scholarly journals A unified data set of airborne cloud remote sensing using the HALO Microwave Package (HAMP)

2018 ◽  
Author(s):  
Heike Konow ◽  
Marek Jacob ◽  
Felix Ament ◽  
Susanne Crewell ◽  
Florian Ewald ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Microwave Remote Sensing ◽  
Joint Analysis ◽  
Wet Season ◽  
Data Set ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Wide Range ◽  
Research Aircraft ◽  
Microwave Radiometers

Abstract. Cloud properties and their environmental conditions were observed during four aircraft campaigns over the North Atlantic on 37 flights. The Halo Microwave Package (HAMP) was deployed on the German research aircraft HALO (High Altitude LOng range research aircraft) during these four campaigns. HAMP comprises microwave radiometers with 26 channels in the frequency range between 20 and 183 GHz and a 35 GHz cloud radar. The four campaigns took place between December 2013 and October 2016 out of Barbados and Iceland. Measured situations cover a wide range of conditions including the dry and wet season over the tropical Atlantic and the cold and warm sectors of mid-latitude cyclones. The data set we present here contains measurements of the radar reflectivity factor and linear depolarization ratio from cloud radar, brightness temperatures from microwave radiometers, and atmospheric profiles from dropsondes. It represents a unique combination of active and passive microwave remote sensing measurements and 525 in-situ measured dropsonde profiles. The data from these different instruments are quality controlled and unified into one common format for easy combination of data and joint analysis. The data are available from the CERA database for the four campaigns individually (https://doi.org/10.1594/WDCC/HALO_measurements_1, https://doi.org/10.1594/WDCC/HALO_measurements_2, https://doi.org/10.1594/WDCC/HALO_measurements_3, https://doi.org/10.1594/WDCC/HALO_measurements_4). This data set allows for analyses to get insight into cloud properties and atmospheric state in remote regions over the tropical and mid-latitude Atlantic. In this paper, we describe the four campaigns, the data, and the quality control applied to the data.

scholarly journals A unified data set of airborne cloud remote sensing using the HALO Microwave Package (HAMP)

2019 ◽  
Vol 11 (2) ◽  
pp. 921-934 ◽  
Author(s):  
Heike Konow ◽  
Marek Jacob ◽  
Felix Ament ◽  
Susanne Crewell ◽  
Florian Ewald ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Microwave Remote Sensing ◽  
Joint Analysis ◽  
Wet Season ◽  
Data Set ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Wide Range ◽  
Research Aircraft ◽  
Microwave Radiometers

Abstract. Cloud properties and their environmental conditions were observed during four aircraft campaigns over the North Atlantic on 37 flights. The Halo Microwave Package (HAMP) was deployed on the German research aircraft HALO (High Altitude Long Range Research Aircraft) during these four campaigns. HAMP comprises microwave radiometers with 26 channels in the frequency range between 20 and 183 GHz and a 35 GHz cloud radar. The four campaigns took place between December 2013 and October 2016 out of Barbados and Iceland. Measured situations cover a wide range of conditions including the dry and wet season over the tropical Atlantic and the cold and warm sectors of midlatitude cyclones. The data set we present here contains measurements of the radar reflectivity factor and linear depolarization ratio from cloud radar, brightness temperatures from microwave radiometers and atmospheric profiles from dropsondes. It represents a unique combination of active and passive microwave remote sensing measurements and 525 in situ-measured dropsonde profiles. The data from these different instruments are quality controlled and unified into one common format for easy combination of data and joint analysis. The data are available from the CERA database for the four campaigns individually (https://doi.org/10.1594/WDCC/HALO_measurements_1, https://doi.org/10.1594/WDCC/HALO_measurements_2, https://doi.org/10.1594/WDCC/HALO_measurements_3, https://doi.org/10.1594/WDCC/HALO_measurements_4). This data set allows for analyses to gain insight into cloud properties and the atmospheric state in remote regions over the tropical and midlatitude Atlantic. In this paper, we describe the four campaigns, the data and the quality control applied to the data.

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

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.

scholarly journals Improvement of airborne retrievals of cloud droplet number concentration of trade wind cumulus using a synergetic approach

2019 ◽  
Vol 12 (3) ◽  
pp. 1635-1658 ◽  
Author(s):  
Kevin Wolf ◽  
André Ehrlich ◽  
Marek Jacob ◽  
Susanne Crewell ◽  
Martin Wirth ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Cloud Base ◽  
Trade Wind ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Research Aircraft ◽  
Cloud Droplet Number Concentration

Abstract. In situ measurements of cloud droplet number concentration N are limited by the sampled cloud volume. Satellite retrievals of N suffer from inherent uncertainties, spatial averaging, and retrieval problems arising from the commonly assumed strictly adiabatic vertical profiles of cloud properties. To improve retrievals of N it is suggested in this paper to use a synergetic combination of passive and active airborne remote sensing measurement, to reduce the uncertainty of N retrievals, and to bridge the gap between in situ cloud sampling and global averaging. For this purpose, spectral solar radiation measurements above shallow trade wind cumulus were combined with passive microwave and active radar and lidar observations carried out during the second Next Generation Remote Sensing for Validation Studies (NARVAL-II) campaign with the High Altitude and Long Range Research Aircraft (HALO) in August 2016. The common technique to retrieve N is refined by including combined measurements and retrievals of cloud optical thickness τ, liquid water path (LWP), cloud droplet effective radius reff, and cloud base and top altitude. Three approaches are tested and applied to synthetic measurements and two cloud scenarios observed during NARVAL-II. Using the new combined retrieval technique, errors in N due to the adiabatic assumption have been reduced significantly.

Cloud macrophysical properties from airborne observations during EUREC4A

2020 ◽  
Author(s):  
Heike Konow ◽  
Marcus Klingebiel ◽  
Felix Ament
Keyword(s):  
Deep Convection ◽  
Dry Season ◽  
Trade Wind ◽  
Special Focus ◽  
Wet Season ◽  
Diurnal Cycles ◽  
Cloud Radar ◽  
Wide Range ◽  
Macrophysical Properties ◽  
Different Response

<p><span>Trade wind cumulus clouds are the predominant cloud type over the tropical Atlantic east of the island of Barbados. Parameters describing their macroscopic shape can help characterizing and comparing general features of clouds. This characterizing will indirectly help to constrain estimates of climate sensitivity, because models with different structures of trade wind cumuli feature different response to increased CO2 contents.</span></p><p><span>Two aircraft campaigns with the HALO (High Altitude LOng range) aircraft took place in the recent past in this region: NARVAL-South (Next-generation Aircraft Remote-Sensing for VALidation studies) in December 2013, during the dry season, and NARVAL2 in August 2016, during the wet season. During these two campaigns, a wide range of cloud regimes from shallow to deep convection were sampled. This past observations are now extended with observations from this year’s measurement campaign EUREC<sup>4</sup>A, again during the dry season. EUREC<sup>4</sup>A is endorsed as WCRP capstone experiment and the synergy of four research aircraft, four research vessels and numerous additional observations will provide comprehensive characterizations of trade wind clouds and their environment.</span></p><p><span>Part of the NARVAL payload on HALO is a 35 GHz cloud radar, which has been deployed on HALO on several missions since 2013. These cloud radar measurements are used to segment individual clouds entities by applying connected component analysis to the radar cloud mask. From these segmented individual clouds, macrophysical parameters are derived to characterize each individual cloud. </span></p><p><span>This presentation will give an overview of the cloud macrophysics observed from HALO during EUREC<sup>4</sup>A. Typical macrophysical parameters, i.e. cloud depth, cloud length, cloud fraction, are analyzed. We will relate these to observations from past campaigns and assess the representativeness of EUREC<sup>4</sup>A. As special focus of the EUREC<sup>4</sup>A campaign, measurements will be performed during different times of the day to detect diurnal cycles. Macrophysical parameters can be used to characterize changes over the day and cloud scenes of similar clouds types can be identified.</span></p>

Interpreting Vegetation Optical Depth (VOD) using detailed destructive vegetation sampling of a corn canopy

2020 ◽  
Author(s):  
Saeed Khabbazan ◽  
Ge Gao ◽  
Paul Vermunt ◽  
Susan Steele-Dunne ◽  
Jasmeet Judge ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Vertical Distribution ◽  
Water Content ◽  
Optical Depth ◽  
Microwave Remote Sensing ◽  
Growing Season ◽  
Vegetation Water Content ◽  
Wide Range ◽  
Vegetation Water

<p>Vegetation Optical Depth (VOD) is directly related to Vegetation Water Content (VWC), which can be used in different applications including crop health monitoring, water resources management and drought detection. Moreover, VOD is used to account for the attenuating effect of vegetation in soil moisture retrieval using microwave remote sensing.</p><p>Commonly, to retrieve soil moisture and VOD from microwave remote sensing, VWC is considered to be vertically homogeneous and relatively static.  However, nonuniform vertical distribution of water inside the vegetation may lead to unrealistic retrievals in agricultural areas. Therefore, it is important to improve the understanding of the relation between vegetation optical depth and distribution of bulk vegetation water content during the entire growing season.</p><p>The goal of this study is to investigate the effect of different factors such as phenological stage, different crop elements and nonuniform distribution of internal vegetation water content on VOD. Backscatter data were collected every 15 minutes using a tower-based, fully polarimetric, L-band radar. The methodology of Vreugdenhil et al. [1] was adapted to estimate VOD from single-incidence angle backscatter data in each polarization.</p><p>In order to characterize the vertical distribution of VWC, pre-dawn destructive sampling was conducted three times a week for a full growing season. VWC could therefore be analyzed by constituent (leaf, stem, ear) or by height.</p><p>A temporal correlation analysis showed that the relation between VOD and VWC during the growing season is not constant. The assumed linear relationship is only valid during the vegetative growth stages for corn.  Furthermore, the sensitivity of VOD to various plant components (leaf, stem and ear) varies between phenological stages and depends on polarization.</p><p>Improved understanding of VOD can contribute to improved consideration of vegetation in soil moisture retrieval algorithms. More importantly, it is essential for the interpretation of VOD data in a wide range of vegetation monitoring applications.</p><p>[1] M. Vreugdenhil,W. A. Dorigo,W.Wagner, R. A. De Jeu, S. Hahn, andM. J. VanMarle, “Analyzing the vegetation parameterization in the TU-Wien ASCAT soil moisture retrieval,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 6, pp. 3513–3531, 2016.</p>

scholarly journals Development of a Parameterized Model to Estimate Microwave Radiation Response Depth of Frozen Soil

2019 ◽  
Vol 11 (17) ◽  
pp. 2028 ◽  
Author(s):  
Zhang ◽  
Jiang ◽  
Zhao ◽  
Chai ◽  
Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sensitivity Analysis ◽  
Microwave Radiation ◽  
Microwave Remote Sensing ◽  
Frozen Soil ◽  
Passive Microwave ◽  
Radiation Response ◽  
Passive Microwave Remote Sensing ◽  
Wide Range ◽  
Parameterized Model

The sensing depth of passive microwave remote sensing is a significant factor in quantitative frozen soil studies. In this paper, a microwave radiation response depth (MRRD) was proposed to describe the source of the main signals of passive microwave remote sensing. The main goal of this research was to develop a simple and accurate parameterized model for estimating the MRRD of frozen soil. A theoretical model was introduced first to describe the emission characteristics of a three-layer case, which incorporates multiple reflections at the two boundaries. Based on radiative transfer theory, the total emission of the three layers was calculated. A sensitivity analysis was then performed to demonstrate the effects of soil properties and frequency on the MRRD based on a simulation database comprising a wide range of soil characteristics and frequencies. Sensitivity analysis indicated that soil temperature, soil texture, and frequencies are three of the primary variables affecting MRRD, and a definite empirical relationship existed between the three parameters and the MRRD. Thus, a parameterized model for estimating MRRD was developed based on the sensitivity analysis results. A controlled field experiment using a truck-mounted multi-frequency microwave radiometer (TMMR) was designed and performed to validate the emission model of the soil freeze–thaw cycle and the parameterized model of MRRD developed in this work. The results indicated that the developed parameterized model offers a relatively accurate and simple way of estimating the MRRD. The total root mean square error (RMSE) between the calculated and measured MRRD of frozen loam soil was approximately 0.5 cm for the TMMR’s four frequencies.

scholarly journals Development and Evaluation of a Multi-Year Fractional Surface Water Data Set Derived from Active/Passive Microwave Remote Sensing Data

2015 ◽  
Vol 7 (12) ◽  
pp. 16688-16732 ◽  
Author(s):  
Ronny Schroeder ◽  
Kyle McDonald ◽  
Bruce Chapman ◽  
Katherine Jensen ◽  
Erika Podest ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Water ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Data Set ◽  
Passive Microwave Remote Sensing ◽  
Sensing Data ◽  
Fractional Surface

scholarly journals Cloud<i>_</i>cci ATSR-2 and AATSR data set version 3: a 17-year climatology of global cloud and radiation properties

2020 ◽  
Vol 12 (3) ◽  
pp. 2121-2135
Author(s):  
Caroline A. Poulsen ◽  
Gregory R. McGarragh ◽  
Gareth E. Thomas ◽  
Martin Stengel ◽  
Matthew W. Christensen ◽  
...  
Keyword(s):  
Liquid Water ◽  
European Space Agency ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Data Set ◽  
Water Path ◽  
Cloud Properties ◽  
Wide Range ◽  
Good Agreement

Abstract. We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

Joint analysis of remotely sensed soil moisture and water storage variations from satellite gravimetry

2021 ◽  
Author(s):  
Daniel Blank ◽  
Annette Eicker ◽  
Laura Jensen ◽  
Andreas Güntner
Keyword(s):  
Soil Moisture ◽  
Water Storage ◽  
Microwave Remote Sensing ◽  
Time Shift ◽  
Joint Analysis ◽  
Data Sets ◽  
Time Lags ◽  
Data Set ◽  
Satellite Gravimetry ◽  
Storage Change

&lt;p&gt;Information on water storage changes in the soil can be obtained on a global scale from different types of satellite observations. While active or passive microwave remote sensing is limited to investigating the upper few centimeters of the soil, satellite gravimetry is sensitive to variations in the full column of terrestrial water storage (TWS) but cannot distinguish between storage variations occurring in different soil depths. Jointly analyzing both data types promises interesting insights into the underlying hydrological dynamics and may enable a better process understanding of water storage change in the subsurface.&lt;/p&gt;&lt;p&gt;In this study, we aim at investigating the global relationship of (1) several satellite soil moisture (SM) products and (2) non-standard daily TWS data from the GRACE and GRACE-FO satellite gravimetry missions on different time scales. We decompose the data sets into different temporal frequencies from seasonal to sub-monthly signals and carry out the comparison with respect to spatial patterns and temporal variability. Level-3 (Surface SM up to 5 cm depth) and Level-4 (Root-Zone SM up to 1 m depth) data sets of the SMOS and SMAP missions as well as the ESA CCI data set are used in this investigation.&lt;br&gt;Since a direct comparison of the absolute values is not possible due to the different integration depths of the two data sets (SM and TWS), we will analyze their relationship using Pearson&amp;#8217;s pairwise correlation coefficient. Furthermore, a time-shift analysis is carried out by means of cross-correlation to identify time lags between SM and TWS data sets that indicate differences in the temporal dynamics of SM storage change in varying depth layers.&lt;/p&gt;

scholarly journals The backscatter cloud probe – a compact low-profile autonomous optical spectrometer

2014 ◽  
Vol 7 (5) ◽  
pp. 1443-1457 ◽  
Author(s):  
K. Beswick ◽  
D. Baumgardner ◽  
M. Gallagher ◽  
A. Volz-Thomas ◽  
P. Nedelec ◽  
...  
Keyword(s):  
Climate Models ◽  
Equivalent Diameter ◽  
The European Union ◽  
Data Quality Control ◽  
Cloud Particle ◽  
Cloud Data ◽  
Airborne Measurements ◽  
Cloud Properties ◽  
Wide Range ◽  
Research Aircraft

Abstract. A compact (500 cm3), lightweight (500 g), near-field, single particle backscattering optical spectrometer is described that mounts flush with the skin of an aircraft and measures the concentration and optical equivalent diameter of particles from 5 to 75 μm. The backscatter cloud probe (BCP) was designed as a real-time qualitative cloud detector primarily for data quality control of trace gas instruments developed for the climate monitoring instrument packages that are being installed on commercial passenger aircraft as part of the European Union In-Service Aircraft for a Global Observing System (IAGOS) program (http://www.iagos.org/). Subsequent evaluations of the BCP measurements on a number of research aircraft, however, have revealed it capable of delivering quantitative particle data products including size distributions, liquid-water content and other information on cloud properties. We demonstrate the instrument's capability for delivering useful long-term climatological, as well as aviation performance information, across a wide range of environmental conditions. The BCP has been evaluated by comparing its measurements with those from other cloud particle spectrometers on research aircraft and several BCPs are currently flying on commercial A340/A330 Airbus passenger airliners. The design and calibration of the BCP is described in this article, along with an evaluation of measurements made on the research and commercial aircraft. Preliminary results from more than 7000 h of airborne measurements by the BCP on two Airbus A340s operating on routine global traffic routes (one Lufthansa, the other China Airlines) show that more than 340 h of cloud data have been recorded at normal cruise altitudes (> 10 km) and more than 40% of the > 1200 flights were through clouds at some point between takeoff and landing. These data are a valuable contribution to databases of cloud properties, including sub-visible cirrus, in the upper troposphere and useful for validating satellite retrievals of cloud water and effective radius; in addition, providing a broader, geographically and climatologically relevant view of cloud microphysical variability that is useful for improving parameterizations of clouds in climate models. Moreover, they are also useful for monitoring the vertical climatology of clouds over airports, especially those over megacities where pollution emissions may be impacting local and regional climate.

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