Monitoring Water and Energy Cycles at Climate Scale in the Third Pole Environment (CLIMATE-TPE)

A better understanding of the water and energy cycles at climate scale in the Third Pole Environment is essential for assessing and understanding the causes of changes in the cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and for predicting the possible changes in water resources in South and East Asia. This paper reports the following results: (1) A platform of in situ observation stations is briefly described for quantifying the interactions in hydrosphere-pedosphere-atmosphere-cryosphere-biosphere over the Tibetan Plateau. (2) A multiyear in situ L-Band microwave radiometry of land surface processes is used to develop a new microwave radiative transfer modeling system. This new system improves the modeling of brightness temperature in both horizontal and vertical polarization. (3) A multiyear (2001–2018) monthly terrestrial actual evapotranspiration and its spatial distribution on the Tibetan Plateau is generated using the surface energy balance system (SEBS) forced by a combination of meteorological and satellite data. (4) A comparison of four large scale soil moisture products to in situ measurements is presented. (5) The trajectory of water vapor transport in the canyon area of Southeast Tibet in different seasons is analyzed, and (6) the vertical water vapor exchange between the upper troposphere and the lower stratosphere in different seasons is presented

Modelling of Multi-Frequency Microwave Backscatter and Emission of Land Surface by a Community Land Active Passive Microwave Radiative Transfer Modelling Platform (CLAP)

Emission and backscattering signals of land surfaces at different frequencies have distinctive responses to soil and vegetation physical states. The use of multi-frequency combined active and passive microwave signals provides complementary information to better understand and interpret the observed signals in relation to surface states and the underlying physical processes. Such a capability also improves our ability to retrieve surface parameters and states such as soil moisture, freeze-thaw dynamics and vegetation biomass and vegetation water content (VWC) for ecosystem monitoring. We present here a prototype Community Land Active Passive Microwave Radiative Transfer Modelling platform (CLAP) for simulating both backscatter (&sigma;0) and emission (TB) signals of land surfaces, in which the CLAP is backboned by an air-to-soil transition model (ATS) (accounting for surface dielectric roughness) integrated with the Advanced Integral Equation Model (AIEM) for modelling soil surface scattering, and the Tor Vergata model for modelling vegetation scattering and the interaction between vegetation and soil parts. The CLAP was used to simulate both ground-based and space-borne multi-frequency microwave measurements collected at the Maqu observatory on the eastern Tibetan plateau. The ground-based systems include a scatterometer system (1&ndash;10 GHz) and an L-band microwave radiometer. The space-borne measurements are obtained from the X-band and C-band Advanced Microwave Scanning Radiometer 2 (AMSR2) radiation observations. The impacts of different vegetation properties (i.e., structure, water and temperature dynamics) and soil conditions (i.e., different moisture and temperature profiles) on the microwave signals were investigated by CLAP simulation for understanding factors that can account for diurnal variations of the observed signals. The results show that the dynamic VWC partially accounts for the diurnal variation of the observed signal at the low frequencies (i.e., S- and L-bands), while the diurnal variation of the observed signals at high frequencies (i.e., X- and C-bands) is more due to vegetation temperature changing, which implies the necessity to first disentangle the impact of vegetation temperature for the use of high frequency microwave signals. The model derived vegetation optical depth &tau; differs in terms of frequencies and different model parameterizations, while its diurnal variation depends on the diurnal variation of VWC regardless of frequency. After normalizing &tau; at multi-frequency by wavenumber, difference is still observed among different frequencies. This indicates that &tau; is indeed frequency-dependent, and &tau; for each frequency is suggested to be applied in the retrieval of soil and vegetation parameters. Moreover, &tau; at different frequencies (e.g., X-band and L-band) cannot be simply combined for constructing accurate long time series microwave-based vegetation product. To this purpose, it is suggested to investigate the role of the leaf water potential in regulating plant water use and its impact on the normalized &tau; at multi-frequency. Overall, the CLAP is expected to improve our capability for understanding and applying current and future multi-frequency space-borne microwave systems (e.g. those from ROSE-L and CIMR) for vegetation monitoring.</p

Retrieving landscape freeze/thaw state fromSoil Moisture Active Passive (SMAP) radar and radiometer measurements

Over one-third of the global land area undergoes a seasonal transition between predominantly frozen and non-frozen conditions each year, with the land surface freeze/thaw (FT) state a significant control on hydrological and biospheric processes over northern land areas and at high elevations. The NASA Soil Moisture Active Passive (SMAP) mission produced a daily landscape FT product at 3-km spatial resolution derived from ascending and descending orbits of SMAP high-resolution L-band (1.4 GHz) radar measurements. Following the failure of the SMAP radar in July 2015, coarser (36-km) footprint SMAP radiometer inputs were used to develop an alternative daily passive microwave freeze/thaw product. In this study, in situ observations are used to examine differences in the sensitivity of the 3-km radar versus the 36-km radiometer measurements to the landscape freeze/thaw state during the period of overlapping instrument operation. Assessment of the retrievals at high-latitude SMAP core validation sites showed excellent agreement with in situ flags, exceeding the 80% SMAP mission accuracy requirement. Similar performance was found for the radar and radiometer products using both air temperature and soil temperature derived FT reference flags. There was a tendency for SMAP thaw retrievals to lead the surface flags due to the influence of wet snow cover conditions on both the radar and radiometer signal. Comparison with other satellite derived FT products showed those derived from passive measurements (SMAP radiometer; Aquarius radiometer; Advanced Microwave Scanning Radiometer - 2) retrieved less frozen area than the active products (SMAP radar; Aquarius radar)

Remote Sensing of Environmental Changes in Cold Regions

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing

Analyse des cycles gel/dégel des régions nordiques par télédétection micro-ondes passives en bande L

Le réchauffement climatique dans les régions nordiques, fort important depuis le milieu du siècle dernier, a de multiples impacts sur la dynamique des écosystèmes, notamment sur les cycles gel/dégel de surface qui influencent les flux de carbone, l'activité biogéochimique des sols, l'hydrologie et le pergélisol aux hautes latitudes. La télédétection satellitaire du gel/dégel par micro-ondes passives est un outil très prometteur permettant un suivi continu et global, mais comporte des difficultés souvent reliées à l’effet d’hétérogénéité spatiale intra-pixel relié aux résolutions grossières des capteurs micro-ondes passives à basse fréquence. L’objectif principal du projet est d’évaluer l’utilisation de la télédétection micro-onde passive en bande L (1.4 GHz) pour le suivi de l’état de gel/dégel de la surface en forêt boréale. Un premier objectif spécifique est d’évaluer un nouveau produit des cycles de gel/dégel de surface estimée à partir des radiomètres bande L satellitaires Aquarius. Cette base de données de 3.5 années a été mise en ligne au National Snow and Ice Data Center (NSIDC). Le deuxième objectif spécifique est d’analyser l’effet de la variabilité spatiale intrapixel de l’état de gel du sol et de son impact sur les températures de brillance (TB) mesurées par le radiomètre de la mission Soil Moisture Active Passive (SMAP) en période de transition afin de quantifier la fraction de sol gelé. Les résultats pour le premier objectif montrent que la nouvelle base de données possède une bonne capacité à estimer l’état de gel/dégel de la surface sur l’ensemble de l’Hémisphère Nord (> 50°N). Cette recherche offre également une rare intercomparaison entre produits de gel/dégel satellitaires en comparant le produit Aquarius au Freeze/Thaw-Earth System Data Record (FT-ESDR) développé avec les données à plus hautes fréquences du capteur SSM/I. Pour le deuxième objectif, des capteurs de température distribués le long de transects de plusieurs kilomètres sur deux différents sites de taïga montrent que la variabilité spatiale du gel à l’automne peut être de 7.5 à 9.5 semaines. Il est également démontré que les mesures de SMAP sont sensibles à cette variabilité et un algorithme développé permet d’estimer le pourcentage intrapixel de sol gelé avec des coefficients de détermination (R2) entre 0.63 et 0.88 lorsque comparé aux mesures in situ. Ces résultats offrent de nouveaux outils pour mieux comprendre et quantifier les cycles de gel/dégel de l’environnement boréal et leurs impacts sur les processus biogéophysiques, hydrologiques et sur le pergélisol.Abstract: Climate change in nordic regions, which has been of growing significance over the past century has multiple impacts on the dynamic of ecosystems, notably on the surface freeze/thaw cycles, which influences carbon flux, soil biogeochemical activity, hydrology and permafrost at high latitudes. Satellite remote sensing of freeze/thaw with passive microwaves is a promising tool to offer continuous and global monitoring, but can also entail some difficulties due to intra-pixel spatial variability effects coming from the low resolution of low-frequency passive microwave sensors. The primary objective of the project is to evaluate the use of passive microwave remote sensing in L-band (1.4 GHz) for monitoring of the surface freeze/thaw in the boreal forest. A first specific objective is to evaluate a new surface freeze/thaw product estimated by the Aquarius satellite L-band radiometers. This 3.5 year-old database has been put online at the National Snow and Ice Data Center (NSIDC) website. The second specific objective is to analyse the effect of intra-pixel spatial variability of freeze/thaw and its impact on brightness temperatures (TB) measured by the Soil Moisture Active Passive (SMAP) radiometer during transition periods in order to quantify the frozen soil fraction. Results for the first objective show that the new database possesses a good capacity to estimate the surface freeze/thaw state for the entirety of the Northern Hemisphere (>50°N). This research also offers a rare intercomparison between freeze/thaw satellite products by comparing the Aquarius product to the Freeze/Thaw-Earth System Data Record (FT-ESDR) product developed with higher frequencies data of the SSM/I sensor. For the second objective, temperature sensors distributed along transects of several kilometers on two different taiga sites show that the spatial variability of autumn soil freeze onset can be between 7.5 and 9.5 weeks. It demonstrates that SMAP measurements are sensitive to this variability and a developed algorithm offers estimations of the intrapixel soil frozen fraction with coefficients of determination (R2) between 0.63 and 0.88 when compared to in situ measurements. These results offer new tools for a better understanding and quantification of freeze/thaw cycles in boreal environments and their impacts on biogeochemical and hydrologic processes and on permafrost

Détection des cycles de gel/dégel de la couche active du sol en toundra arctique à partir d’imageries radar à synthèse d’ouverture (RSO) multicapteur en bande C

L’augmentation de la température de l’air moyenne annuelle, chiffrée à +2,3 °C pour les régions de l’arctique Canadien entre 1948 et 2016, a des impacts considérables sur le couvert nival arctique et sur la végétation en place. Ces deux paramètres influencent le régime thermique du sol et donc, les cycles de gel/dégel de sa couche active dans l’écosystème arctique. L’importance du suivi de ces cycles réside dans leur influence sur plusieurs paramètres de la cryosphère tels que le cycle hydrologique et du carbone, la saison de croissance de la végétation, l’état du pergélisol sous-jacent ainsi que l’épaisseur de sa couche active. L’utilisation de données ponctuelles ou provenant de capteurs micro-onde passive à basse résolution présente un enjeu pour le suivi spatial et temporel de ces cycles. Le projet vise à développer un algorithme de détection des cycles de gel/dégel du sol en toundra arctique à partir d’imageries RSO multicapteur (i.e., Sentinel-1 et RADARSAT-2) ayant une couverture temporelle quasi journalière en bande C, afin d’évaluer l’impact de la variabilité spatiale et temporelle des paramètres influençant le régime thermique du sol tel que, les écosystèmes terrestres (i.e., écotype) et la présence de neige. L’étude se concentre sur une zone à l’intérieur du bassin versant du lac Greiner à proximité de la ville de Cambridge Bay au Nunavut. La normalisation de l’angle d’incidence a permis de diminuer le bruit dans les séries temporelles ainsi que de rendre possible l’utilisation d'images acquises à l'intérieur de plusieurs orbites d’observation. Cela a aussi permis d’uniformiser les données des deux capteurs pour les combiner en une seule série temporelle. Deux algorithmes de détections ont été utilisés, soit un algorithme de seuil saisonnier (STA) ainsi qu’un algorithme de détection de changement (CPD). La validation s’est faite à partir des données spatialement distribuées de température du sol et de l’air indépendamment sous forme de précision (%) et de délai (#jours) de détection. Les deux algorithmes ont permis d’obtenir une précision de détection de plus de 97% sur les sites de référence. Une spatialisation, pixel par pixel, de la méthode STA a permis la création de cartes de jour de gel/dégel pour le site d’étude. La combinaison des cartes de jour de transition avec la carte d’écotype a permis de modéliser l’impact des caractéristiques des écotypes sur le jour de transition. Les résultats obtenus dans ce projet démontrent clairement le potentiel de l’utilisation des données RSO en bande C pour la détection des cycles de gel/dégel, ce qui constitue un résultat important en raison de la quantité grandissante de données à cette fréquence (e.g., RCM, Sentinel-1A-C-D). La méthode présentée dans ce projet pourrait permettre de créer des cartes de transition pour tout le bassin versant du lac Greiner à partir de données RSO en bande C.Abstract : The observed average annual surface temperature increase of 2.3°C in the Canadian Arctic regions between 1948 and 2016 has significant effects on the Arctic snow cover and on the vegetation in place. Those two parameters influence the thermal regime of the ground and therefore the freeze and thaw (F/T) cycles of the soil active layer in the Arctic tundra ecosystem. The importance of monitoring these cycles lies in their influence on several parameters of the cryosphere such as the hydrological and carbon cycle, the vegetation growing season, the state of the underlying permafrost and the thickness of its active layer. The use of punctual data or low-resolution passive microwave sensors presents a challenge for the spatial and temporal monitoring of these cycles. The project aims to develop an algorithm for soil freeze/thaw cycles detection in arctic tundra from multisensor C-band imagery (i.e., Sentinel-1 and RADARSAT-2) to assess the impact of the spatial and temporal variability of the parameters influencing the thermal regime of the ground, such as the terrestrial ecosystems (i.e., ecotype) and the snow cover. The study focused on a region of the Greiner lake watershed on Victoria Island in Nunavut. An incidence angle normalization was applied to the backscatter time series to remove influence of the acquisition angle on backscatter and to allow for the use of images acquired within several orbits of observation. This also standardized the data from the two sensors to combine them into a single time series. Two detection algorithms were used on the normalized backscatter coefficient data, namely a seasonal threshold algorithm (STA) and a change point detection algorithm (CPD). A spatially distributed network of soil and air temperature were used for validation in the form of accuracy (%) and delay (#days) of detection. Both algorithms achieved a detection accuracy of more than 97% for the entire analysis period on the reference sites. A pixel-by-pixel spatialization of the STA method allowed to create F/T transition maps for the extended study site. The combination of the transition maps with the ecotype data made it possible to model the impact of ecotype characteristics on the day of transition. The results obtained in this project clearly demonstrate the potential of using C-band for the detection of F/T cycles, which is an important aspect due to the increasing number of data at this frequency (e.g., RCM, Sentinel -1A-C-D). The method presented in this project could then make it possible to create transition maps for the entire Greiner Lake watershed from C-band SAR data and thus improve the integration of this parameter in climate models

Northern Hemisphere surface freeze–thaw product from Aquarius L-band radiometers

In the Northern Hemisphere, seasonal changes in surface freeze–thaw (FT) cycles are an important component of surface energy, hydrological and eco-biogeochemical processes that must be accurately monitored. This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the Equal-Area Scalable Earth Grid version 2.0, above the parallel 50∘&thinsp;N, with a spatial resolution of 36&thinsp;km&thinsp;×&thinsp;36&thinsp;km. The FT-AP classification algorithm is based on a seasonal threshold approach using the normalized polarization ratio, references for frozen and thawed conditions and optimized thresholds. To evaluate the uncertainties of the product, we compared it with another satellite FT product also derived from passive microwave observations but at higher frequency: the resampled 37&thinsp;GHz FT Earth Science Data Record (FT-ESDR). The assessment was carried out during the overlapping period between 2011 and 2014. Results show that 77.1&thinsp;% of their common grid cells have an agreement better than 80&thinsp;%. Their differences vary with land cover type (tundra, forest and open land) and freezing and thawing periods. The best agreement is obtained during the thawing transition and over forest areas, with differences between product mean freeze or thaw onsets of under 0.4 weeks. Over tundra, FT-AP tends to detect freeze onset 2–5 weeks earlier than FT-ESDR, likely due to FT sensitivity to the different frequencies used. Analysis with mean surface air temperature time series from six in situ meteorological stations shows that the main discrepancies between FT-AP and FT-ESDR are related to false frozen retrievals in summer for some regions with FT-AP. The Aquarius product is distributed by the U.S. National Snow and Ice Data Center (NSIDC) at https://nsidc.org/data/aq3_ft/versions/5 with the DOI https://doi.org/10.5067/OV4R18NL3BQR.</p

Characterization of site-specific vegetation activity in Alaskan wet and dry tundra as related to climate and soil state

We present discrete (2-h resolution) multi-year (2008–2017) in situ measurements of seasonal vegetation growth and soil biophysical properties from two sites on Alaska\u27s North Slope, USA, representing dry and wet sedge tundra. We examine measurements of vertical active soil layer temperature and soil moisture profiles (freeze/thaw status), woody shrub vegetation physiological activity, and meteorological site data to assess interrelationships within (and between) these two study sites. Vegetation phenophases (cold de-hardening start, physiological function start, stem growth start, stem growth end, physiological function end, cold hardening completion) were found to have greater interannual day of year (DOY) occurrence variability at the dry site compared with the wet site. At the dry site, vegetation activity begins on average ~7 days earlier and ends ~11 days earlier. The mean active stem growth window lasts ~54 days for the dry site and ~51 days for the wet site. Vegetation, in both tundra environments, began cold de-hardening functions (warm season prep) prior to atmospheric temperatures warming above 0°C. Similar results were found related to the critical soil freeze/thaw/transition dates; the dry site had a DOY phenophase occurrence range that was 8 days larger than that of the wet site. A longer continuous summer thaw period was captured at the wet site by ~26 days throughout the active layer. In addition, the dry site was measured to have longer spring and fall soil isothermal conditions than the wet site by ~9 and 5 days throughout the active layer. These results show that the dry site\u27s willow shrub vegetation physiology and soil condition phenology is more variable than the wet site. Alongside the in situ data, a remote sensing product from NASA\u27s MEaSUREs program was utilized; our research indicates that the AMSR-derived satellite product is more precise over the wet tundra site with critical date alignment between remote sensing observations and in situ measurements ranging from ~4 to 11 days. Furthermore, the AMSR product was shown to preemptively estimate land surface condition change during the spring transition for both tundra types while lagging during the fall transition and freeze-up periods

Parameter Optimization of a Discrete Scattering Model by Integration of Global Sensitivity Analysis Using SMAP Active and Passive Observations

Active and passive microwave signatures respond differently to the land surface and provide complementary information on the characteristics of the observed scenes. The objective of this paper is to explore the synergy of active radar and passive radiometer observations at the same spatial scale to constrain a discrete radiative transfer model, the Tor Vergata (TVG) model, to gain insights into the microwave scattering and emission mechanisms over grasslands. The TVG model can simultaneously simulate the backscattering coefficient and emissivity with a set of input parameters. To calibrate this model, in situ soil moisture and temperature data collected from the Maqu area in the northeastern region of the Tibetan Plateau, interpolated leaf area index (LAI) data from the Moderate Resolution Imaging Spectroradiometer LAI eight-day products, and concurrent and coincident Soil Moisture Active Passive (SMAP) radar and radiometer observations are used. Because this model needs numerous input parameters to be driven, the extended Fourier amplitude sensitivity test is first applied to conduct global sensitivity analysis (GSA) to select the sensitive and insensitive parameters. Only the most sensitive parameters are defined as free variables, to separately calibrate the active-only model (TVG-A), the passive-only model (TVG-P), and the active and passive combined model (TVG-AP). The accuracy of the calibrated models is evaluated by comparing the SMAP observations and the model simulations. The results show that TVG-AP can well reproduce the backscattering coefficient and brightness temperature, with correlation coefficients of 0.87, 0.89, 0.78, and 0.43 and root-mean-square errors of 0.49 dB, 0.52 dB, 7.20 K, and 10.47 K for &#x03C3; HH&#x2070; , &#x03C3; VV&#x2070; , TBH, and TBV, respectively. In contrast, TVG-A and TVG-P can only accurately model the backscattering coefficient and brightness temperature, respectively. Without any modifications of the calibrated parameters, the error metrics computed from the validation data are slightly worse than those of the calibration data. These results demonstrate the feasibility of the synergistic use of SMAP active radar and passive radiometer observations under the unified framework of a physical model. In addition, the results demonstrate the necessity and effectiveness of applying GSA in model optimization. It is expected that these findings can contribute to the development of model-based soil moisture retrieval methods using active and passive microwave remote sensing data