Active Microwave Research Articles

A Satellite-Observed Substantial Decrease in Multiyear Ice Area Export through the Fram Strait over the Last Decade

Revealing the changes in the Fram Strait (FS) multiyear ice (MYI) export is crucial due to their climate relevance in the context of the loss rate of MYI being faster than that of the total ice in the Arctic. Here, we estimated winter (October–April) MYI area export through the FS over the last 2 decades by using updated MYI concentration data retrieved from active and passive microwave satellite observations. We divided the period into two regimes relative to the ice index: D1 (2002/03–2010/11) and D2 (2012/13–2019/20). The observed variations of winter MYI exports D2 were compared with those of the previous decade D1. The results show that the MYI area exports display strong interannual variability. A significant decrease in MYI export for the periods between D1 and D2 is noted. On average, the wintertime MYI area exports declined sharply by 22% from 3.82 × 105 km2 in D1 to 3.00 × 105 km2 in D2. In addition, the percentage of MYI in the total sea ice outflow through the FS (PCM) also decreased distinctly from 72% in D1 to 59% in D2. Statistics show that weekly sea ice drift across the strait can explain 76% of the MYI area export variability. Furthermore, the dominant atmospheric drivers contributing to the decline in MYI area export during D2 were examined. In the last decade (D2), the strengthened low pressure in the North Atlantic sector, combined with an eastward shift in the axis of dipole anomaly (DA), resulted in reduced MYI advection from the Beaufort Sea and Siberian Coast toward the FS. Moreover, weakened cyclonic activity south of the FS also contributed to the reduction in MYI export during D2.

Remote Sensing of Surface Water Dynamics in the Context of Global Change—A Review

Inland surface water is often the most accessible freshwater source. As opposed to groundwater, surface water is replenished in a comparatively quick cycle, which makes this vital resource—if not overexploited—sustainable. From a global perspective, freshwater is plentiful. Still, depending on the region, surface water availability is severely limited. Additionally, climate change and human interventions act as large-scale drivers and cause dramatic changes in established surface water dynamics. Actions have to be taken to secure sustainable water availability and usage. This requires informed decision making based on reliable environmental data. Monitoring inland surface water dynamics is therefore more important than ever. Remote sensing is able to delineate surface water in a number of ways by using optical as well as active and passive microwave sensors. In this review, we look at the proceedings within this discipline by reviewing 233 scientific works. We provide an extensive overview of used sensors, the spatial and temporal resolution of studies, their thematic foci, and their spatial distribution. We observe that a wide array of available sensors and datasets, along with increasing computing capacities, have shaped the field over the last years. Multiple global analysis-ready products are available for investigating surface water area dynamics, but so far none offer high spatial and temporal resolution.

Year-round sea ice and snow characterization from combined passive and active microwave observations and radiative transfer modeling

Satellite microwave observations from 1.4 to 36 GHz already showed sensitivity to several geophysical parameters of sea ice such as Sea Ice Concentration (SIC), Sea Ice Thickness (SIT) or snow depth. The main goal of this article is to provide a realistic and comprehensive characterization of the sea ice and its snow cover that explains the microwave observations during a whole year using a radiative transfer model. For this purpose, we construct a unique dataset of passive microwave observations, to mimic the future Copernicus Imaging Microwave Radiometer (CIMR), along with the active microwave scatterometer data (ASCAT). CIMR database is used to classify sea ice microwave signatures in their spectral dimension with a machine learning technique while ASCAT data are used to help interpret the results of the classification. Classification results are then interpreted with a state-of-art sea ice and Snow Microwave Radiative Transfer model (SMRT) for all highlighted signatures and all seasons. Results make it possible to identify the specific behaviors from the observation co-variabilities for SIC, SIT, and snow structure. Our analysis underlined the role of the depth hoar over multi-year ice, for the interpretation of scattering signals in winter. Scattering signals that appear in late summer are explained by the presence of superimposed ice. This characterization will benefit from future advances in SMRT development, as well as the improved observations of future satellite missions.

Remote sensing of phenology: Towards the comprehensive indicators of plant community dynamics from species to regional scales

Abstract Remote sensing of vegetation phenology has long been used to characterize ecosystem functions and responses to climate at spatial and temporal scales unfeasible to field surveys. However, the potential of remote sensing to elucidate mechanistic drivers of phenology and the underlying plant community processes at such scales remains under‐discussed. This review synthesizes possibilities to advance this knowledge using multi‐temporal remote sensing and discusses remaining challenges and progress in instruments and analytical tools. Recent evidence indicates that, besides documenting vegetation seasonality and responses to climate, remote sensing of phenology can help meet emerging needs for indicators of plant diversity, vegetation structure and ecosystem change. Responses of phenological metrics to stressors over large, heterogeneous regions may provide clues on ecological resilience manifested in asynchronies, recovery of vegetation cycles and stable microrefugia. At the same time, important barriers persist in relation to choosing among phenological estimation methods and paradigms, characterizing phenological events beyond changes in photosynthetically active biomass, and mechanistic interpretation of phenological patterns. Synthesis. Increasing temporal frequency of products, opportunities for multi‐sensor data fusion, and advances in historically less available hyperspectral, active microwave and lidar instruments promise to help navigate these barriers and enable more comprehensive assessments of seasonality. Progress in customizable local platforms such as unoccupied aerial vehicles and phenocams may further enrich ground‐level understanding of phenology and validate satellite‐based assessments. However, remote sensing analyses alone are insufficient for mechanistic interpretation of phenology, which can be challenged by artefacts in remote sensing data and sensitivity of estimated metrics to landscape structure and spatial resolution of the inputs. Robust and informative phenological assessments call for rigorous collaborations with field ecological studies, strategic selection of ancillary environmental and geographic data, and wider adoption of causal inference approaches to address these needs and support novel explorations in plant ecology.

SAR Image Fusion Classification Based on the Decision-Level Combination of Multi-Band Information

Synthetic aperture radar (SAR) is an active coherent microwave remote sensing system. SAR systems working in different bands have different imaging results for the same area, resulting in different advantages and limitations for SAR image classification. Therefore, to synthesize the classification information of SAR images into different bands, an SAR image fusion classification method based on the decision-level combination of multi-band information is proposed in this paper. Within the proposed method, the idea of Dempster–Shafer evidence theory is introduced to model the uncertainty of the classification result of each pixel and used to combine the classification results of multiple band SAR images. The convolutional neural network is used to classify single-band SAR images. Calculate the belief entropy of each pixel to measure the uncertainty of single-band classification, and generate the basic probability assignment function. The idea of the term frequency-inverse document frequency in natural language processing is combined with the conflict coefficient to obtain the weight of different bands. Meanwhile, the neighborhood classification of each pixel in different band sensors is considered to obtain the total weight of each band sensor, generate weighted average BPA, and obtain the final ground object classification result after fusion. The validity of the proposed method is verified in two groups of multi-band SAR image classification experiments, and the proposed method has effectively improved the accuracy compared to the modified average approach.

An Active and Low-cost Microwave Imaging System for Detection of Breast Cancer Using Back Scattered Signal.

A defected ground antenna with dielectric reflector is designed and investigated for breast tumour diagnosis. Ultra-wide band resonance (3.1 to 10.6 GHz) is achieved by etching two slots and adding a narrow vertical strip in a patch antenna. A high dielectric constant substrate is added below the antenna, which shows remarkable effect on performance. Antenna performance is verified experimentally on an artificially fabricated breast tissue and tumour. Malignant tissue has different dielectric properties than the normal tissue which causes deviation in the scattered antenna power. Average value of backscattered signal variation and ground penetrating radar (GPR) algorithm is used to localize the tumour of radius 4mm in breast tissue.

A novel design of a reconfigurable power divider with stubs for mobile applications

<p><span>Nowadays, the world knows a huge revolution in telecommunications, which has led to the need to integrate many services, such as long-term evolution (LTE), 5G, wireless local area network (WLAN), and Bluetooth, in one receiving and transmitting device. In the same way, all active and passive microwave circuits must be compatible with the integration of services, including the power divider, which is the subject of our work. This passive component is used in several fields such as medicine, surveillance, radar systems and others applications. Wilkinson divider is one of the most prominent power dividers, it is classified as narrow-band power divider and it is a very useful component in mobile applications (2.4 and 5.8 GHz). In this work, a reconfigurable 4-ports Wilkinson divider is designed using PIN diodes and simulated using connected speech test (CST) simulator software. This designed divider can easily modify the operation mode by activating or disabling the PIN diodes.</span></p>

Widespread occurrence of anomalous C-band backscatter signals in arid environments caused by subsurface scattering

Backscatter measured by scatterometers and Synthetic Aperture Radars is sensitive to the dielectric properties of the soil and normally increases with increasing soil moisture content. However, when the soil is dry, the radar waves penetrate deeper into the soil, potentially sensing subsurface scatterers such as near-surface rocks and stones. In this paper we propose an exponential model to describe the impact of such subsurface scatterers on C-Band backscatter measurements acquired by the Advanced Scatterometer (ASCAT) on board of the METOP satellites. The model predicts an increase of the subsurface scattering contributions with decreasing soil wetness that may counteract the signal from the soil surface. This may cause anomalous backscatter signals that deteriorate soil moisture retrievals from ASCAT. We test whether this new model is able to explain ASCAT observations better than a bare soil backscatter model without a subsurface scattering term, using k-fold cross validation and the Bayesian Information Criterion for model selection. We find that arid landscapes with Leptosols and Arenosols represent ideal environmental conditions for the occurrence of subsurface scattering. Nonetheless, subsurface scattering may also become important in more humid environments during dry spells. We conclude that subsurface scattering is a widespread phenomenon that (i) needs to be accounted for in active microwave soil moisture retrievals and (ii) has a potential for soil mapping, particularly in arid and semi-arid environments.

A Lightweight Position-Enhanced Anchor-Free Algorithm for SAR Ship Detection

As an active microwave device, synthetic aperture radar (SAR) uses the backscatter of objects for imaging. SAR image ship targets are characterized by unclear contour information, a complex background and strong scattering. Existing deep learning detection algorithms derived from anchor-based methods mostly rely on expert experience to set a series of hyperparameters, and it is difficult to characterize the unique characteristics of SAR image ship targets, which greatly limits detection accuracy and speed. Therefore, this paper proposes a new lightweight position-enhanced anchor-free SAR ship detection algorithm called LPEDet. First, to resolve unclear SAR target contours and multiscale performance problems, we used YOLOX as the benchmark framework and redesigned the lightweight multiscale backbone, called NLCNet, which balances detection speed and accuracy. Second, for the strong scattering characteristics of the SAR target, we designed a new position-enhanced attention strategy, which suppresses background clutter by adding position information to the channel attention that highlights the target information to more accurately identify and locate the target. The experimental results for two large-scale SAR target detection datasets, SSDD and HRSID, show that our method achieves a higher detection accuracy and a faster detection speed than state-of-the-art SAR target detection methods.

GPM-CO observations of Medicane Ianos: Comparative analysis of precipitation structure between development and mature phase

The present work exploits the satellite measurements from the NASA/JAXA Global Precipitation Measurement Core Observatory (GPM-CO) active and passive microwave sensors to analyze the precipitation structure of the most intense Mediterranean Hurricane (Medicane) on record, named Ianos, which swept across the Ionian Sea between 14 and 18 September 2020. Two GPM-CO overpasses, available during Ianos development and tropical-like cyclone (mature) phase, are analyzed in detail. GPM Microwave Imager measurements are used to carry out a comparative analysis of the medicane precipitation structure and microphysics processes between the two phases. The GPM-CO Dual-frequency Precipitation Radar overpass, available for the first time during a medicane mature phase, provides key measurements and products to analyze the 3D precipitation structure in the rainbands, offering further evidence of the main precipitation microphysics processes inferred from the passive microwave measurement analysis. Substantial difference in the rainband precipitation structure is observed, with deeper convection and stronger updraft features during development than at the mature phase, when also shallow precipitation/warm rain processes are observed in the inner region around the medicane eye. These features play a key role to explain the substantial drop in lightning activity during Ianos mature phase. Graupel-ice electrification process is inhibited due to the combined effect of strong horizontal wind and the observed limited growth of graupel. The study demonstrates the value of the GPM-CO not only to characterize Medicane Ianos precipitation structure and microphysics processes with unprecedented detail, but also to provide evidence of its exceptional intensity, tropical-like characteristics during its mature phase, and its similarities with tropical cyclones.

Multi-Scale Assessment of SMAP Level 3 and Level 4 Soil Moisture Products over the Soil Moisture Network within the ShanDian River (SMN-SDR) Basin, China

The Soil Moisture Active Passive (SMAP) mission with high-precision soil moisture (SM) retrieval products provides global daily composites of SM at 3, 9, and 36 km earth grids measured by L-band active and passive microwave sensors. The capability of passive microwave remote sensing has been recognized for the estimation of SM variations. The purpose of this work was to establish an interaction between the highly variable SM spatial distribution on the ground and the SMAP’s coarse resolution radiometer-based SM retrievals. In this work, SMAP Level 3 (L3) and Level 4 (L4) SM products are validated with in situ datasets observed from the different locations of the Soil Moisture Network within the ShanDian River (SMN-SDR) Basin over the period of January 2018 to December 2019. The values of the unbiased root mean square error (ubRMSE) for L3 (SPL3SMP_E) SM retrievals are close to the standard SMAP mission SM accuracy requirement of 0.04 m3/m3 at the 9-km scale, with an averaged ubRMSE value of 0.041 m3/m3 (0.050 m3/m3) for descending (ascending) SM with the correlation (R) values of 0.62 (0.42) against the sparse network sites. The L4 (SPL4SMGP) Surface and Root-zone SM (RZSM) estimates show less error (ubRMSE < 0.04) and high correlation (R > 0.60) values, and are consistent with the previous SMAP-based SM estimations. The SMAP L4 SM products (SPL4SMGP) performed well compared to the L3 SM retrieval products (SPL3SMP_E). In vegetated land, the variability and compatibility of the SMAP SM estimates with the evaluation metrics for both products (L3 and L4) showed a good performance in the grassland, then in the farmland, and worst in the woodlands. Finally, SMAP algorithm parameters sensitivity analysis of the satellite products was conducted to produce time-series and highly precise SM datasets in China.

Retrieving Freeze/Thaw Cycles Using Sentinel-1 Data in Eastern Nunavik (Québec, Canada)

In the terrestrial cryosphere, freeze/thaw (FT) state transitions play an important and measurable role in climatic, hydrological, ecological, and biogeochemical processes in permafrost landscapes. Active and passive microwave remote sensing has shown a principal capacity to provide effective monitoring of landscape FT dynamics. The study presents a seasonal threshold approach, which examines the timeseries progression of remote sensing measurements relative to signatures acquired during seasonal frozen and thawed reference states. This is used to estimate the FT state from the Sentinel-1 database and applied and evaluated for the region of Eastern Nunavik (Québec, Canada). An optimization process of the threshold is included. In situ measurements from the meteorological station network were used for the validation process. Overall, acceptable estimation accuracy (>70%) was achieved in most tests; on the best-performing sites, an accuracy higher than 90% was reached. The performance of the seasonal threshold approach over the study region was further discussed with consideration of land cover, spatial heterogeneity, and soil depth. This work is dedicated to providing more accurate data to capture the spatiotemporal heterogeneity of freeze/thaw transitions and to improving our understanding of related processes in permafrost landscapes.

Arctic Sea Ice Type Classification by Combining CFOSCAT and AMSR‐2 Data

AbstractFirst‐year ice (FYI) and multi‐year ice (MYI) are the two most common ice types in the Arctic. In this article, the classification of FYI and MYI over the Arctic region in the winter of 2019/2020 and 2020/2021 is investigated by combining the data of the scatterometer on Chinese‐French Oceanography Satellite (CFOSCAT) and the Advanced Microwave Scanning Radiometer‐2 (AMSR‐2) based on the Tree Augmented Naive Bayes (TAN) classifier. The CFOSCAT/AMSR ice type classification results are validated by using Ocean and Sea Ice Satellite Application Facility (OSI SAF) sea ice type products, Canadian Ice Service ice charts, and synthetic‐aperture radar data. The results showed that the overall MYI extent change trend retrieved from CFOSCAT/AMSR was consistent with the OSI SAF product with a correlation coefficient of 0.89 for winter of 2019/2020 and 0.88 for 2020/2021. In addition, CFOSCAT/AMSR identified a slightly larger MYI extent than OSI SAF and the average deviation between them is 10.1% for 2019/2020 while 8.3% for 2020/2021. Besides, CFOSCAT/AMSR can identify more MYI pixels when the MYI concentration is relatively low in the Western Arctic region. We also used CFOSCAT data only to retrieve ice type and found that the active and passive microwave data fusion could capture more MYI pixels located near the boundary of MYI and FYI main body, and the introduction of AMSR‐2 data in ice type classification could reduce the error caused by the abnormal values of CFOSCAT parameters.

Design and Test of Innovative Three-Couplers-Based Bandpass Negative Group Delay Active Circuit

An innovative design method of bandpass (BP) negative group delay (NGD) active circuit is developed. The BP NGD topology consists originally of octopole and hexapole coupled line (CL) couplers. The NGD active circuit is validated by a prototype implemented in hybrid technology. The measured results are in good agreement with simulations. The CL-based passive circuit generates BP NGD performance with simulated and measured results showing NGD level of approximately -12 ns having 1.97 GHz center frequency with -11 dB transmission coefficient and -16 dB reflection coefficient. To compensate the loss, active circuit was fabricated by cascading the passive circuit with a microwave amplifier. Subsequently, the previous BP NGD performance is achieved with 0 dB gain. Moreover, a notable active microwave device characterization is performed with the NGD prototype via nonlinear measurements. It was found that the tested NGD prototype operates with 10-dB noise figure, 21 dBm P1dB compression, 29 dBm and 41 dBm OIP3.

Diurnal and Seasonal Variations of Passive and Active Microwave Satellite Observations Over Tropical Forests

AbstractDocumenting the large scale variability of tropical forest structure and function is needed for improved understanding of the carbon and water cycles. The seasonal and diurnal cycles of passive and active microwave satellite observations are jointly analyzed for the first time, using the Global Precipitation Mission (GPM). Collocated backscattering coefficients from the GPM Dual‐frequency Precipitation Radar (DPR) and emissivities derived from the GPM Microwave Imager (GMI) are studied for 4 yr over the Tropics, at the available multiple frequencies, angles, and polarizations. Our analysis confirms the diurnal patterns already observed with radars, with a maximum backscatter in the early morning attributed to the water xylem refill at night. At the same time, early in the morning, we evidence a minimum emissivity over most of tropical forests: the backscatter and emissivity diurnal cycles tend to be in phase opposition, as well as their seasonal cycles. However, during the dry season in the south eastern Amazonian forest where precipitation can be low for several months, the emissivity diurnal cycle changes, implying a different behavior of the forest in this area, related to the state of the canopy.

Relationship Between Active and Passive Microwave Signals Over Vegetated Surfaces

The NASA Soil Moisture Active Passive (SMAP) satellite mission aims to produce enhanced resolution surface soil moisture products by combining coincident but multiresolution L-band active and passive microwave measurements. Since the SMAP radar ceased operations early in the mission, Copernicus Sentinel-1 C-band radar observations are used in the combined product. The synergy is built on two basic foundations: first, active and passive signals covary in a known and systematic fashion, and second, measurements are available at multiple resolutions. In this study, we perform numerical simulations and assess global satellite observations to test the first foundation (covariation). Specific focus lies on the role of the vegetation canopy in modulating the active–passive relationship. We use a discrete radiative transfer model to simulate the slope <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> and coefficient of determination <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> of the relationship between active and passive signals, considering three vegetation types for which the model has been extensively assessed in previous experimental studies. We find that a linear relationship between backscatter and emissivity can be established over a range of vegetation conditions. The coupling between active and passive signals decreases with increasing vegetation water content, such that moderate or higher correlations (nonzero slopes) are retained up to 4 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (6.3 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) for L-band/L-band and 1.5 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (2 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) for the C-band/L-band configuration. We decompose the effects of different soil-vegetation scattering mechanisms, such as double-bounce, and different measurement error levels on the active–passive relationship. Comparisons with satellite data confirm that our simulations capture magnitudes and major trends found across global vegetated land masses.

High-Resolution, Sensitivity-Enhanced Active Resonator Sensor Using Substrate-Embedded Channel for Characterizing Low-Concentration Liquid Mixtures

Sensitivity and resolution are important parameters that pose a significant challenge in using microwave microfluidic sensors to monitor low-concentration binary liquid mixtures. This work presents a microwave split-ring resonator (SRR) sensor equipped with a substrate-embedded fluidic channel and an active feedback loop to enhance sensitivity and resolution, respectively. The substrate-embedded channel eliminated the impact of the liquid-carrying tubes’ wall and maintained a significant interaction between the liquid in the channel and the electromagnetic (EM) field confined between the SRR and ground plane. Therefore, embedding the channel inside the substrate of the SRR sensor, operating at 2.63 GHz, enhanced the sensitivity by 60%. The constructive energy from the active feedback loop boosted the quality factor of the passive SRR by over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$100\times $ </tex-math></inline-formula> (from 116 to 13 000), which significantly enhanced the resolution of the sensor. As a proof of concept, two prototypes of the sensor having different substrate-embedded channels with cross-sectional diameters of 1 and 0.762 mm were fabricated and used to detect low concentrations of ethanol (0–0.08 vol%) and salt (0–200 mM) in water. Embedding the channel inside the substrate of the active SRR sensor achieved a linear correlation ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2} = 0.99$ </tex-math></inline-formula> ) between the resonant frequency and the concentration of ethanol and salt in water with high sensitivity (19.95 MHz/vol% for ethanol and 4.35 kHz/mM for salt) and resolution (0.001 vol% for ethanol and 2.298 mM for salt). The achieved results demonstrate the feasibility of using the active SRR microwave sensor with a substrate-embedded channel for monitoring ethanol in fermentation broths and electrolytes in human sweat.

Study of the Real-Time Onboard Radio Frequency Interference Detection and Mitigation Strategy for MICAP L-Band Radiometer

Microwave Imager Combined Active and Passive (MICAP), which is a package of active and passive microwave instruments including L/C/K-band radiometers and L-band scatterometer, has been chosen as one of the primary payloads for the Chinese Ocean Salinity Mission (COSM). The L-band one-dimensional synthetic aperture radiometer (L-Rad) is the key part of MICAP to measure sea surface salinity (SSS). As radio frequency interference (RFI) has been reported as a severe threat to L-band radiometry, it can be foreseen that MICAP L-Rad will encounter RFI contaminations unavoidably. Due to the conflict between the huge transmission data volume and the limited downlink budget, it is challenging for MICAP L-Rad to transmit all rapidly sampled sub-band data products and conduct on-ground RFI processing like Soil Moisture Active Passive (SMAP) microwave radiometer. The onboard real-time RFI detection and mitigation strategy is proposed accordingly for MICAP L-Rad. It is designed based on the distributed digital processing structure and the synthetic-aperture feature. The proposed RFI processing strategy is evaluated and verified by the system simulations and hardware experiment, demonstrating its RFI detection capability and low false alarm rate performance.

Impact of Rain on Retrieved Warm Cloud Properties Using Visible and Near-Infrared Reflectances Using Markov Chain Monte Carlo Techniques

Estimates of cloud droplet effective radius ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r_e</i> ) and optical thickness (τ) can be derived using reflected sunlight in a visible non-absorbing channel combined with reflectances from a near IR channel that is absorbing (e.g., The bi-spectral method or BSM). Discrepancies between BSM-estimated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r_e</i> and collocated in situ measurements are commonly attributed to a violation of the assumptions used in the BSM algorithm such as plane parallel geometry, and a single mode droplet size distribution. This research uses Markov Chain Monte Carlo experiments to examine the impact of precipitation on BSM-retrieved <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r_e</i> near optical cloud top by comparing the retrievals and associated uncertainties obtained from two types of experiments assuming a unimodal or bimodal drop size distribution. Where rain is present, BSM-retrieved <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r_e</i> overestimates the true cloud mode <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r_e</i> . Moreover, there is no longer a unique measure of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r_e</i> within the precipitating liquid-phased clouds, resulting in a substantial increase in retrieval uncertainties. This leads to a corresponding loss of information on total number concentration and liquid water content near cloud top. It is found that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r_e</i> biases are not strongly correlated with properties exclusively pertaining to rain, such as rain water content or precipitation rates, but tend to be a function of the ratio between rain and cloud water content and the cloud total number concentration. These results highlight the need for additional independent information such as from an active or passive microwave sensor that can identify the presence of precipitation and constrain additional aspects of bimodal droplet distributions.

Active and Passive Microwave Signatures of Diurnal Soil Freeze-Thaw Transitions on the Tibetan Plateau

Active and passive microwave characteristics of diurnal soil freeze-thaw transitions and their relationships are crucial for developing retrieval algorithms of the soil liquid water content ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\theta _{\mathrm {liq}}$ </tex-math></inline-formula> ) and freeze/thaw state, which, however, have been less explored. This study investigates these microwave characteristics and relationships via analysis of ground-based measurements of brightness temperature ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{B}$ </tex-math></inline-formula> ) and backscattering coefficients ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma ^{0}$ </tex-math></inline-formula> ) in combination with simulations performed with the Tor Vergata discrete radiative transfer model. Both an L-band (1.4 GHz) radiometer ELBARA-III and a wide-band (1–10 GHz) scatterometer are installed in a seasonally frozen Tibetan meadow ecosystem to measure diurnal variations of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{B}$ </tex-math></inline-formula> and copolarized <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma ^{0}$ </tex-math></inline-formula> at both hh ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma _{\mathrm {hh}}^{0}$ </tex-math></inline-formula> ) and vv ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma _{\mathrm {vv}}^{0}$ </tex-math></inline-formula> ) polarizations. Analysis of measurements collected between December 2017 and March 2018 shows that 1) diurnal cycles are observed in both <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{B}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma ^{0}$ </tex-math></inline-formula> due to the change in surface <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\theta _{\mathrm {liq}}$ </tex-math></inline-formula> caused by diurnal soil freeze-thaw transitions; 2) a negatively linear relationship is found between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$e$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma ^{0}$ </tex-math></inline-formula> regardless of frequency, polarization combinations, and observation angles; 3) slopes ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta$ </tex-math></inline-formula> ) of linearly fit equations between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$e^{H}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma _{\mathrm {hh}}^{0}$ </tex-math></inline-formula> decrease with increasing observation angles of ELBARA-III, while the ones between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$e^{V}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma _{\mathrm {vv}}^{\mathrm {0 {}}}$ </tex-math></inline-formula> increase with increasing observation angles; and 4) correlations between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$e$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma ^{0}$ </tex-math></inline-formula> increase with decreasing microwave frequency of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma ^{0}$ </tex-math></inline-formula> measurements and ELBARA-III observation angles, and magnitudes of diurnal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma ^{0}$ </tex-math></inline-formula> cycles also increase with decreasing microwave frequency. Moreover, the calibrated Tor Vergata model shows capability to reproduce both diurnal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$e$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma ^{\mathrm {0 {}}}$ </tex-math></inline-formula> variations as well as to quantify their relationships at different frequencies and observation angles.