The Potential of Satellite Sounding Observations for Deriving Atmospheric Wind in All-Weather Conditions

Atmospheric wind is an essential parameter in the global observing system. In this study, the water vapor field in Typhoon Lekima and its surrounding areas simulated by the Weather Research and Forecasting (WRF) model is utilized to track the atmospheric motion wind through the Farneback Optical Flow (OF) algorithm. A series of experiments are conducted to investigate the influence of temporal and spatial resolutions on the errors of tracked winds. It is shown that the wind accuracy from tracking the specific humidity is higher than that from tracking the relative humidity. For fast-evolving weather systems such as typhoons, the shorter time step allows for more accurate wind retrievals, whereas for slow to moderate evolving weather conditions, the longer time step is needed for smaller retrieval errors. Compared to the traditional atmospheric motion vectors (AMVs) algorithm, the Farneback OF wind algorithm achieves a pixel-wise feature tracking and obtains a higher spatial resolution of wind field. It also works well under some special circumstances such as very low water vapor content or the region where the wind direction is parallel to the moisture gradient direction. This study has some significant implications for the configuration of satellite microwave sounding missions through their derived water vapor fields. The required temporal and spatial resolutions in the OF algorithm critically determine the satellite revisiting time and the field of view size. The brightness temperature (BT) simulated through Community Radiative Transfer Model (CRTM) is also used to track winds. It is shown that the error of tracking BT is generally larger than that of tracking water vapor. This increased error may result from the uncertainty in simulations of brightness temperatures at 183 GHz.

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A Satellite-Based Assessment of Upper-Tropospheric Water Vapor Measurements during AFWEX

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2250.1 ◽

2009 ◽

Vol 48 (11) ◽

pp. 2284-2294 ◽

Cited By ~ 5

Author(s):

Eui-Seok Chung ◽

Brian J. Soden

Keyword(s):

Water Vapor ◽

Radiative Transfer Model ◽

Transfer Model ◽

Raman Lidar ◽

Test Bed ◽

Upper Troposphere ◽

Brightness Temperatures ◽

Radiation Test ◽

Humidity Measurements ◽

Atmospheric Radiation Measurement

Abstract Consistency of upper-tropospheric water vapor measurements from a variety of state-of-the-art instruments was assessed using collocated Geostationary Operational Environmental Satellite-8 (GOES-8) 6.7-μm brightness temperatures as a common benchmark during the Atmospheric Radiation Measurement Program (ARM) First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX). To avoid uncertainties associated with the inversion of satellite-measured radiances into water vapor quantity, profiles of temperature and humidity observed from in situ, ground-based, and airborne instruments are inserted into a radiative transfer model to simulate the brightness temperature that the GOES-8 would have observed under those conditions (i.e., profile-to-radiance approach). Comparisons showed that Vaisala RS80-H radiosondes and Meteolabor Snow White chilled-mirror dewpoint hygrometers are systemically drier in the upper troposphere by ∼30%–40% relative to the GOES-8 measured upper-tropospheric humidity (UTH). By contrast, two ground-based Raman lidars (Cloud and Radiation Test Bed Raman lidar and scanning Raman lidar) and one airborne differential absorption lidar agree to within 10% of the GOES-8 measured UTH. These results indicate that upper-tropospheric water vapor can be monitored by these lidars and well-calibrated, stable geostationary satellites with an uncertainty of less than 10%, and that correction procedures are required to rectify the inherent deficiencies of humidity measurements in the upper troposphere from these radiosondes.

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WRF Model Experiments on the Antarctic Atmosphere in Winter

Monthly Weather Review ◽

10.1175/2010mwr3478.1 ◽

2011 ◽

Vol 139 (4) ◽

pp. 1279-1291 ◽

Cited By ~ 23

Author(s):

Esa-Matti Tastula ◽

Timo Vihma

Keyword(s):

Boundary Layer ◽

Surface Layer ◽

Wind Speed ◽

Surface Pressure ◽

Mesoscale Model ◽

Wrf Model ◽

Radiative Transfer Model ◽

Transfer Model ◽

Temperature Bias ◽

Radiation Parameterizations

Abstract The standard and polar versions 3.1.1 of the Weather Research and Forecasting (WRF) model, both initialized by the 40-yr ECMWF Re-Analysis (ERA-40), were run in Antarctica for July 1998. Four different boundary layer–surface layer–radiation scheme combinations were used in the standard WRF. The model results were validated against observations of the 2-m temperature, surface pressure, and 10-m wind speed at 9 coastal and 2 inland stations. The best choice for boundary layer and radiation parameterizations of the standard WRF turned out to be the Yonsei University boundary layer scheme in conjunction with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) surface layer scheme and the Rapid Radiative Transfer Model for longwave radiation. The respective temperature bias was on the order of 3°C less than the biases obtained with the other combinations. Increasing the minimum value for eddy diffusivity did, however, improve the performance of the asymmetric convective scheme by 0.8°C. Averaged over the 11 stations, the error growths in 24-h forecasts were almost identical for the standard and Polar WRF, but in 9-day forecasts Polar WRF gave a smaller 2-m temperature bias. For the Vostok station, however, the standard WRF gave a less positively biased 24-h temperature forecast. On average, the polar version gave the least biased surface pressure simulation. The wind speed simulation was characterized by low correlation values, especially under weak winds and for stations surrounded by complex topography.

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Performance of the line-by-line radiative transfer model (LBLRTM) for temperature and species retrievals: IASI case studies from JAIVEx

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-7397-2009 ◽

2009 ◽

Vol 9 (19) ◽

pp. 7397-7417 ◽

Cited By ~ 56

Author(s):

M. W. Shephard ◽

S. A. Clough ◽

V. H. Payne ◽

W. L. Smith ◽

S. Kireev ◽

...

Keyword(s):

Water Vapor ◽

Radiative Transfer ◽

Trace Gas ◽

Radiative Transfer Model ◽

Transfer Model ◽

Line Intensities ◽

Remote Sounding ◽

Instrument Noise ◽

Large Peak ◽

Line Coupling

Abstract. Presented here are comparisons between the Infrared Atmospheric Sounding instrument (IASI) and the "Line-By-Line Radiative Transfer Model" (LBLRTM). Spectral residuals from radiance closure studies during the IASI JAIVEx validation campaign provide insight into a number of spectroscopy issues relevant to remote sounding of temperature, water vapor and trace gases from IASI. In order to perform quality IASI trace gas retrievals, the temperature and water vapor fields must be retrieved as accurately as possible. In general, the residuals in the CO2 ν2 region are of the order of the IASI instrument noise. However, outstanding issues with the CO2 spectral regions remain. There is a large residual ~−1.7 K in the 667 cm−1 Q-branch, and residuals in the CO2 ν2 and N2O/CO2 ν3 spectral regions that sample the troposphere are inconsistent, with the N2O/CO2 ν3 region being too negative (warmer) by ~0.7 K. Residuals on this lower wavenumber side of the CO2 ν3 band will be improved by line parameter updates, while future efforts to reduce the residuals reaching ~−0.5 K on the higher wavenumber side of the CO2 ν3 band will focus on addressing limitations in the modeling of the CO2 line shape (line coupling and duration of collision) effects. Brightness temperature residuals from the radiance closure studies in the ν2 water vapor band have standard deviations of ~0.2–0.3 K with some large peak residuals reaching ±0.5–1.0 K. These are larger than the instrument noise indicating that systematic errors still remain. New H2O line intensities and positions have a significant impact on the retrieved water vapor, particularly in the upper troposphere where the water vapor retrievals are 10% drier when using line intensities compared with HITRAN 2004. In addition to O3, CH4, and CO, of the IASI instrument combined with an accurate forward model allows for the detection of minor species with weak atmospheric signatures in the nadir radiances, such as HNO3 and OCS.

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VIS-NIR, Red-Edge and NIR-Shoulder Based Normalized Vegetation Indices Response to Co-Varying Leaf and Canopy Structural Traits in Heterogeneous Grasslands

Remote Sensing ◽

10.3390/rs12142254 ◽

2020 ◽

Vol 12 (14) ◽

pp. 2254 ◽

Cited By ~ 1

Author(s):

Hafiz Ali Imran ◽

Damiano Gianelle ◽

Duccio Rocchini ◽

Michele Dalponte ◽

M. Pilar Martín ◽

...

Keyword(s):

Near Infrared ◽

Spatial Scales ◽

Vegetation Indices ◽

Radiative Transfer Model ◽

Transfer Model ◽

Sharp Change ◽

Full Potential ◽

Area Index ◽

Red Edge ◽

Temporal And Spatial

Red-edge (RE) spectral vegetation indices (SVIs)—combining bands on the sharp change region between near infrared (NIR) and visible (VIS) bands—alongside with SVIs solely based on NIR-shoulder bands (wavelengths 750–900 nm) have been shown to perform well in estimating leaf area index (LAI) from proximal and remote sensors. In this work, we used RE and NIR-shoulder SVIs to assess the full potential of bands provided by Sentinel-2 (S-2) and Sentinel-3 (S-3) sensors at both temporal and spatial scales for grassland LAI estimations. Ground temporal and spatial observations of hyperspectral reflectance and LAI were carried out at two grassland sites (Monte Bondone, Italy, and Neustift, Austria). A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), we demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. The RENDVI783.740 SVI was the least affected by traits co-variation, and more studies are needed to confirm its potential for heterogeneous grasslands LAI monitoring using S-2, S-3, or Gaofen-5 (GF-5) and PRISMA bands.

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Understanding Satellite-Observed Mountain-Wave Signatures Using High-Resolution Numerical Model Data

Weather and Forecasting ◽

10.1175/2008waf2222127.1 ◽

2009 ◽

Vol 24 (1) ◽

pp. 76-86 ◽

Cited By ~ 23

Author(s):

W. F. Feltz ◽

K. M. Bedka ◽

J. A. Otkin ◽

T. Greenwald ◽

S. A. Ackerman

Keyword(s):

Water Vapor ◽

High Resolution ◽

Weighting Function ◽

Model Simulation ◽

Wave Train ◽

Radiative Transfer Model ◽

Transfer Model ◽

Model Data ◽

Mountain Wave ◽

Mountain Waves

Abstract Prior work has shown that pilot reports of severe turbulence over Colorado often occur when complex interference or crossing wave patterns are present in satellite water vapor imagery downstream of the Rocky Mountains. To improve the understanding of these patterns, a high-resolution (1-km) Weather Research and Forecasting (WRF) model simulation was performed for an intense mountain-wave event that occurred on 6 March 2004. Synthetic satellite imagery was subsequently generated by passing the model-simulated data through a forward radiative transfer model. Comparison with concurrent Moderate Resolution Imaging Spectroradiometer (MODIS) water vapor imagery demonstrates that the synthetic satellite data realistically captured many of the observed mesoscale features, including a mountain-wave train extending far downstream of the Colorado Front Range, the deformation of this wave train by an approaching cold front, and the substantially warmer brightness temperatures in the lee of the major mountain ranges composing the Colorado Rockies. Inspection of the model data revealed that the mountain waves redistributed the water vapor within the lower and middle troposphere, with the maximum column-integrated water vapor content occurring one-quarter wavelength downstream of the maximum ascent within each mountain wave. Due to this phase shift, the strongest vertical motions occur halfway between the locally warm and cool brightness temperature couplets in the water vapor imagery. Interference patterns seen in the water vapor imagery appear to be associated with mesoscale variability in the ambient wind field at or near mountaintop due to flow interaction with the complex topography. It is also demonstrated that the synergistic use of multiple water vapor channels provides a more thorough depiction of the vertical extent of the mountain waves since the weighting function for each channel peaks at a different height in the atmosphere.

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2018 Atmospheric Motion Vector (AMV) Intercomparison Study

Remote Sensing ◽

10.3390/rs11192240 ◽

2019 ◽

Vol 11 (19) ◽

pp. 2240 ◽

Cited By ~ 1

Author(s):

David Santek ◽

Richard Dworak ◽

Sharon Nebuda ◽

Steve Wanzong ◽

Régis Borde ◽

...

Keyword(s):

Weather Prediction ◽

Motion Vector ◽

Estimation Method ◽

Japan Meteorological Agency ◽

Radiative Transfer Model ◽

Transfer Model ◽

European Organization ◽

Specific Configuration ◽

Atmospheric Motion ◽

Height Assignment

Atmospheric Motion Vectors (AMVs) calculated by six different institutions (Brazil Center for Weather Prediction and Climate Studies/CPTEC/INPE, European Organization for the Exploitation of Meteorological Satellites/EUMETSAT, Japan Meteorological Agency/JMA, Korea Meteorological Administration/KMA, Unites States National Oceanic and Atmospheric Administration/NOAA, and the Satellite Application Facility on Support to Nowcasting and Very short range forecasting/NWCSAF) with JMA’s Himawari-8 satellite data and other common input data are here compared. The comparison is based on two different AMV input datasets, calculated with two different image triplets for 21 July 2016, and the use of a prescribed and a specific configuration. The main results of the study are summarized as follows: (1) the differences in the AMV datasets depend very much on the ‘AMV height assignment’ used and much less on the use of a prescribed or specific configuration; (2) the use of the ‘Common Quality Indicator (CQI)’ has a quantified skill in filtering collocated AMVs for an improved statistical agreement between centers; (3) Among the six AMV operational algorithms verified by this AMV Intercomparison, JMA AMV algorithm has the best overall performance considering all validation metrics, mainly due to its new height assignment method: ‘Optimal estimation method considering the observed infrared radiances, the vertical profile of the Numerical Weather Prediction wind, and the estimated brightness temperature using a radiative transfer model’.

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Local Tilt Optimization of Photovoltaic Solar Panels for Maximum Radiation Absorption

International Journal of Photoenergy ◽

10.1155/2019/3254780 ◽

2019 ◽

Vol 2019 ◽

pp. 1-10

Author(s):

Mauro Masili ◽

Liliane Ventura

Keyword(s):

Solar Radiation ◽

Tilt Angle ◽

Spectral Response ◽

Solar Spectrum ◽

Weather Conditions ◽

Solar Irradiation ◽

Radiation Absorption ◽

Radiative Transfer Model ◽

Transfer Model ◽

Solar Panels

Incident solar radiation on photovoltaic (PV) solar panels is not constant throughout the year. Besides dependence on the season, solar radiation is reliant on the location and weather conditions. For a given location on Earth, the best-fixed orientation of a PV panel can be determined by achieving the maximum incident solar irradiance throughout the year or for a predetermined period. In this paper, we use a sophisticated atmospheric radiative transfer model to calculate the direct and diffuse solar irradiation (radiant exposure) for the solar spectrum incident on PV solar panels to determine the best tilt angle of the panel in order to maximize absorption of solar radiation for selected periods. We used the Regula-Falsi numerical method to obtain the tilt angle at which the derivative of solar irradiation (concerning the tilt angle) approaches zero. Moreover, the spectral response of typical silicon cells is taken into account. These calculations were carried out in São Carlos (SP), a town in the southeast of Brazil. The best tilt angle was obtained for three selected periods. Additionally, we provide results for Southern latitudes ranging from 0° to −55° in steps of −5° for the meteorological seasons. We have shown that for each period, there is an increase in solar radiation absorption compared to the traditional installation angle based exclusively on the local latitude. These calculations can be extended to any location.

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Greenhouse effects of aircraft emissions as calculated by a radiative transfer model

Annales Geophysicae ◽

10.1007/s00585-995-0413-4 ◽

1995 ◽

Vol 13 (4) ◽

pp. 413-418 ◽

Cited By ~ 29

Author(s):

J. P. F. Fortuin ◽

R. van Dorland ◽

W. M. F. Wauben ◽

H. Kelder

Keyword(s):

Water Vapor ◽

Radiative Transfer ◽

Indirect Effect ◽

Radiative Forcing ◽

Combustion Products ◽

Ozone Production ◽

Radiative Transfer Model ◽

Transfer Model ◽

Aircraft Emissions ◽

The North

Abstract. With a radiative transfer model, assessments are made of the radiative forcing in northern mid-latitudes due to aircraft emissions up to 1990. Considered are the direct climate effects from the major combustion products carbon dioxide, nitrogen dioxide, water vapor and sulphur dioxide, as well as the indirect effect of ozone production from NOx emissions. Our study indicates a local radiative forcing at the tropopause which should be negative in summer (–0.5 to 0.0 W/m2) and either negative or positive in winter (–0.3 to 0.2 W/m2). To these values the indirect effect of contrails has to be added, which for the North Atlantic Flight Corridor covers the range –0.2 to 0.3 W/m2 in summer and 0.0 to 0.3 W/m2 in winter. Apart from optically dense non-aged contrails during summer, negative forcings are due to solar screening by sulphate aerosols. The major positive contributions come from contrails, stratospheric water vapor in winter and ozone in summer. The direct effect of NO2 is negligible and the contribution of CO2 is relatively small.

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Mesoscale Simulations of Australian Direct Normal Irradiance, Featuring an Extreme Dust Event

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-17-0091.1 ◽

2018 ◽

Vol 57 (3) ◽

pp. 493-515 ◽

Cited By ~ 7

Author(s):

S. K. Mukkavilli ◽

A. A. Prasad ◽

R. A. Taylor ◽

A. Troccoli ◽

M. J. Kay

Keyword(s):

Radiative Transfer ◽

Climate Models ◽

Global Climate ◽

Weather Prediction ◽

Wrf Model ◽

Global Climate Models ◽

Radiative Transfer Model ◽

Transfer Model ◽

Dust Event ◽

Direct Normal Irradiance

AbstractDirect normal irradiance (DNI) is the main input for concentrating solar power (CSP) technologies—an important component in future energy scenarios. DNI forecast accuracy is sensitive to radiative transfer schemes (RTSs) and microphysics in numerical weather prediction (NWP) models. Additionally, NWP models have large regional aerosol uncertainties. Dust aerosols can significantly attenuate DNI in extreme cases, with marked consequences for applications such as CSP. To date, studies have not compared the skill of different physical parameterization schemes for predicting hourly DNI under varying aerosol conditions over Australia. The authors address this gap by aiming to provide the first Weather and Forecasting (WRF) Model DNI benchmarks for Australia as baselines for assessing future aerosol-assimilated models. Annual and day-ahead simulations against ground measurements at selected sites focusing on an extreme dust event are run. Model biases are assessed for five shortwave RTSs at 30- and 10-km grid resolutions, along with the Thompson aerosol-aware scheme in three different microphysics configurations: no aerosols, fixed optical properties, and monthly climatologies. From the annual simulation, the best schemes were the Rapid Radiative Transfer Model for global climate models (RRTMG), followed by the new Goddard and Dudhia schemes, despite the relative simplicity of the latter. These top three RTSs all had 1.4–70.8 W m−2 lower mean absolute error than persistence. RRTMG with monthly aerosol climatologies was the best combination. The extreme dust event had large DNI mean bias overpredictions (up to 4.6 times), compared to background aerosol results. Dust storm–aware DNI forecasts could benefit from RRTMG with high-resolution aerosol inputs.

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