Microwave signatures of ice hydrometeors from ground-based observations above Summit, Greenland

Abstract. Multi-instrument, ground-based measurements provide unique and comprehensive datasets of the atmosphere for a specific location over long periods of time and resulting data compliments past and existing global satellite observations. This paper explores the effect of ice hydrometeors on ground-based, high frequency passive microwave measurements and attempts to isolate an ice signature for summer seasons at Summit, Greenland from 2010–2013. Data from a combination of passive microwave, cloud radar, radiosonde, and ceilometer were examined to isolate the ice signature at microwave wavelengths. By limiting the study to a cloud liquid water path of 40 g m−2 or less, the cloud radar can identify cases where the precipitation was dominated by ice. These cases were examined using liquid water and gas microwave absorption models, and brightness temperatures were calculated for the high frequency microwave channels: 90, 150, and 225 GHz. By comparing the measured brightness temperatures from the microwave radiometers and the calculated brightness temperature using only gas and liquid contributions, any residual brightness temperature difference is due to emission and scattering of microwave radiation from the ice hydrometeors in the column. The ice signature in the 90, 150, and 225 GHz channels for the Summit Station summer months was isolated. This measured ice signature was then compared to an equivalent brightness temperature difference calculated with a radiative transfer model including microwave single scattering properties for several ice habits. Initial model results compare well against the four years of summer season isolated ice signature in the high-frequency microwave channels.

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Microwave signatures of ice hydrometeors from ground-based observations above Summit, Greenland

Atmospheric Chemistry and Physics ◽

10.5194/acp-16-4743-2016 ◽

2016 ◽

Vol 16 (7) ◽

pp. 4743-4756 ◽

Cited By ~ 6

Author(s):

Claire Pettersen ◽

Ralf Bennartz ◽

Mark S. Kulie ◽

Aronne J. Merrelli ◽

Matthew D. Shupe ◽

...

Keyword(s):

Brightness Temperature ◽

Temperature Difference ◽

Liquid Water ◽

High Frequency ◽

Passive Microwave ◽

Radiative Transfer Model ◽

Transfer Model ◽

Cloud Radar ◽

Brightness Temperatures ◽

High Frequency Microwave

Abstract. Multi-instrument, ground-based measurements provide unique and comprehensive data sets of the atmosphere for a specific location over long periods of time and resulting data compliment past and existing global satellite observations. This paper explores the effect of ice hydrometeors on ground-based, high-frequency passive microwave measurements and attempts to isolate an ice signature for summer seasons at Summit, Greenland, from 2010 to 2013. Data from a combination of passive microwave, cloud radar, radiosonde, and ceilometer were examined to isolate the ice signature at microwave wavelengths. By limiting the study to a cloud liquid water path of 40 g m−2 or less, the cloud radar can identify cases where the precipitation was dominated by ice. These cases were examined using liquid water and gas microwave absorption models, and brightness temperatures were calculated for the high-frequency microwave channels: 90, 150, and 225 GHz. By comparing the measured brightness temperatures from the microwave radiometers and the calculated brightness temperature using only gas and liquid contributions, any residual brightness temperature difference is due to emission and scattering of microwave radiation from the ice hydrometeors in the column. The ice signature in the 90, 150, and 225 GHz channels for the Summit Station summer months was isolated. This measured ice signature was then compared to an equivalent brightness temperature difference calculated with a radiative transfer model including microwave single-scattering properties for several ice habits. Initial model results compare well against the 4 years of summer season isolated ice signature in the high-frequency microwave channels.

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HAMP – the microwave package on the High Altitude and LOng range research aircraft HALO

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-4623-2014 ◽

2014 ◽

Vol 7 (5) ◽

pp. 4623-4657

Author(s):

M. Mech ◽

E. Orlandi ◽

S. Crewell ◽

F. Ament ◽

L. Hirsch ◽

...

Keyword(s):

High Altitude ◽

Long Range ◽

Microwave Remote Sensing ◽

Passive Microwave ◽

Lower Atmosphere ◽

Radiative Transfer Model ◽

Transfer Model ◽

Model Calculations ◽

Cloud Radar ◽

Research Aircraft

Abstract. An advanced package of microwave remote sensing instrumentation has been developed for the operation on the new German High Altitude LOng range research aircraft (HALO). The HALO Microwave Package, HAMP, consists of two nadir looking instruments: a cloud radar at 36 GHz and a suite of passive microwave radiometers with 26 frequencies in different bands between 22.24 and 183.31 ± 12.5 GHz. We present a description of HAMP's instrumentation together with an illustration of its potential. To demonstrate this potential synthetic measurements for the implemented passive microwave frequencies and the cloud radar based on cloud resolving and radiative transfer model calculations were performed. These illustrate the advantage of HAMP's chosen frequency coverage, which allows for improved detection of hydrometeors both via the emission and scattering of radiation. Regression algorithms compare HAMP retrieval with standard satellite instruments from polar orbiters and show its advantages particularly for the lower atmosphere with a reduced root mean square error by 5 and 15% for temperature and humidity, respectively. HAMP's main advantage is the high spatial resolution of about 1 km which is illustrated by first measurements from test flights. Together these qualities make it an exciting tool for gaining better understanding of cloud processes, testing retrieval algorithms, defining future satellite instrument specifications, and validating platforms after they have been placed in orbit.

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Effect of Structural Uncertainty in Passive Microwave Soil Moisture Retrieval Algorithm

Sensors ◽

10.3390/s20041225 ◽

2020 ◽

Vol 20 (4) ◽

pp. 1225

Author(s):

Lanka Karthikeyan ◽

Ming Pan ◽

Dasika Nagesh Kumar ◽

Eric F. Wood

Keyword(s):

Soil Moisture ◽

Global Scale ◽

Passive Microwave ◽

Radiative Transfer Model ◽

Retrieval Algorithm ◽

Transfer Model ◽

Structural Uncertainty ◽

Three Solutions ◽

Brightness Temperatures ◽

Retrieval Algorithms

Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (TB) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized TB measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the τ-ω types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that is inherent in all τ-ω types of models in passive microwave SM retrieval algorithms. In the process, a new analytical solution for concurrent VOD and SM retrieval is presented, along with two widely used existing analytical solutions. All three solutions are applied to a fixed framework of RTM to retrieve VOD and SM on a global scale, using X-band Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) TB data. Results indicate that, with structural uncertainty, there ensues a noticeable impact on the VOD and SM retrievals. In an era where the sensitivity of retrieval algorithms is still being researched, we believe the structural indeterminacy of RTM identified here would contribute to uncertainty in the soil moisture retrievals.

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Validation of the Hurricane Imaging Radiometer Forward Radiative Transfer Model for a Convective Rain Event

Remote Sensing ◽

10.3390/rs11222650 ◽

2019 ◽

Vol 11 (22) ◽

pp. 2650

Author(s):

Abdusalam Alasgah ◽

Maria Jacob ◽

Linwood Jones ◽

Larry Schneider

Keyword(s):

Radiative Transfer ◽

Brightness Temperature ◽

Surface Wind ◽

Surface Wind Speed ◽

Temperature Measurements ◽

Radiative Transfer Model ◽

Squall Line ◽

Transfer Model ◽

Rain Event ◽

Brightness Temperatures

The airborne Hurricane Imaging Radiometer (HIRAD) was developed to remotely sense hurricane surface wind speed (WS) and rain rate (RR) from a high-altitude aircraft. The approach was to obtain simultaneous brightness temperature measurements over a wide frequency range to independently retrieve the WS and RR. In the absence of rain, the WS retrieval has been robust; however, for moderate to high rain rates, the joint WS/RR retrieval has not been successful. The objective of this paper was to resolve this issue by developing an improved forward radiative transfer model (RTM) for the HIRAD cross-track viewing geometry, with separated upwelling and specularly reflected downwelling atmospheric paths. Furthermore, this paper presents empirical results from an unplanned opportunity that occurred when HIRAD measured brightness temperatures over an intense tropical squall line, which was simultaneously observed by a ground based NEXRAD (Next Generation Weather Radar) radar. The independently derived NEXRAD RR created the simultaneous 3D rain field “surface truth”, which was used as an input to the RTM to generate HIRAD modeled brightness temperatures. This paper presents favorable results of comparisons of theoretical and the simultaneous, collocated HIRAD brightness temperature measurements that validate the accuracy of this new HIRAD RTM.

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HAMP – the microwave package on the High Altitude and LOng range research aircraft (HALO)

Atmospheric Measurement Techniques ◽

10.5194/amt-7-4539-2014 ◽

2014 ◽

Vol 7 (12) ◽

pp. 4539-4553 ◽

Cited By ~ 33

Author(s):

M. Mech ◽

E. Orlandi ◽

S. Crewell ◽

F. Ament ◽

L. Hirsch ◽

...

Keyword(s):

High Altitude ◽

Long Range ◽

Microwave Remote Sensing ◽

Passive Microwave ◽

Lower Atmosphere ◽

Radiative Transfer Model ◽

Transfer Model ◽

Model Calculations ◽

Cloud Radar ◽

Research Aircraft

Abstract. An advanced package of microwave remote sensing instrumentation has been developed for the operation on the new German High Altitude LOng range research aircraft (HALO). The HALO Microwave Package, HAMP, consists of two nadir-looking instruments: a cloud radar at 36 GHz and a suite of passive microwave radiometers with 26 frequencies in different bands between 22.24 and 183.31 ± 12.5 GHz. We present a description of HAMP's instrumentation together with an illustration of its potential. To demonstrate this potential, synthetic measurements for the implemented passive microwave frequencies and the cloud radar based on cloud-resolving and radiative transfer model calculations were performed. These illustrate the advantage of HAMP's chosen frequency coverage, which allows for improved detection of hydrometeors both via the emission and scattering of radiation. Regression algorithms compare HAMP retrieval with standard satellite instruments from polar orbiters and show its advantages particularly for the lower atmosphere with a root-mean-square error reduced by 5 and 15% for temperature and humidity, respectively. HAMP's main advantage is the high spatial resolution of about 1 km, which is illustrated by first measurements from test flights. Together these qualities make it an exciting tool for gaining a better understanding of cloud processes, testing retrieval algorithms, defining future satellite instrument specifications, and validating platforms after they have been placed in orbit.

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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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Dependence of Simulation Biases at AHI Surface-Sensitive Channels on Land Surface Emissivity over China

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-17-0152.1 ◽

2018 ◽

Vol 35 (6) ◽

pp. 1283-1298 ◽

Cited By ~ 1

Author(s):

X. Zhuge ◽

X. Zou ◽

F. Weng ◽

M. Sun

Keyword(s):

Brightness Temperature ◽

Spectral Resolution ◽

Land Surface ◽

High Spectral Resolution ◽

Radiative Transfer Model ◽

Transfer Model ◽

Surface Emissivity ◽

Bare Rock ◽

Land Surface Emissivity ◽

M Channels

AbstractThis study compares the simulation biases of Advanced Himawari Imager (AHI) brightness temperature to observations made at night over China through the use of three land surface emissivity (LSE) datasets. The University of Wisconsin–Madison High Spectral Resolution Emissivity dataset, the Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer and Moderate Resolution Imaging Spectroradiometer Emissivity database over Land High Spectral Resolution Emissivity dataset, and the International Geosphere–Biosphere Programme (IGBP) infrared LSE module, as well as land skin temperature observations from the National Basic Meteorological Observing stations in China are used as inputs to the Community Radiative Transfer Model. The results suggest that the standard deviations of AHI observations minus background simulations (OMBs) are largely consistent for the three LSE datasets. Also, negative biases of the OMBs of brightness temperature uniformly occur for each of the three datasets. There are no significant differences in OMB biases estimated with the three LSE datasets over cropland and forest surface types for all five AHI surface-sensitive channels. Over the grassland surface type, significant differences (~0.8 K) are found at the 10.4-, 11.2-, and 12.4-μm channels if using the IGBP dataset. Over nonvegetated surface types (e.g., sandy land, gobi, and bare rock), the lack of a monthly variation in IGBP LSE introduces large negative biases for the 3.9- and 8.6-μm channels, which are greater than those from the two other LSE datasets. Thus, improvements in simulating AHI infrared surface-sensitive channels can be made when using spatially and temporally varying LSE estimates.

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Modelling the L-Band Snow-Covered Surface Emission in a Winter Canadian Prairie Environment

Remote Sensing ◽

10.3390/rs10091451 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1451 ◽

Cited By ~ 3

Author(s):

Alexandre Roy ◽

Marion Leduc-Leballeur ◽

Ghislain Picard ◽

Alain Royer ◽

Peter Toose ◽

...

Keyword(s):

Radiative Transfer ◽

Brightness Temperature ◽

Frozen Soil ◽

Microwave Emission ◽

Radiative Transfer Model ◽

Transfer Model ◽

Emission Model ◽

Canadian Prairie ◽

Seasonal Snow ◽

L Band

Detailed angular ground-based L-band brightness temperature (TB) measurements over snow covered frozen soil in a prairie environment were used to parameterize and evaluate an electromagnetic model, the Wave Approach for LOw-frequency MIcrowave emission in Snow (WALOMIS), for seasonal snow. WALOMIS, initially developed for Antarctic applications, was extended with a soil interface model. A Gaussian noise on snow layer thickness was implemented to account for natural variability and thus improve the TB simulations compared to observations. The model performance was compared with two radiative transfer models, the Dense Media Radiative Transfer-Multi Layer incoherent model (DMRT-ML) and a version of the Microwave Emission Model for Layered Snowpacks (MEMLS) adapted specifically for use at L-band in the original one-layer configuration (LS-MEMLS-1L). Angular radiometer measurements (30°, 40°, 50°, and 60°) were acquired at six snow pits. The root-mean-square error (RMSE) between simulated and measured TB at vertical and horizontal polarizations were similar for the three models, with overall RMSE between 7.2 and 10.5 K. However, WALOMIS and DMRT-ML were able to better reproduce the observed TB at higher incidence angles (50° and 60°) and at horizontal polarization. The similar results obtained between WALOMIS and DMRT-ML suggests that the interference phenomena are weak in the case of shallow seasonal snow despite the presence of visible layers with thicknesses smaller than the wavelength, and the radiative transfer model can thus be used to compute L-band brightness temperature.

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Version 4 CALIPSO IIR ice and liquid water cloud microphysical properties, Part I: the retrieval algorithms

10.5194/amt-2020-387 ◽

2020 ◽

Author(s):

Anne Garnier ◽

Jacques Pelon ◽

Nicolas Pascal ◽

Mark A. Vaughan ◽

Philippe Dubuisson ◽

...

Keyword(s):

Liquid Water ◽

Cloud Base ◽

Transfer Model ◽

Effective Diameter ◽

Ice Clouds ◽

Clear Sky ◽

Brightness Temperatures ◽

Microphysical Properties ◽

Data Products ◽

Level 2

Abstract. Following the release of the Version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version 4 (V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear sky brightness temperatures over oceans has been updated and tuned for the simulations using MERRA-2 data to match IIR observations in clear sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5-km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ± 0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also aimed at improving retrievals in ice clouds having large optical depths by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and the CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3, and increases the number of retrievals in dense ice clouds. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 μm and 10.6 μm and at 12.05 μm and 08.65 μm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice crystal models from the recent TAMUice 2016 database, namely the single hexagonal column model and the 8-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 µm and 10.6 µm and effective diameter as derived from in situ measurements at tropical and mid-latitudes during the TC4 and SPARTICUS field experiments.

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