Ground-Based Temperature and Humidity Profiling Using Spectral Infrared and Microwave Observations. Part II: Actual Retrieval Performance in Clear-Sky and Cloudy Conditions

AbstractAlthough current upper-air observing systems provide an impressive array of observations, many are deficient in observing the temporal evolution of the boundary layer thermodynamic profile. Ground-based remote sensing instruments such as the multichannel microwave radiometer (MWR) and Atmospheric Emitted Radiance Interferometer (AERI) are able to provide profiles of temperature and water vapor through the boundary layer at 5-min resolution or better. Previous work compared these instruments through optimal-estimation retrievals on simulated clear-sky spectra to evaluate the retrieval accuracy and information content of each instrument. In this study, this method is duplicated using real observations from collocated MWR and AERI instruments from a field campaign in southwestern Germany. When compared with radiosondes, this study confirms the previous results that AERI retrievals are more accurate than MWR retrievals in clear-sky and below-cloud-base profiling. These results demonstrate that the AERI has nearly 2 times as much information as the MWR.

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Remote sensing of boundary-layer temperature profiles by a scanning 5-mm microwave radiometer and RASS: a comparison experiment

IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development ◽

10.1109/igarss.1997.609236 ◽

2002 ◽

Cited By ~ 1

Author(s):

E.R. Westwater ◽

Y. Han ◽

V.G. Irisov ◽

V. Leuskiy ◽

E.N. Kadygrov ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Microwave Radiometer ◽

Temperature Profiles ◽

Comparison Experiment

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Assessing the accuracy of microwave radiometers and radio acoustic sounding systems for wind energy applications

10.5194/amt-2016-321 ◽

2016 ◽

Cited By ~ 2

Author(s):

Laura Bianco ◽

Katja Friedrich ◽

James Wilczak ◽

Duane Hazen ◽

Daniel Wolfe ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Relative Humidity ◽

Mean Absolute Error ◽

Microwave Radiometer ◽

Absolute Error ◽

Acoustic Sounding ◽

Energy Applications ◽

Virtual Temperature ◽

Microwave Radiometers

Abstract. To assess current remote-sensing capabilities for wind energy applications, a remote-sensing system evaluation study, called XPIA (eXperimental Planetary boundary layer Instrument Assessment), was held in the spring of 2015 at NOAA’s Boulder Atmospheric Observatory (BAO) facility. Several remote-sensing platforms were evaluated to determine their suitability for the verification and validation processes used to test the accuracy of numerical weather prediction models. The evaluation of these platforms was performed with respect to well-defined reference systems: the BAO’s 300-m tower equipped at 6 levels (50, 100, 150, 200, 250, and 300 m) with 12 sonic anemometers and 6 temperature and relative humidity sensors; and approximately 60 radiosonde launches. In this study we first employ these reference measurements to validate temperature profiles retrieved by two co-located microwave radiometers, as well as virtual temperature measured by co-located wind profiling radars equipped with radio acoustic sounding systems. Results indicate a mean absolute error in the temperature retrieved by the microwave radiometers below 1.5 °C in the lowest 5 km of the atmosphere, and a mean absolute error in the virtual temperature measured by the radio acoustic sounding systems below 0.8 °C in the layer of the atmosphere covered by these measurements (up to approximately 1.6–2 km). We also investigated the benefit of the vertical velocity applied to the speed of sound before computing the virtual temperature by the radio acoustic sounding systems. We find that using this correction frequently increases the RASS error, and that it should not be routinely applied to all data. Water vapor density profiles measured by the MWRs were also compared with similar measurements from the soundings, showing the capability of MWRs to follow the vertical profile measured by the sounding, and finding a mean absolute error below 0.5 g m−3 in the lowest 5 km of the atmosphere. However, the relative humidity profiles measured by the microwave radiometer lack the high-resolution details available from radiosonde profiles. An encouraging and significant finding of this study was that the coefficient of determination between the lapse rate measured by the microwave radiometer and the tower measurements over the tower levels between 50 and 300 m ranged from 0.76 to 0.91, proving that these remote-sensing instruments can provide accurate information on atmospheric stability conditions in the lower boundary layer.

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Observed Boundary Layer Controls on Shallow Cumulus at the ARM Southern Great Plains Site

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-17-0244.1 ◽

2018 ◽

Vol 75 (7) ◽

pp. 2235-2255 ◽

Cited By ~ 15

Author(s):

Neil P. Lareau ◽

Yunyan Zhang ◽

Stephen A. Klein

Keyword(s):

Boundary Layer ◽

Great Plains ◽

Vertical Velocity ◽

Mass Flux ◽

Cloud Base ◽

Liquid Water Path ◽

Southern Great Plains ◽

Clear Sky ◽

Shallow Cumulus ◽

In Situ Sensors

Abstract The boundary layer controls on shallow cumulus (ShCu) convection are examined using a suite of remote and in situ sensors at ARM Southern Great Plains (SGP). A key instrument in the study is a Doppler lidar that measures vertical velocity in the CBL and along cloud base. Using a sample of 138 ShCu days, the composite structure of the ShCu CBL is examined, revealing increased vertical velocity (VV) variance during periods of medium cloud cover and higher VV skewness on ShCu days than on clear-sky days. The subcloud circulations of 1791 individual cumuli are also examined. From these data, we show that cloud-base updrafts, normalized by convective velocity, vary as a function of updraft width normalized by CBL depth. It is also found that 63% of clouds have positive cloud-base mass flux and are linked to coherent updrafts extending over the depth of the CBL. In contrast, negative mass flux clouds lack coherent subcloud updrafts. Both sets of clouds possess narrow downdrafts extending from the cloud edges into the subcloud layer. These downdrafts are also present adjacent to cloud-free updrafts, suggesting they are mechanical in origin. The cloud-base updraft data are subsequently combined with observations of convective inhibition to form dimensionless “cloud inhibition” (CI) parameters. Updraft fraction and liquid water path are shown to vary inversely with CI, a finding consistent with CIN-based closures used in convective parameterizations. However, we also demonstrate a limited link between CBL vertical velocity variance and cloud-base updrafts, suggesting that additional factors, including updraft width, are necessary predictors for cloud-base updrafts.

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A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer

Atmospheric Measurement Techniques ◽

10.5194/amt-8-553-2015 ◽

2015 ◽

Vol 8 (2) ◽

pp. 553-566 ◽

Cited By ~ 5

Author(s):

M.-H. Ahn ◽

D. Han ◽

H. Y. Won ◽

V. Morris

Keyword(s):

Water Vapor Pressure ◽

Microwave Radiometer ◽

Surface Air Temperature ◽

Detection Algorithm ◽

Probability Of Detection ◽

Cloud Base ◽

Cloud Detection ◽

Clear Sky ◽

Spectral Test ◽

Free Data

Abstract. For better utilization of the ground-based microwave radiometer, it is important to detect the cloud presence in the measured data. Here, we introduce a simple and fast cloud detection algorithm by using the optical characteristics of the clouds in the infrared atmospheric window region. The new algorithm utilizes the brightness temperature (Tb) measured by an infrared radiometer installed on top of a microwave radiometer. The two-step algorithm consists of a spectral test followed by a temporal test. The measured Tb is first compared with a predicted clear-sky Tb obtained by an empirical formula as a function of surface air temperature and water vapor pressure. For the temporal test, the temporal variability of the measured Tb during one minute compares with a dynamic threshold value, representing the variability of clear-sky conditions. It is designated as cloud-free data only when both the spectral and temporal tests confirm cloud-free data. Overall, most of the thick and uniform clouds are successfully detected by the spectral test, while the broken and fast-varying clouds are detected by the temporal test. The algorithm is validated by comparison with the collocated ceilometer data for six months, from January to June 2013. The overall proportion of correctness is about 88.3% and the probability of detection is 90.8%, which are comparable with or better than those of previous similar approaches. Two thirds of discrepancies occur when the new algorithm detects clouds while the ceilometer does not, resulting in different values of the probability of detection with different cloud-base altitude, 93.8, 90.3, and 82.8% for low, mid, and high clouds, respectively. Finally, due to the characteristics of the spectral range, the new algorithm is found to be insensitive to the presence of inversion layers.

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Studying turbulence by remote sensing systems during slope-2016 campaign

EPJ Web of Conferences ◽

10.1051/epjconf/201817606010 ◽

2018 ◽

Vol 176 ◽

pp. 06010

Author(s):

Gregori de A. Moreira ◽

Juan L. Guerrero-Rascado ◽

Jose A. Benavent-Oltra ◽

Pablo Ortiz-Amezcua ◽

Roberto Róman ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Planetary Boundary Layer ◽

Microwave Radiometer ◽

Passive Microwave ◽

Doppler Lidar ◽

Sensing Systems ◽

Remote Sensing Systems ◽

Lowermost Part

The Planetary Boundary Layer (PBL) is the lowermost part of the troposphere. In this work, we analysed some high order moments and PBL height detected continuously by three remote sensing systems: an elastic lidar, a Doppler lidar and a passive Microwave Radiometer, during the SLOPE-2016 campaign, which was held in Granada from May to August 2016. This study confirms the feasibility of these systems for the characterization of the PBL, helping us to justify and understand its behaviour along the day.

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A novel technique for extracting clouds base height using ground based imaging

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-3-4231-2010 ◽

2010 ◽

Vol 3 (5) ◽

pp. 4231-4260 ◽

Cited By ~ 1

Author(s):

E. Hirsch ◽

E. Agassi ◽

I. Koren

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Thermal Imaging ◽

Field Measurements ◽

Cloud Base ◽

Convective Clouds ◽

Boundary Layer Clouds ◽

Remote Sensing Techniques ◽

Power Needs ◽

Cloud Base Height

Abstract. The height of a cloud in the atmospheric column is a key parameter in its characterization. Several remote sensing techniques (passive and active, either ground-based or on space-borne platforms) and in-situ measurements are routinely used in order to estimate top and base heights of clouds. In this article we present a novel method that combines thermal imaging from the ground and sounded wind profile in order to derive the cloud base height. This method is independent of cloud types, making it efficient for both low boundary layer and high clouds. In addition, using thermal imaging ensures extraction of clouds' features during daytime as well as at nighttime. The proposed technique was validated by comparison to active sounding by ceilometers (which is a standard ground based method), to lifted condensation level (LCL) calculations, and to MODIS products obtained from space. As all passive remote sensing techniques, the proposed method extracts only the height of the lowest cloud layer, thus upper cloud layers are not detected. Nevertheless, the information derived from this method can be complementary to space-borne cloud top measurements when deep-convective clouds are present. Unlike techniques such as LCL, this method is not limited to boundary layer clouds, and can extract the cloud base height at any level, as long as sufficient thermal contrast exists between the radiative temperatures of the cloud and its surrounding air parcel. Another advantage of the proposed method is its simplicity and modest power needs, making it particularly suitable for field measurements and deployment at remote locations. Our method can be further simplified for use with visible CCD or CMOS camera (although nighttime clouds will not be observed).

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Assimilation of Surface-Based Boundary Layer Profiler Observations during a Cool-Season Weather Event Using an Observing System Simulation Experiment. Part I: Analysis Impact

Monthly Weather Review ◽

10.1175/2011mwr3622.1 ◽

2011 ◽

Vol 139 (8) ◽

pp. 2309-2326 ◽

Cited By ~ 19

Author(s):

Jason A. Otkin ◽

Daniel C. Hartung ◽

David D. Turner ◽

Ralph A. Petersen ◽

Wayne F. Feltz ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Simulation Experiment ◽

System Simulation ◽

Microwave Radiometer ◽

Lower Troposphere ◽

Moisture Profile ◽

Wind Profiles ◽

Observing System Simulation Experiment ◽

The Impact

AbstractIn this study, an Observing System Simulation Experiment was used to examine how the assimilation of temperature, water vapor, and wind profiles from a potential array of ground-based remote sensing boundary layer profiling instruments impacts the accuracy of atmospheric analyses when using an ensemble Kalman filter data assimilation system. Remote sensing systems evaluated during this study include the Doppler wind lidar (DWL), Raman lidar (RAM), microwave radiometer (MWR), and the Atmospheric Emitted Radiance Interferometer (AERI). The case study tracked the evolution of several extratropical weather systems that occurred across the contiguous United States during 7–8 January 2008. Overall, the results demonstrate that using networks of high-quality temperature, wind, and moisture profile observations of the lower troposphere has the potential to improve the accuracy of wintertime atmospheric analyses over land. The impact of each profiling system was greatest in the lower and middle troposphere on the variables observed or retrieved by that instrument; however, some minor improvements also occurred in the unobserved variables and in the upper troposphere, particularly when RAM observations were assimilated. The best analysis overall was achieved when DWL wind profiles and temperature and moisture observations from the RAM, AERI, or MWR were assimilated simultaneously, which illustrates that both mass and momentum observations are necessary to improve the analysis accuracy.

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The COTUR project: Remote sensing of offshore turbulence for wind energy application

10.5194/amt-2020-511 ◽

2021 ◽

Author(s):

Etienne Cheynet ◽

Martin Flügge ◽

Joachim Reuder ◽

Jasna B. Jakobsen ◽

Yngve Heggelund ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Surface Layer ◽

Atmospheric Boundary Layer ◽

Wind Turbines ◽

Microwave Radiometer ◽

Wind Load ◽

Offshore Wind ◽

Offshore Wind Turbines ◽

Sensing Technology

Abstract. The paper presents the measurement strategy and dataset collected during the COTUR (COherence of TURbulence with lidars) campaign. This field experiment took place from February 2019 to April 2020 on the southwestern coast of Norway. The coherence quantifies the spatial correlation of eddies and is little known in the marine atmospheric boundary layer. The study was motivated by the need to better characterize the lateral coherence, which partly governs the dynamic wind load on multi-megawatt offshore wind turbines. During the COTUR campaign, the coherence was studied using land-based remote sensing technology. The instrument setup consisted of three long-range scanning Doppler wind lidars, one Doppler wind lidar profiler and one passive microwave radiometer. Both the WindScanner software and Lidar Planner software were used jointly to simultaneously orient the three scanner heads into the mean wind direction, which was provided by the lidar wind profiler. The radiometer instrument complemented these measurements by providing temperature and humidity profiles in the atmospheric boundary layer. The preliminary results show an undocumented variation of the lateral coherence with the distance from the coast. The scanning beams were pointed slightly upwards to record turbulence characteristics both within and above the surface layer, providing further insight on the applicability of surface-layer scaling to model the turbulent wind load on offshore wind turbines.

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Assimilation of Surface-Based Boundary Layer Profiler Observations during a Cool-Season Weather Event Using an Observing System Simulation Experiment. Part II: Forecast Assessment

Monthly Weather Review ◽

10.1175/2011mwr3623.1 ◽

2011 ◽

Vol 139 (8) ◽

pp. 2327-2346 ◽

Cited By ~ 19

Author(s):

Daniel C. Hartung ◽

Jason A. Otkin ◽

Ralph A. Petersen ◽

David D. Turner ◽

Wayne F. Feltz

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Microwave Radiometer ◽

Moisture Flux ◽

Ensemble Forecasts ◽

Thermodynamic Structure ◽

Critical Success ◽

Object Based ◽

Remote Sensing Systems ◽

Wind Profiles

AbstractIn this study, atmospheric analyses obtained through assimilation of temperature, water vapor, and wind profiles from a potential network of ground-based remote sensing boundary layer profiling instruments were used to generate short-range ensemble forecasts for each assimilation experiment performed in Part I. Remote sensing systems evaluated during this study include the Doppler wind lidar (DWL), Raman lidar (RAM), microwave radiometer (MWR), and the Atmospheric Emitted Radiance Interferometer (AERI). Overall, the results show that the most accurate forecasts were achieved when mass (temperature and humidity profiles from the RAM, MWR, and/or AERI) and momentum (wind profiles from the DWL) observations were assimilated simultaneously, which is consistent with the main conclusion from Part I. For instance, the improved wind and moisture analyses obtained through assimilation of these observations contributed to more accurate forecasts of moisture flux convergence and the intensity and location of accumulated precipitation (ACPC) due to improved dynamical forcing and mesoscale boundary layer thermodynamic structure. An object-based verification tool was also used to assess the skill of the ACPC forecasts. Overall, total interest values for ACPC matched objects, along with traditional forecast skill statistics like the equitable threat score and critical success index, were most improved in the multisensor assimilation cases.

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Atmospheric boundary layer parameters retrieval from Stepped Frequency Microwave Radiometer measurements in tropical cyclones

10.5194/egusphere-egu2020-9379 ◽

2020 ◽

Author(s):

Nikita Rusakov ◽

Evgeny Poplavsky ◽

Olga Ermakova ◽

Yuliya Troitskaya ◽

Daniil Sergeev ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Atmospheric Boundary Layer ◽

Microwave Radiometer ◽

Remote Sensing Data ◽

Field Measurements ◽

Radar Signal ◽

Time And Space ◽

Sensing Data ◽

Radar Images

Active microwave sensing using satellite instruments has great advantages, since in this range the absorption by clouds and atmospheric gases is noticeably reduced, it allows for round-the-clock and all-weather monitoring of the ocean. One of the main problems is concerned with obtaining the dependency between the RCS of radar signal scattered by the wavy water surface and the parameters of the atmospheric boundary layer in hurricane conditions. To obtain this dependence, we used field measurements of wind speed in a hurricane from falling NOAA GPS-sondes and SAR images from the Sentinel-1 satellite. However, there is the problem of correct collocation of remote sensing data with field measurements of the atmospheric boundary layer parameters, since they are separated in time and space. In this regard, the amount of data suitable for analysis is very limited, which forces us to look for new data sources for processing. A six-channel SFMR radiometer is also installed on board of NOAA research aircraft that measures the emissivity of the ocean surface beneath the aircraft. Thus, it becomes possible to relate the radiometric measurements of SFMR with the parameters of the atmospheric boundary layer in a tropical cyclone obtained from wind velocity profiles, since they are carried out as close as possible in time and space. Using this relation, the SFMR data and the hurricane radar images were analyzed together and an alternative method was found for constructing the dependence of the RCS on the parameters of the boundary layer.This work was supported by the RFBR projects No. 19-05-00249, 19-05-00366, 18-35-20068 (remote sensing data analysis) and RSF No. 19-17-00209 (GPS-sondes data assimilation and processing).&#160;

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