Advances in using radar to observe vegetation water dynamics

2020 ◽  
Author(s):  
Susan Steele-Dunne ◽  
Paul Vermunt ◽  
Saeed Khabbazan ◽  
Ashwini Petchiappan ◽  
Jasmeet Judge ◽  
...  
Keyword(s):  
Water Content ◽  
Temporal Dynamics ◽  
Radar Data ◽  
Global Scale ◽  
Water Dynamics ◽  
Radar Observations ◽  
Vegetation Water ◽  
Meaningful Relationships ◽  
The Impact ◽  
Spaceborne Radar

<p>Vegetation acts as an interface between the earth's surface and the atmosphere, modulating exchanges of water, carbon and energy and responding to environmental stressors. Improved understanding of water transport through the soil-vegetation-atmosphere continuum is essential to understand the role of vegetation at a catchment and a global scale. The sensitivity of radar remote sensing observations to the water content of soil and vegetation makes it well-suited to monitoring spatio-temporal dynamics of processes in the soil-vegetation-atmosphere continuum.</p><p>Here, we present the latest results from studies using ground-based and spaceborne radar demonstrating the potential of radar to monitor vegetation water dynamics at scales from meters to tens of kilometers. Field data will be used to demonstrate the sensitivity of radar observations to surface and internal vegetation water content. These results illustrate the potential value of radar for monitoring rapid plant water dynamics, and the impact of water-limited conditions on land-atmosphere exchanges. Satellite data will be used to illustrate the degree to which current spaceborne radar systems can already be used to monitor these processes and the limitations posed by revisit time and resolution.</p><p>We will conclude with an outline of future opportunities and challenges. The next generation of spaceborne radar sensors offers  unprecedented monitoring capability. To avail of this opportunity, we need improved alignment between the treatment of vegetation in hydrological and radiative transfer models. This is essential to ensure meaningful relationships between new radar data products and hydrological states of interest, and to facilitate the assimilation of radar observations to constrain vegetation processes in hydrological models.</p>

scholarly journals Reconstructing Continuous Vegetation Water Content To Understand Sub-daily Backscatter Variations

2021 ◽  
Author(s):  
Paul C. Vermunt ◽  
Susan C. Steele-Dunne ◽  
Saeed Khabbazan ◽  
Jasmeet Judge ◽  
Nick C. van de Giesen
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Water Cycle ◽  
Water Dynamics ◽  
High Temporal Resolution ◽  
Daily Variations ◽  
Vegetation Water Content ◽  
Dew Formation ◽  
Vegetation Water ◽  
Canopy Water

Abstract. Microwave observations are sensitive to vegetation water content (VWC). Consequently, the increasing temporal and spatial resolution of spaceborne microwave observations creates a unique opportunity to study vegetation water dynamics and its role in the diurnal water cycle. However, we currently have a limited understanding of sub-daily variations in VWC and how they affect passive and active microwave observations. This is partly due to the challenges associated with measuring internal VWC for validation, particularly non-destructively and at timescales of less than a day. In this study, we aimed to (1) use field sensors to reconstruct diurnal and continuous records of internal VWC of corn, and (2) use these records to interpret the sub-daily behaviour of a 10-day time series of polarimetric L-band backscatter with high temporal resolution. Sub-daily variations of internal VWC were calculated based on the cumulative difference between estimated transpiration and sap flow rates at the base of the stems. Destructive samples were used to constrain the estimates and for validation. The inclusion of continuous surface canopy water estimates (dew or interception) and surface soil moisture allowed us to attribute hour-to-hour backscatter dynamics to either internal VWC, surface canopy water or soil moisture variations. Our results showed that internal VWC varied with 10–20 % during the day in non-stressed conditions, and the effect on backscatter was significant. Diurnal variations of internal VWC and nocturnal dew formation affected vertically polarized backscatter most. Moreover, on a typical dry day, backscatter variations were 1.5 (HH-pol) to 3 (VV-pol) times more sensitive to VWC than to soil moisture. These results demonstrate that radar observations have the potential to provide unprecedented insight into the role of vegetation water dynamics in land-atmosphere interactions at sub-daily timescales.

scholarly journals The Impacts of Representing the Correlation of Errors in Radar Data Assimilation. Part I: Experiments with Simulated Background and Observation Estimates

2014 ◽  
Vol 142 (11) ◽  
pp. 3998-4016 ◽  
Author(s):  
Dominik Jacques ◽  
Isztar Zawadzki
Keyword(s):  
Data Assimilation ◽  
Cost Function ◽  
Radar Data ◽  
Spatial Correlations ◽  
Radar Observations ◽  
Lack Of Information ◽  
Data Thinning ◽  
The Cost ◽  
The Impact ◽  
Radar Data Assimilation

Abstract In radar data assimilation, statistically optimal analyses are sought by minimizing a cost function in which the variance and covariance of background and observation errors are correctly represented. Radar observations are particular in that they are often available at spatial resolution comparable to that of background estimates. Because of computational constraints and lack of information, it is impossible to perfectly represent the correlation of errors. In this study, the authors characterize the impact of such misrepresentations in an idealized framework where the spatial correlations of background and observation errors are each described by a homogeneous and isotropic exponential decay. Analyses obtained with perfect representation of correlations are compared to others obtained by neglecting correlations altogether. These two sets of analyses are examined from a theoretical and an experimental perspective. The authors show that if the spatial correlations of background and observation errors are similar, then neglecting the correlation of errors has a small impact on the quality of analyses. They suggest that the sampling noise, related to the precision with which analysis errors may be estimated, could be used as a criterion for determining when the correlations of errors may be omitted. Neglecting correlations altogether also yields better analyses than representing correlations for only one term in the cost function or through the use of data thinning. These results suggest that the computational costs of data assimilation could be reduced by neglecting the correlations of errors in areas where dense radar observations are available.

scholarly journals Retrieval of digital elevation models from Sentinel-1 radar data – open applications, techniques, and limitations

2021 ◽  
Vol 13 (1) ◽  
pp. 532-569
Author(s):  
Andreas Braun
Keyword(s):  
Digital Elevation Models ◽  
Radar Data ◽  
Error Sources ◽  
New Era ◽  
Differential Interferometry ◽  
Digital Elevation ◽  
Radar Imagery ◽  
Solid Foundation ◽  
The Impact ◽  
Spaceborne Radar

Abstract With the launch of Sentinel-1 in 2014, a new era of openly accessible spaceborne radar imagery was begun, and its potential has been demonstrated throughout all fields of applications. However, while interferometric approaches to detect surface deformations are continuously being published, only a few studies address the derivation of digital elevation models (DEMs) from Sentinel-1 data. This is mainly because of the narrow orbital tube, which was primarily designed for subsidence measurements using differential interferometry. Nonetheless, the technical conditions are provided for successful applications involving DEM generation. These are outlined in the first part of this article with a focus on potential error sources and the impact of the most important constraints, namely, temporal and perpendicular baselines. The second part evaluates 21 studies on this topic, their aims, and how they dealt with error sources and the necessity of validation. These studies are then discussed based on the main challenges and potentials including how these can be tackled in the future to lay a solid foundation for scientific discourse.

scholarly journals Parametrization of a lake water dynamics model MLake in the ISBA-CTRIP land surface system (SURFEX v8.1)

2021 ◽  
Vol 14 (3) ◽  
pp. 1309-1344
Author(s):  
Thibault Guinaldo ◽  
Simon Munier ◽  
Patrick Le Moigne ◽  
Aaron Boone ◽  
Bertrand Decharme ◽  
...  
Keyword(s):  
Land Surface ◽  
Lake Level ◽  
Climate Models ◽  
Hydrological Modeling ◽  
Lake Victoria ◽  
Global Scale ◽  
Water Dynamics ◽  
Lake Outlet ◽  
The Impact ◽  
River Routing

Abstract. Lakes are of fundamental importance in the Earth system as they support essential environmental and economic services, such as freshwater supply. Streamflow variability and temporal evolution are impacted by the presence of lakes in the river network; therefore, any change in the lake state can induce a modification of the regional hydrological regime. Despite the importance of the impact of lakes on hydrological fluxes and the water balance, a representation of the mass budget is generally not included in climate models and global-scale hydrological modeling platforms. The goal of this study is to introduce a new lake mass module, MLake (Mass-Lake model), into the river-routing model CTRIP to resolve the specific mass balance of open-water bodies. Based on the inherent CTRIP parameters, the development of the non-calibrated MLake model was introduced to examine the influence of such hydrological buffer areas on global-scale river-routing performance. In the current study, an offline evaluation was performed for four river networks using a set of state-of-the-art quality atmospheric forcings and a combination of in situ and satellite measurements for river discharge and lake level observations. The results reveal a general improvement in CTRIP-simulated discharge and its variability, while also generating realistic lake level variations. MLake produces more realistic streamflows both in terms of daily and seasonal correlation. Excluding the specific case of Lake Victoria having low performances, the mean skill score of Kling–Gupta efficiency (KGE) is 0.41 while the normalized information contribution (NIC) shows a mean improvement of 0.56 (ranging from 0.15 to 0.94). Streamflow results are spatially scale-dependent, with better scores associated with larger lakes and increased sensitivity to the width of the lake outlet. Regarding lake level variations, results indicate a good agreement between observations and simulations with a mean correlation of 0.56 (ranging from 0.07 to 0.92) which is linked to the capability of the model to retrieve seasonal variations. Discrepancies in the results are mainly explained by the anthropization of the selected lakes, which introduces high-frequency variations in both streamflows and lake levels that degraded the scores. Anthropization effects are prevalent in most of the lakes studied, but they are predominant for Lake Victoria and are the main cause for relatively low statistical scores for the Nile River However, results on the Angara and the Neva rivers also depend on the inherent gap of ISBA-CTRIP process representation, which relies on further development such as the partitioned energy budget between the snow and the canopy over a boreal zone. The study is a first step towards a global coupled land system that will help to qualitatively assess the evolution of future global water resources, leading to improvements in flood risk and drought forecasting.

Estimating Vegetation Water Content of Corn and Soybean Using Different Polarization Ratios Based on L- and S-Band Radar Data

2017 ◽  
Vol 14 (3) ◽  
pp. 364-368 ◽  
Author(s):  
Jianwei Ma ◽  
Shifeng Huang ◽  
Jiren Li ◽  
Xiaotao Li ◽  
Xiaoning Song ◽  
...  
Keyword(s):  
Water Content ◽  
Radar Data ◽  
Vegetation Water Content ◽  
Vegetation Water

scholarly journals The Impact of the Radar-Sampling Volume on Multiwavelength Spaceborne Radar Measurements Using Airborne Radar Observations

2019 ◽  
Vol 11 (19) ◽  
pp. 2263 ◽  
Author(s):  
Lukas Pfitzenmaier ◽  
Alessandro Battaglia ◽  
Pavlos Kollias
Keyword(s):  
Moving Average ◽  
Particle Diameter ◽  
Dual Wavelength ◽  
Radar Observations ◽  
Airborne Measurements ◽  
Microphysical Properties ◽  
Characteristic Particle ◽  
Sampling Volume ◽  
The Impact ◽  
Spaceborne Radar

Multiwavelength radar observations have demonstrated great potential in improving microphysical retrievals of cloud properties especially in ice and snow precipitation systems. Advancements in spaceborne radar technology have already fostered the launch in 2014 of the first multiwavelength radar system in space, while several future spaceborne multiwavelength radar concepts are under consideration. However, due to antenna size limitations, the sampling volume of spaceborne radars is considerably larger than those achieved by surface- and airborne-based radars. Here, the impact of these large sampling volumes in the information content of the Dual-Wavelength Ratio estimates at Ka-W, Ku-Ka is investigated. High-resolution airborne multiwavelength radar observations during the Olympic Mountain Experiment (OLYMPEx) are used to perform retrievals of ice/snow characteristic particle size, such as mass-weighted particle diameter. To mimic the different satellite sampling volumes, a moving average is applied to the airborne measurements. The radar-observed variables (reflectivity and dual-wavelength ratios) and retrieved microphysical properties at the coarser resolution are compared against those at the original resolution. Our analysis indicates that future Ka-W spaceborne radar missions should take into account the impact of the radar resolution volume on the retrieval of microphysical properties and avoid footprints larger than 2–3 km.

scholarly journals Towards Estimation of Seasonal Water Dynamics of Winter Wheat from Ground-Based L-Band Radiometry 

2021 ◽  
Author(s):  
Thomas Jagdhuber ◽  
François Jonard ◽  
Anke Fluhrer ◽  
David Chaparro ◽  
Martin J. Baur ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Relative Water Content ◽  
Water Status ◽  
Water Dynamics ◽  
Relative Water ◽  
L Band ◽  
The Difference ◽  
Vegetation Water ◽  
Flow Resistances

Abstract. The vegetation optical depth (VOD) parameter contains information on plant water content and biomass, and can be estimated alongside soil moisture from currently operating satellite radiometer missions, such as SMOS (ESA) and SMAP (NASA). The estimation of water fluxes, such as plant water uptake (PWU) and transpiration rate (TR), from these Earth system parameters (VOD, soil moisture) requires assessing potential (suction tension) gradients of water and flow resistances in the soil, the vegetation and the atmosphere, yet it remains an elusive challenge especially on global scale. Here, we used a field-scale experiment to test mechanistic models for the estimation of seasonal water fluxes (PWU and TR) of a winter wheat stand including measurements of soil moisture, VOD, and relative air humidity (RH) under a controlled environment. We utilized microwave L-band observations from a tower-based radiometer to estimate VOD of a wheat stand during the 2017 growing season at the Selhausen laboratory in Germany. From VOD, we first extracted the gravimetric moisture of vegetation and then determined subsequently the relative water content (RWC) and the vegetation water potential (VWP) of the wheat field. Although the relative water content could directly be estimated from VOD, our results indicate this may be problematic for the phenological phases, when rapid biomass and plant structure development take place in the wheat canopy. The water uptake from the soil to the wheat plants was estimated from the difference between the soil and vegetation potentials divided by flow resistance from soil into wheat plants. The transpiration rate from the wheat plants into the atmosphere was obtained from the difference between the vegetation and atmosphere potentials divided by flow resistances from plants to the atmosphere. For this, the required soil matric potential (SMP), the vapor pressure deficit and the flow resistances were obtained from on-site observations of soil, plant and atmosphere and simple mechanistic models. This pathfinder study shows that the L-band microwave radiation contains valuable information on vegetation water status that enables the estimation of water dynamics (up to fluxes) from the soil via wheat plants into the atmosphere, when combined with additional information of soil and atmosphere water content. Still, assumptions when estimating the vegetation water potential from relative water content as well as when estimating the water flow resistances between soil, wheat plants and atmosphere had to be made. Moreover, validation of water flux estimates for assessing their absolute accuracy could not be performed due to a lack of in situ PWU and TR measurements. Nonetheless, our estimates of water status, potentials and fluxes show the expected temporal dynamics and intercompare reasonably well in absolute terms, providing confidence in further developing the proposed approach. Our findings support that passive microwave remote sensing techniques allow for the estimation of vegetation water dynamics next to traditionally measured stand-scale or plot-scale techniques. This might shed light on the potential capabilities of monitoring water dynamics in the soil-plant-atmosphere system using wide-area, remote sensing-based Earth observation data.

scholarly journals Microwave Vegetation Index from Multi-Angular Observations and Its Application in Vegetation Properties Retrieval: Theoretical Modelling

2019 ◽  
Vol 11 (6) ◽  
pp. 730 ◽  
Author(s):  
Somayeh Talebiesfandarani ◽  
Tianjie Zhao ◽  
Jiancheng Shi ◽  
Paolo Ferrazzoli ◽  
Jean-Pierre Wigneron ◽  
...  
Keyword(s):  
Water Content ◽  
Vegetation Index ◽  
Soil Layer ◽  
Global Scale ◽  
Optical Observations ◽  
Theoretical Modelling ◽  
Vegetation Monitoring ◽  
L Band ◽  
Vegetation Water ◽  
Global Vegetation

Monitoring global vegetation dynamics is of great importance for many environmental applications. The vegetation optical depth (VOD), derived from passive microwave observation, is sensitive to the water content in all aboveground vegetation and could serve as complementary information to optical observations for global vegetation monitoring. The microwave vegetation index (MVI), which is originally derived from the zero-order model, is a potential approach to derive VOD and vegetation water content (VWC), however, it has limited application at dense vegetation in the global scale. In this study, we preferred to use a more complex vegetation model, the Tor Vergata model, which takes into account multi-scattering effects inside the vegetation and between the vegetation and soil layer. Validation with ground-based measurements proved this model is an efficient tool to describe the microwave emissions of corn and wheat. The MVI has been derived through two methods: (i) polarization independent ( MVI B P ) and (ii) time invariant ( MVI B T ), based on model simulations at the L band. Results show that the MVI B T has a stronger sensitivity to vegetation properties compared with MVI B P . MVI B T is used to retrieve VOD and VWC, and the results were compared to physical VOD and measured VWC. Comparisons indicated that MVI B T has a great potential to retrieve VOD and VWC. By using L band time-series information, the performance of MVIs could be enhanced and its application in a global scale could be improved while paying attention to vegetation structure and saturation effects.

Impacts of 4DVAR Assimilation of Airborne Doppler Radar Observations on Numerical Simulations of the Genesis of Typhoon Nuri (2008)

2014 ◽  
Vol 53 (10) ◽  
pp. 2325-2343 ◽  
Author(s):  
Zhan Li ◽  
Zhaoxia Pu ◽  
Juanzhen Sun ◽  
Wen-Chau Lee
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Numerical Simulations ◽  
Doppler Radar ◽  
Initial Conditions ◽  
Radar Data ◽  
Radar Observations ◽  
Wind Analysis ◽  
The Impact ◽  
Airborne Doppler Radar

AbstractThe Weather Research and Forecasting Model and its four-dimensional variational data assimilation (4DVAR) system are employed to examine the impact of airborne Doppler radar observations on predicting the genesis of Typhoon Nuri (2008). Electra Doppler Radar (ELDORA) airborne radar data, collected during the Office of Naval Research–sponsored Tropical Cyclone Structure 2008 field experiment, are used for data assimilation experiments. Two assimilation methods are evaluated and compared, namely, the direct assimilation of radar-measured radial velocity and the assimilation of three-dimensional wind analysis derived from the radar radial velocity. Results show that direct assimilation of radar radial velocity leads to better intensity forecasts, as this process enhances the development of convective systems and improves the inner-core structure of Nuri, whereas assimilation of the radar-retrieved wind analysis is more beneficial for tracking forecasts, as it results in improved environmental flows. The assimilation of both the radar-retrieved wind and the radial velocity can lead to better forecasts in both intensity and tracking, if the radial velocity observations are assimilated first and the retrieved winds are then assimilated in the same data assimilation window. In addition, experiments with and without radar data assimilation led to developing and nondeveloping disturbances in numerical simulations of Nuri’s genesis. The improved initial conditions and forecasts from the data assimilation imply that the enhanced midlevel vortex and moisture conditions are favorable for the development of deep convection in the center of the pouch and eventually contribute to Nuri’s genesis. The improved simulations of the convection and associated environmental conditions produce enhanced upper-level warming in the core region and lead to the drop in sea level pressure.

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