea ice?Cland forecast system. This study focuses on the analysis of climate variability for a set of surface variables including precipitation, surface air 2-m temperature (T2m), and surface heat fluxes. None of these quantities are assimilated directly and thus an assessment of their variability provides an independent measure of the accuracy. The CFSR is compared with observational estimates and three previous reanalyses (the NCEP/NCAR reanalysis or R1, the NCEP/DOE reanalysis or R2, and the ERA40 produced by the European Centre for Medium-Range Weather Forecasts). The CFSR has improved time-mean precipitation distribution over various regions compared to the three previous reanalyses, leading to a better representation of freshwater flux (evaporation minus precipitation). For interannual variability, the CFSR shows improved precipitation correlation with observations over the Indian Ocean, Maritime Continent, and western Pacific. The T2m of the CFSR is superior to R1 and R2 with more realistic interannual variability and long-term trend. On the other hand, the CFSR overestimates downward solar radiation flux over the tropical Western Hemisphere warm pool, consistent with a negative cloudiness bias and a positive sea surface temperature bias. Meanwhile, the evaporative latent heat flux in CFSR appears to be larger than other observational estimates over most of the globe. A few deficiencies in the long-term variations are identified in the CFSR. Firstly, dramatic changes are found around 1998?C2001 in the global average of a number of variables, possibly related to the changes in the assimilated satellite observations. Secondly, the use of multiple streams for the CFSR induces spurious jumps in soil moisture between adjacent streams. Thirdly, there is an inconsistency in long-term sea ice extent variations over the Arctic regions between the CFSR and other observations with the CFSR showing smaller sea ice extent before 1997 and larger extent starting in 1997. These deficiencies may have impacts on the application of the CFSR for climate diagnoses and predictions. Relationships between surface heat fluxes and SST tendency and between SST and precipitation are analyzed and compared with observational estimates and other reanalyses. Global mean fields of surface heat and water fluxes together with radiation fluxes at the top of the atmosphere are documented and presented over the entire globe, and for the ocean and land separately. 相似文献
1000.
Diagnostic metrics for evaluation of annual and diurnal cycles 总被引:1,自引:0,他引:1
Two sets of diagnostic metrics are proposed for evaluation of global models?? simulation of annual and diurnal cycles of precipitation. The metrics for the annual variation include the annual mean, the solstice and equinoctial asymmetric modes of the annual cycle (AC), and the global monsoon precipitation domain and intensity. The metrics for the diurnal variation include the diurnal range, the land?Csea contrast and transition modes of the diurnal cycle (DC), and the diurnal peak propagation in coastal regions. The proposed modes for the AC and DC represent faithfully the first two leading empirical orthogonal functions and explain, respectively, 82% of the total annual variance and 87% of the total diurnal variance over the globe between 45°S and 45°N. The simulated AC and DC by the 20-km-mesh MRI/JMA atmospheric general circulation model (AGCM) are in a wide-ranging agreement with observations; the model considerably outperforms any individual AMIP II GCMs and has comparable performance to 12-AMIP II model ensemble simulation measured by Pearson??s pattern correlation coefficient. Comparison of four versions of the MRI/JMA AGCM with increasing resolution (180, 120, 60, and 20?km) reveals that the 20-km version reproduces the most realistic annual and diurnal cycles. However, the improved performance is not a linear function of the resolution. Marked improvement of the simulated DC (AC) occurs at the resolution of 60?km (20?km). The results suggest that better represented parameterizations that are adequately tuned to increased resolutions may improve models?? simulation on the forced responses. The common deficiency in representing the monsoon domains suggests the models having difficulty in replicating annual march of the Subtropical Highs that is largely driven by prominent east-west land?Cocean thermal contrast. Note that the 20-km model reproduces realistic diurnal cycle, but fails to capture realistic Madden-Julian Oscillation. 相似文献