Boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy

Abstract. Daytime clear-sky total column water vapour (TCWV) is commonly retrieved from visible and shortwave infrared reflectance (VSWIR) measurements, and modern missions such as the upcoming Earth Surface Mineral Dust Source Investigation (EMIT) offer unprecedented horizontal resolution of order 30–80 m. We provide evidence that for convective planetary boundary layers (PBLs), spatial variability in TCWV corresponds to variability in PBL water vapour. Using an observing system simulation experiment (OSSE) applied to large eddy simulation (LES) output, we show that EMIT can retrieve horizontal variability in PBL water vapour, provided that the domain surface is uniformly composed of either vegetated surfaces or mineral surfaces. Random retrieval errors are easily quantified and removed, but biases from −7 % to +34 % remain in retrieved spatial standard deviation and are primarily related to the retrieval's assumed atmospheric profiles. Future retrieval development could greatly mitigate these errors. Finally, we account for changing solar zenith angle (SZA) from 15 to 60∘ and show that the non-vertical solar path destroys the correspondence between footprint-retrieved TCWV and the true TCWV directly above that footprint. Even at the 250 m horizontal resolution regularly obtained by current sensors, the derived maps correspond poorly to true TCWV at the pixel scale, with r2<0.6 at SZA=30∘. However, the derived histograms of TCWV in an area are closely related to the true histograms of TCWV at the nominal footprint resolution. Upcoming VSWIR instruments, primarily targeting surface properties, can therefore offer new information on PBL water vapour spatial statistics to the atmospheric community.

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Boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy

10.5194/amt-2021-89 ◽

2021 ◽

Author(s):

Mark T. Richardson ◽

David R. Thompson ◽

Marcin J. Kurowski ◽

Matthew D. Lebsock

Keyword(s):

Water Vapour ◽

Imaging Spectroscopy ◽

Optimal Estimation ◽

Horizontal Resolution ◽

Mineral Surfaces ◽

Eddy Simulation ◽

New Information ◽

Planetary Boundary Layers ◽

Surface Mineral ◽

Shortwave Infrared

Abstract. Daytime clear-sky total column water vapour (TCWV) is commonly retrieved from visible and shortwave infrared reflectance (VSWIR) measurements, and upcoming missions such as the Earth Surface Mineral Dust Source Investigation (EMIT) will offer unprecedented horizontal resolution of order 30–80 m. We provide evidence that for convective planetary boundary layers (PBLs), spatial variability in TCWV corresponds to variability in PBL water vapour. Using synthetic optimal estimation retrievals applied to Large Eddy Simulation (LES) output, we show that EMIT can retrieve horizontal variability in PBL water vapour, provided that the domain surface is uniformly composed of either vegetated surfaces or mineral surfaces. Random retrieval errors are easily quantified and removed, but biases from −7 % to +34 % remain in retrieved spatial standard deviation and are primarily related to the retrieval’s assumed atmospheric profiles. Future retrieval development could greatly mitigate these errors. Finally, we account for changing solar zenith angle (SZA) from 15–60° and show that the non-vertical solar path destroys the correspondence between footprint retrieved TCWV and the true TCWV directly above that footprint. Even at the 250 m horizontal resolution regularly obtained by current sensors, the derived maps correspond poorly to true TCWV at the pixel-scale, with r2 < 0.6 at SZA = 30°. However, the derived histograms of TCWV in an area are closely related to the true histograms of TCWV at the nominal footprint resolution. Upcoming VSWIR instruments, primarily targeting surface properties, can therefore offer new information on PBL water vapour spatial statistics to the atmospheric community.

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New sampling strategy mitigates a solar-geometry-induced bias in sub-kilometre vapour scaling statistics derived from imaging spectroscopy

Atmospheric Measurement Techniques ◽

10.5194/amt-15-117-2022 ◽

2022 ◽

Vol 15 (1) ◽

pp. 117-129

Author(s):

Mark T. Richardson ◽

David R. Thompson ◽

Marcin J. Kurowski ◽

Matthew D. Lebsock

Keyword(s):

Water Vapour ◽

Imaging Spectroscopy ◽

Sampling Strategy ◽

Horizontal Resolution ◽

Noise Model ◽

Dust Source ◽

Clear Sky ◽

Large Eddy ◽

Instrument Noise ◽

Surface Mineral

Abstract. Upcoming spaceborne imaging spectrometers will retrieve clear-sky total column water vapour (TCWV) over land at a horizontal resolution of 30–80 m. Here we show how to obtain, from these retrievals, exponents describing the power-law scaling of sub-kilometre horizontal variability in clear-sky bulk planetary boundary layer (PBL) water vapour (q) accounting for realistic non-vertical sunlight paths. We trace direct solar beam paths through large eddy simulations (LES) of shallow convective PBLs and show that retrieved 2-D water vapour fields are “smeared” in the direction of the solar azimuth. This changes the horizontal spatial scaling of the field primarily in that direction, and we address this by calculating exponents perpendicular to the solar azimuth, that is to say flying “across” the sunlight path rather than “towards” or “away” from the Sun. Across 23 LES snapshots, at solar zenith angle SZA = 60∘ the mean bias in calculated exponent is 38 ± 12 % (95 % range) along the solar azimuth, while following our strategy it is 3 ± 9 % and no longer significant. Both bias and root-mean-square error decrease with lower SZA. We include retrieval errors from several sources, including (1) the Earth Surface Mineral Dust Source Investigation (EMIT) instrument noise model, (2) requisite assumptions about the atmospheric thermodynamic profile, and (3) spatially nonuniform aerosol distributions. By only considering the direct beam, we neglect 3-D radiative effects such as light scattered into the field of view by nearby clouds. However, our proposed technique is necessary to counteract the direct-path effect of solar geometries and obtain unique information about sub-kilometre PBL q scaling from upcoming spaceborne spectrometer missions.

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New sampling strategy removes imaging spectroscopy solar-smearing bias in sub-km vapour scaling statistics

10.5194/amt-2021-163 ◽

2021 ◽

Author(s):

Mark T. Richardson ◽

David R. Thompson ◽

Marcin J. Kurowski ◽

Matthew D. Lebsock

Keyword(s):

Water Vapour ◽

Imaging Spectroscopy ◽

Sampling Strategy ◽

Horizontal Resolution ◽

Noise Model ◽

Dust Source ◽

Clear Sky ◽

Large Eddy ◽

Instrument Noise ◽

Surface Mineral

Abstract. Upcoming spaceborne imaging spectrometers will allow retrieval of total column water vapour (TCWV) over land at horizontal resolution of 30–80 m. Here we show how to obtain, from these retrievals, exponents describing the power-law scaling of sub-km horizontal variability in clear-sky bulk planetary boundary layer (PBL) water vapour (q). Using large-eddy simulations (LES) of shallow convective PBLs we show how sunlight entering the PBL up to several km away from the footprint location degrades estimates of these exponents. We address this by calculating exponents perpendicular to the solar azimuth, that is to say flying “across” the sunlight path rather than “towards” or “away” from the Sun. Across 23 LES snapshots, at SZA = 60° the mean bias in calculated exponent is 38 ± 12 % (95 % range) along the solar azimuth, while following our strategy it is 3 ± 9 % and no longer significant. Both bias and root-mean-square error RMSE decrease with lower SZA. We include retrieval errors from several sources including: (1) the Earth Surface Mineral Dust Source Investigation (EMIT) instrument noise model, (2) requisite assumptions about the atmospheric thermodynamic profile, and (3) spatially nonuniform aerosol distributions. This technique can be used to obtain unique information about sub-km PBL q scaling from upcoming spaceborne spectrometer missions, while mitigating errors due to challenging solar geometries.

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Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project

Atmospheric Measurement Techniques ◽

10.5194/amt-11-2395-2018 ◽

2018 ◽

Vol 11 (4) ◽

pp. 2395-2426 ◽

Cited By ~ 33

Author(s):

Isabelle De Smedt ◽

Nicolas Theys ◽

Huan Yu ◽

Thomas Danckaert ◽

Christophe Lerot ◽

...

Keyword(s):

Near Infrared ◽

Horizontal Resolution ◽

Retrieval Algorithm ◽

User Requirements ◽

Vertical Column ◽

Ultraviolet Range ◽

Order Of Magnitude ◽

Shortwave Infrared ◽

Double Channel ◽

The Eu

Abstract. On board the Copernicus Sentinel-5 Precursor (S5P) platform, the TROPOspheric Monitoring Instrument (TROPOMI) is a double-channel, nadir-viewing grating spectrometer measuring solar back-scattered earthshine radiances in the ultraviolet, visible, near-infrared, and shortwave infrared with global daily coverage. In the ultraviolet range, its spectral resolution and radiometric performance are equivalent to those of its predecessor OMI, but its horizontal resolution at true nadir is improved by an order of magnitude. This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the S5P operational processor and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted. Finally, verification results based on the application of the algorithm to OMI measurements are presented, demonstrating the performances expected for TROPOMI.

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Determination of the viability of retinispora (Hinoki cypress) seeds using shortwave infrared hyperspectral imaging spectroscopy

Journal of Near Infrared Spectroscopy ◽

10.1177/0967033519898890 ◽

2020 ◽

Vol 28 (2) ◽

pp. 70-80 ◽

Cited By ~ 1

Author(s):

Perez Mukasa ◽

Collins Wakholi ◽

Akbar Faqeerzada Mohammad ◽

Eunsoo Park ◽

Jayoung Lee ◽

...

Keyword(s):

Discriminant Analysis ◽

Hyperspectral Imaging ◽

Imaging Spectroscopy ◽

Partial Least Square ◽

Least Square ◽

Successive Projections Algorithm ◽

Hinoki Cypress ◽

Sorting System ◽

Shortwave Infrared ◽

Successive Projections

The combination of hyperspectral imaging with multivariate data analysis methods has recently been applied to develop a nondestructive technique, required to determine the seed viability of artificially aged vegetable and cereal seeds. In this study, the potential of shortwave infrared hyperspectral imaging to determine the viability of naturally aged seeds was investigated and thereafter a model for online seed sorting system was developed. The hyperspectral images of 400 Hinoki cypress tree seeds were acquired, and germination tests were conducted for viability confirmation, which indicated 31.5% of the viable seeds. Partial least square discriminant analysis models with 179 variables in the wavelength region of 1000–1800 nm were developed with a maximum model accuracy of 98.4% and 93.8% in both the calibration and validation sets, respectively. The partial least square discriminant analysis beta coefficient revealed the key wavelengths to differentiate viable from nonviable seeds, determined based on the differences in the chemical compositions of the seeds, including their lipid and fatty acid contents, which may control the germination ability of the seeds. The most effective wavelengths were selected using two model-based variable selection methods (i.e., the variable importance of projection (15 variables) and the successive projections algorithm (8 variables)) to develop the model. The successive projections algorithm wavelength selection method was considered to develop a viability model, and its application to the raw data resulted in a prediction accuracy of 94.7% in the calibration set and 92.2% in the validation set. These results demonstrate the potential of shortwave infrared hyperspectral imaging spectroscopy as a powerful nondestructive method to determine the viability of Hinoki cypress seeds. This method could be applied to develop an online seed sorting system for seed companies and nurseries.

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Remote sounding of atmospheric temperature from satellites IV. The selective chopper radiometer for Nimbus 5

Proceedings of the Royal Society of London Series A - Mathematical and Physical Sciences ◽

10.1098/rspa.1973.0085 ◽

1973 ◽

Vol 334 (1597) ◽

pp. 149-170 ◽

Cited By ~ 43

Keyword(s):

Water Vapour ◽

Near Infrared ◽

Far Infrared ◽

Atmospheric Temperature ◽

Horizontal Resolution ◽

Ice Clouds ◽

New Instrument ◽

Remote Sounding ◽

Complete Set ◽

High Clouds

An improved version of the selective chopper radiometer which has successfully flown for three years on the Nimbus 4 satellite has been built for the Nimbus 5 satellite which was launched in December 1972. The new instrument has 16 channels, eight of which observe emission from the 15 μm band of carbon dioxide for remote temperature sounding, two observe emission from water-vapour and ice clouds in the far infrared, one observes emission from low atmospheric water-vapour, three are in spectral regions where the atmosphere is substantially transparent, i.e. window regions, and two observe reflected sunlight from high clouds near to 2.7 μm in the near infrared. The horizontal resolution of the instrument is about 25 km and a complete set of measurements is made every 4 s. The design, construction and calibration of the instrument are described.

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Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle

10.5194/egusphere-egu2020-21947 ◽

2020 ◽

Author(s):

Veronique Michot ◽

Helene Brogniez ◽

Mathieu Vrac ◽

Soulivanh Thao ◽

Helene Chepfer ◽

...

Keyword(s):

Relative Humidity ◽

Quantile Regression ◽

Water Vapour ◽

Climate Models ◽

Water Cycle ◽

Skill Score ◽

Horizontal Resolution ◽

Atmospheric Water ◽

Global Knowledge ◽

Humidity Profiles

<p>The multi-scale interactions at the origin of the links between clouds and water vapour are essential for the Earth's energy balance and thus the climate, from local to global. Knowledge of the distribution and variability of water vapour in the troposphere is indeed a major issue for the understanding of the atmospheric water cycle. At present, these interactions are poorly known at regional and local scales, i.e. within 100km, and are therefore poorly represented in numerical climate models. This is why we have sought to predict cloud scale relative humidity profiles in the intertropical zone, using a non-parametric statistical downscaling method called quantile regression forest. The procedure includes co-located data from 3 satellites: CALIPSO lidar and CloudSat radar, used as predictors and providing cloud properties at 90m and 1.4km horizontal resolution respectively; SAPHIR data used as a predictor and providing relative humidity at an initial horizontal resolution of 10km. Quantile regression forests were used to predict relative humidity profiles at the CALIPSO and CloudSat scales. These predictions are able to reproduce a relative humidity variability consistent with the cloud profiles and are confirmed by values of coefficients of determination greater than 0.7, relative to observed relative humidity, and Continuous Rank Probability Skill Score between 0 and 1, relative to climatology. Lidar measurements from the NARVAL 1&2 campaigns and radiosondes from the EUREC4A campaigns were also used to compare Relative Humidity profiles at the SAPHIR scale and at the scale of forest regression prediction by quantile regression.</p>

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Large-eddy simulation of the plume generated by the fire at the Buncefield oil depot in December 2005

Proceedings of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rspa.2008.0288 ◽

2008 ◽

Vol 465 (2102) ◽

pp. 397-419 ◽

Cited By ~ 8

Author(s):

B.J Devenish ◽

J.M Edwards

Keyword(s):

Solar Radiation ◽

Large Eddy Simulation ◽

Water Vapour ◽

Maximum Concentration ◽

Initial Conditions ◽

Aerosol Concentration ◽

Eddy Simulation ◽

Incoming Solar Radiation ◽

Small Depth ◽

Large Eddy

The explosion at the Buncefield oil depot in Hertfordshire, UK on 11 December 2005 produced the largest fire in Europe since the Second World War. The magnitude of the fire and the scale of the resulting plume thus present a stringent test of any mathematical model of buoyant plumes. A large-eddy simulation of the Boussinesq equations with suitable initial conditions is shown to reproduce the characteristics of the observed plume; both the height of the plume above the source and the direction of the downwind spread agree with the observations. This supports the use of the Boussinesq assumption, even for such a powerful plume as the one generated by the Buncefield fire. The presence of a realistic water vapour profile does not lead to significant additional latent heating of the plume, but does lead to a small increase in the final rise height of the plume due to the increased buoyancy provided by the water vapour. Our simulations include the interaction of radiation with the aerosol in the plume, and reproduce the observed optical thickness of the plume and the reduction of solar radiation reaching the ground. Far downwind of the source, solar radiation is shown to play a role in lofting the laterally spreading plume, but the manner in which it does so depends on the aerosol concentration. In the case of high aerosol concentration, the thickness of the plume increases; the incoming solar radiation is absorbed over such a small depth that only the top of the plume is lofted upwards and the level of maximum concentration remains almost unchanged relative to the case with no radiation. When the aerosol concentration is low, the whole plume is heated by the incoming solar radiation and the lofting is more coherent, with the result that the level of maximum concentration increases relative to the case with no radiation, but the thickness of the plume increases only slightly.

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Statistical downscaling of water vapour satellite measurements from profiles of tropical ice clouds

Earth System Science Data ◽

10.5194/essd-12-1-2020 ◽

2020 ◽

Vol 12 (1) ◽

pp. 1-20 ◽

Cited By ~ 1

Author(s):

Giulia Carella ◽

Mathieu Vrac ◽

Hélène Brogniez ◽

Pascal Yiou ◽

Hélène Chepfer

Keyword(s):

Relative Humidity ◽

Water Vapour ◽

Water Cycle ◽

Skill Score ◽

Horizontal Resolution ◽

Coefficient Of Determination ◽

Climate Projections ◽

Ice Clouds ◽

Multi Scale ◽

Scattering Ratio

Abstract. Multi-scale interactions between the main players of the atmospheric water cycle are poorly understood, even in the present-day climate, and represent one of the main sources of uncertainty among future climate projections. Here, we present a method to downscale observations of relative humidity available from the Sondeur Atmosphérique du Profil d'Humidité Intertropical par Radiométrie (SAPHIR) passive microwave sounder at a nominal horizontal resolution of 10 km to the finer resolution of 90 m using scattering ratio profiles from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar. With the scattering ratio profiles as covariates, an iterative approach applied to a non-parametric regression model based on a quantile random forest is used. This allows us to effectively incorporate into the predicted relative humidity structure the high-resolution variability from cloud profiles. The finer-scale water vapour structure is hereby deduced from the indirect physical correlation between relative humidity and the lidar observations. Results are presented for tropical ice clouds over the ocean: based on the coefficient of determination (with respect to the observed relative humidity) and the continuous rank probability skill score (with respect to the climatology), we conclude that we are able to successfully predict, at the resolution of cloud measurements, the relative humidity along the whole troposphere, yet ensure the best possible coherence with the values observed by SAPHIR. By providing a method to generate pseudo-observations of relative humidity (at high spatial resolution) from simultaneous co-located cloud profiles, this work will help revisit some of the current key barriers in atmospheric science. A sample dataset of simultaneous co-located scattering ratio profiles of tropical ice clouds and observations of relative humidity downscaled at the resolution of cloud measurements is available at https://doi.org/10.14768/20181022001.1 (Carella et al., 2019).

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Water vapour total columns from SCIAMACHY spectra in the 2.36 μm window

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-2-1453-2009 ◽

2009 ◽

Vol 2 (3) ◽

pp. 1453-1485

Author(s):

H. Schrijver ◽

A. M. S. Gloudemans ◽

C. Frankenberg ◽

I. Aben

Keyword(s):

Water Vapour ◽

Weather Forecast ◽

Mean Value ◽

Likelihood Method ◽

Independent Verification ◽

Scattering Effects ◽

Spectroscopic Information ◽

Novel Method ◽

Iterative Maximum Likelihood ◽

Shortwave Infrared

Abstract. The potential of the shortwave infrared channel of the atmospheric spectrometer SCIAMACHY on Envisat to provide accurate measurements of total atmospheric water vapour columns is explored. It is shown that good quality results can be obtained for cloud free scenes above the continents using the Iterative Maximum Likelihood Method. In addition to the standard cloud filter employed in this method, further cloud screening is obtained by comparing simultaneously retrieved methane columns with values expected from models. A novel method is used to correct for the scattering effects introduced in the spectra by the ice layer on the detector window. The retrieved water vapour total columns for the period 2003–2007 are compared with spatially and temporally collocated values from the European Centre for Mid-Range Weather Forecast (ECMWF) data. The observed differences for individual measurements have standard deviations not higher than 0.3 g/cm2 and an absolute mean value smaller than 0.01 g/cm2 with some regional excursions. The use of recently published spectroscopic data for water vapour led to a significant improvement in the agreement of the retrieved water vapour total columns and the values derived from ECMWF data. This analysis thus provides independent verification of the new spectroscopic information using atmospheric data.

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