scholarly journals Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

2014 ◽  
Vol 7 (4) ◽  
pp. 1641-1659 ◽  
Author(s):  
L. M. S. Paiva ◽  
G. C. R. Bodstein ◽  
L. C. G. Pimentel
Keyword(s):  
High Resolution ◽  
Observational Data ◽  
Atmospheric Circulation ◽  
Potential Temperature ◽  
European Space Agency ◽  
Parametric Models ◽  
Lateral Boundary Condition ◽  
Area Index ◽  
Regional Prediction ◽  
Local Atmospheric Circulation

Abstract. Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation-type data from the European Space Agency (ESA) GlobCover project, and 30 arc-sec leaf area index and fraction of absorbed photosynthetically active radiation data from the ESA GlobCarbon project. Simulations are carried out for the metropolitan area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering three periods of time are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, grid resolution, topographic and land-use databases. Our comparisons show overall good agreement between simulated and observational data, mainly for the potential temperature and the wind speed fields, and clearly indicate that the use of high-resolution databases improves significantly our ability to predict the local atmospheric circulation.

scholarly journals Influence of high-resolution surface databases on the modeling of local atmospheric circulation systems

2013 ◽  
Vol 6 (4) ◽  
pp. 6659-6715
Author(s):  
L. M. S. Paiva ◽  
G. C. R. Bodstein ◽  
L. C. G. Pimentel
Keyword(s):  
Atmospheric Circulation ◽  
Urban Areas ◽  
Initial Conditions ◽  
European Space Agency ◽  
Parametric Models ◽  
Lateral Boundary Condition ◽  
United States Geological Survey ◽  
Area Index ◽  
Regional Prediction ◽  
Local Atmospheric Circulation

Abstract. Large-eddy simulations are performed using the Advanced Regional Prediction System (ARPS) code at horizontal grid resolutions as fine as 300 m to assess the influence of detailed and updated surface databases on the modeling of local atmospheric circulation systems of urban areas with complex terrain. Applications to air pollution and wind energy are sought. These databases are comprised of 3 arc-sec topographic data from the Shuttle Radar Topography Mission, 10 arc-sec vegetation type data from the European Space Agency (ESA) GlobCover Project, and 30 arc-sec Leaf Area Index and Fraction of Absorbed Photosynthetically Active Radiation data from the ESA GlobCarbon Project. Simulations are carried out for the Metropolitan Area of Rio de Janeiro using six one-way nested-grid domains that allow the choice of distinct parametric models and vertical resolutions associated to each grid. ARPS is initialized using the Global Forecasting System with 0.5°-resolution data from the National Center of Environmental Prediction, which is also used every 3 h as lateral boundary condition. Topographic shading is turned on and two soil layers with depths of 0.01 and 1.0 m are used to compute the soil temperature and moisture budgets in all runs. Results for two simulated runs covering the period from 6 to 7 September 2007 are compared to surface and upper-air observational data to explore the dependence of the simulations on initial and boundary conditions, topographic and land-use databases and grid resolution. Our comparisons show overall good agreement between simulated and observed data and also indicate that the low resolution of the 30 arc-sec soil database from United States Geological Survey, the soil moisture and skin temperature initial conditions assimilated from the GFS analyses and the synoptic forcing on the lateral boundaries of the finer grids may affect an adequate spatial description of the meteorological variables.

scholarly journals Wheat Leaf Area Index Prediction Using Data Fusion Based on High-Resolution Unmanned Aerial Vehicle Imagery

2021 ◽  
Author(s):  
Shuang Wu ◽  
Lei Deng ◽  
Lijie Guo ◽  
Yanjie Wu
Keyword(s):  
High Resolution ◽  
Data Fusion ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Unmanned Aerial Vehicle ◽  
Prediction Accuracy ◽  
Sensor Data ◽  
Support Vector ◽  
Area Index ◽  
Aerial Vehicle

Abstract Background: Leaf Area Index (LAI) is half of the amount of leaf area per unit horizontal ground surface area. Consequently, accurate vegetation extraction in remote sensing imagery is critical for LAI estimation. However, most studies do not fully exploit the advantages of Unmanned Aerial Vehicle (UAV) imagery with high spatial resolution, such as not removing the background (soil and shadow, etc.). Furthermore, the advancement of multi-sensor synchronous observation and integration technology allows for the simultaneous collection of canopy spectral, structural, and thermal data, making it possible for data fusion.Methods: To investigate the potential of high-resolution UAV imagery combined with multi-sensor data fusion in LAI estimation. High-resolution UAV imagery was obtained with a multi-sensor integrated MicaSense Altum camera to extract the wheat canopy's spectral, structural, and thermal features. After removing the soil background, all features were fused, and LAI was estimated using Random Forest and Support Vector Machine Regression.Result: The results show that: (1) the soil background reduced the accuracy of the LAI prediction, and soil background could be effectively removed by taking advantage of high-resolution UAV imagery. After removing the soil background, the LAI prediction accuracy improved significantly, R2 raised by about 0.27, and RMSE fell by about 0.476. (2) The fusion of multi-sensor synchronous observation data improved LAI prediction accuracy and achieved the best accuracy (R2 = 0.815 and RMSE = 1.023). (3) When compared to other variables, 23 CHM, NRCT, NDRE, and BLUE are crucial for LAI estimation. Even the simple Multiple Linear Regression model could achieve high prediction accuracy (R2 = 0.679 and RMSE = 1.231), providing inspiration for rapid and efficient LAI prediction.Conclusions: The method of this study can be transferred to other sites with more extensive areas or similar agriculture structures, which will facilitate agricultural production and management.

MACRO-GOM: Long Term Multi-Resolution Ocean Current Reanalysis Dataset for the Gulf of Mexico

2021 ◽  
Author(s):  
Neha Groves ◽  
Ashwanth Srinivasan ◽  
Leonid Ivanov ◽  
Jill Storie ◽  
Drew Gustafson ◽  
...  
Keyword(s):  
High Resolution ◽  
Gulf Of Mexico ◽  
Observational Data ◽  
Hydrodynamic Model ◽  
Life Extension ◽  
Ocean Current ◽  
Reanalysis Dataset ◽  
Time Period ◽  
Offshore Industry

Abstract The Gulf of Mexico's unique circulation characteristics pose a particular threat to marine operations and play a significant role in driving the criteria used for design and life extension analyses of offshore infrastructure. Estimates from existing reanalysis datasets used by operators in GOM show less than ideal correlation with in situ measurements and have a limited resolution that disallows for the capture of ocean features of interest. In this paper, we introduce a new high-resolution long-term reanalysis dataset, Multi-resolution Advanced Current Reanalysis for the Ocean – Gulf of Mexico (MACRO-GOM), based on a state-of the-science hydrodynamic model configured specifically for ocean current forecasting and hindcasting services for the offshore industry that assimilates extensive non-conventional observational data. The underlying hydrodynamic model used is the Woods Hole Group – Tendral Ocean Prediction System (WHG-TOPS). MACRO-GOM is being developed at the native resolution of the TOPS-GOM domain, i.e. 1/32° (~3 km) hourly grid for the 1994-2019 time period (25 years). A 3-level downscaling methodology is used wherein observation based estimates are first dynamically interpolated using a 1/4° model before being downscaled to the 1/16° Inter-American Seas (IAS) domain, which in turn is used to generate time-consistent boundary conditions for the 1/32° reanalysis. A multiscale data assimilation technique is used to constrain the model at synoptic and longer time scales. For this paper, a shorter, 5-year reanalysis run was conducted for the 2015-2019 time period for verification against assimilated and unassimilated observations, WHG's proprietary frontal analyses, and other reanalyses. Both the frontal analyses and Notice to Lesses (NTL) rig mounted ADCP data was withheld from assimilation for comparison. Offshore operations in the GOM can benefit from an improved reanalysis dataset capable of assimilating existing non-conventional observational datasets. Existing hindcast and reanalysis model datasets are limited in their ability to comprehensively and reliably quantify the 3D circulation and kinematic properties of the main features partly because of limited assimilation of observational data. MACRO-GOM incorporates all the advantages of available HYCOM-based reanalyses and further enhances the resolution, accuracy, and reliability by the assimilation of over three decades of WHG's proprietary datasets and frontal analyses for continuous model correction and ground-truthing. The final 25-year high resolution dataset will provide highly reliable design and operational criteria for new and existing infrastructure in GOM.

scholarly journals Peatland leaf-area index and biomass estimation with ultra-high resolution remote sensing

2020 ◽  
Vol 57 (7) ◽  
pp. 943-964
Author(s):  
Aleksi Räsänen ◽  
Sari Juutinen ◽  
Margaret Kalacska ◽  
Mika Aurela ◽  
Pauli Heikkinen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Biomass Estimation ◽  
Area Index

scholarly journals Climatology of Cloud Vertical Structures from Long-Term High-Resolution Radiosonde Measurements in Beijing

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 401
Author(s):  
Qing Zhou ◽  
Yong Zhang ◽  
Shuze Jia ◽  
Junli Jin ◽  
Shanshan Lv ◽  
...  
Keyword(s):  
High Resolution ◽  
Atmospheric Circulation ◽  
Frequency Distribution ◽  
Hydrological Cycle ◽  
Global Radiation ◽  
Circulation Model ◽  
Middle Level ◽  
Radiation Budget ◽  
Cloud Base

Clouds are significant in the global radiation budget, atmospheric circulation, and hydrological cycle. However, knowledge regarding the observed climatology of the cloud vertical structure (CVS) over Beijing is still poor. Based on high-resolution radiosonde observations at Beijing Nanjiao Weather Observatory (BNWO) during the period 2010–2017, the method for identifying CVS depending on height-resolved relative humidity thresholds is improved, and CVS estimation by radiosonde is compared with observations by millimeter-wave cloud radar and ceilometer at the same site. Good consistency is shown between the three instruments. Then, the CVS climatology, including the frequency distribution and seasonal variation, is investigated. Overall, the occurrence frequency (OF) of cloudy cases in Beijing is slightly higher than that of clear-sky cases, and the cloud OF is highest in summer and lowest in winter. Single-layer clouds and middle-level clouds are dominant in Beijing. In addition, the average cloud top height (CTH), cloud base height (CBH), and cloud thickness in Beijing are 6.2 km, 4.0 km, and 2.2 km, respectively, and show the trend of reaching peaks in spring and minimums in winter. In terms of frequency distribution, the CTH basically resides below an altitude of 16 km, and approximately 43% of the CBHs are located at altitudes of 0.5–1.5 km. The cloud OF has only one peak located at altitudes of 4–8 km in spring, whereas it shows a trimodal distribution in other seasons. The height at which the cloud OF reaches its peak is highest in summer and lowest in winter. To the best of our knowledge, the cloud properties analyzed here are the first to elucidate the distribution and temporal variation of the CVS in Beijing from a long-term sounding perspective, and these results will provide a scientific observation basis for improving the atmospheric circulation model, as well as comparisons and verifications for measurements by ground-based remote sensing equipment.

scholarly journals High-resolution mapping of the NO<sub>2</sub> spatial distribution over Belgian urban areas based on airborne APEX remote sensing

2017 ◽  
Vol 10 (5) ◽  
pp. 1665-1688 ◽  
Author(s):  
Frederik Tack ◽  
Alexis Merlaud ◽  
Marian-Daniel Iordache ◽  
Thomas Danckaert ◽  
Huan Yu ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Urban Areas ◽  
High Spatial Resolution ◽  
European Space Agency ◽  
Correlation Coefficients ◽  
Time Frame ◽  
Quantitative Information ◽  
Data Sets ◽  
Vertical Column

Abstract. We present retrieval results of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs), mapped at high spatial resolution over three Belgian cities, based on the DOAS analysis of Airborne Prism EXperiment (APEX) observations. APEX, developed by a Swiss-Belgian consortium on behalf of ESA (European Space Agency), is a pushbroom hyperspectral imager characterised by a high spatial resolution and high spectral performance. APEX data have been acquired under clear-sky conditions over the two largest and most heavily polluted Belgian cities, i.e. Antwerp and Brussels on 15 April and 30 June 2015. Additionally, a number of background sites have been covered for the reference spectra. The APEX instrument was mounted in a Dornier DO-228 aeroplane, operated by Deutsches Zentrum für Luft- und Raumfahrt (DLR). NO2 VCDs were retrieved from spatially aggregated radiance spectra allowing urban plumes to be resolved at the resolution of 60  ×  80 m2. The main sources in the Antwerp area appear to be related to the (petro)chemical industry while traffic-related emissions dominate in Brussels. The NO2 levels observed in Antwerp range between 3 and 35  ×  1015 molec cm−2, with a mean VCD of 17.4 ± 3.7  ×  1015 molec cm−2. In the Brussels area, smaller levels are found, ranging between 1 and 20  ×  1015 molec cm−2 and a mean VCD of 7.7 ± 2.1  ×  1015 molec cm−2. The overall errors on the retrieved NO2 VCDs are on average 21 and 28 % for the Antwerp and Brussels data sets. Low VCD retrievals are mainly limited by noise (1σ slant error), while high retrievals are mainly limited by systematic errors. Compared to coincident car mobile-DOAS measurements taken in Antwerp and Brussels, both data sets are in good agreement with correlation coefficients around 0.85 and slopes close to unity. APEX retrievals tend to be, on average, 12 and 6 % higher for Antwerp and Brussels, respectively. Results demonstrate that the NO2 distribution in an urban environment, and its fine-scale variability, can be mapped accurately with high spatial resolution and in a relatively short time frame, and the contributing emission sources can be resolved. High-resolution quantitative information about the atmospheric NO2 horizontal variability is currently rare, but can be very valuable for (air quality) studies at the urban scale.

scholarly journals Solar system tests of a new class of f(z) theory

2020 ◽  
Vol 29 (08) ◽  
pp. 2050060
Author(s):  
Ji-Yao Wang ◽  
Chao-Jun Feng ◽  
Xiang-Hua Zhai ◽  
Xin-Zhou Li
Keyword(s):  
Solar System ◽  
Observational Data ◽  
Ricci Scalar ◽  
Parametric Models ◽  
Alternative Models ◽  
New Class ◽  
Cosmological Data ◽  
Ppn Parameters ◽  
Models Of Gravity

Recently, a new kind of [Formula: see text] theory is proposed to provide a different perspective for the development of reliable alternative models of gravity in which the [Formula: see text] Lagrangian terms are reformulated as polynomial parametrizations [Formula: see text]. In the previous study, the parameters in the [Formula: see text] models have been constrained by using cosmological data. In this paper, these models will be tested by the observations in the solar system. After solving the Ricci scalar as a function of the redshift, one could obtain [Formula: see text] that could be used to calculate the standard Parametrized-Post-Newtonian (PPN) parameters. First, we fit the parametric models with the latest cosmological observational data. Then, the tests are performed by solar system observations. And last we combine the constraints of solar system and cosmology together and reconstruct the [Formula: see text] actions of the [Formula: see text] parametric models.

scholarly journals Interferometric Observations of Mira Variables

2003 ◽  
Vol 210 ◽  
pp. 367-376
Author(s):  
G. Van Belle ◽  
R. R. Thompson ◽  
M.J. Creech-Eakman
Keyword(s):  
High Resolution ◽  
Observational Data ◽  
Atmospheric Chemistry ◽  
Spherical Symmetry ◽  
Atmospheric Dynamics ◽  
Pulsating Stars ◽  
Mira Variables ◽  
Cool Stars ◽  
Phase Lags ◽  
New Generation

Milliarcsecond resolution observations of cool stars are becoming increasingly common and sophisticated as recent advances in telescope technology mature. To varying degrees, these observations rely up on stellar models for interpretation of their data, while at the same time present particular challenges to those models. Indications of departures from spherical symmetry are beginning to be observed as increasingly rich image information is obtained by a new generation of interferometers. Examination the subtle variations of wavelength-specific sizes exhibits rich structure, connected to the atmospheric chemistry. For the pulsating stars, such as Mira variables, that structure varies with time, with the phase lags between the various sizes being connected to the atmospheric dynamics. Complex morphologies associated with atmospheric winds have been revealed with these high resolution experiments. A review of these recent results will be presented, concentrated on their implications upon stellar modelling, and the prospects for future observational data.

scholarly journals Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration

2014 ◽  
Vol 18 (12) ◽  
pp. 5219-5237 ◽  
Author(s):  
S. Ferrant ◽  
S. Gascoin ◽  
A. Veloso ◽  
J. Salmon-Monviola ◽  
M. Claverie ◽  
...  
Keyword(s):  
High Resolution ◽  
Hydrological Model ◽  
A Priori ◽  
Agricultural Practices ◽  
Crop Growth ◽  
Data Set ◽  
Area Index ◽  
Field Level ◽  
Seeding Date ◽  
Crop Field

Abstract. The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006–2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985–2001, was tested on the 2005–2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr−1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution products from the Sentinel-2 satellite mission for improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

Sign in / Sign up

Export Citation Format

Share Document