scholarly journals Cosmic-ray neutron method for the continuous measurement of Arctic snow accumulation and melt

2021 ◽  
Author(s):  
Anton Jitnikovitch ◽  
Philip Marsh ◽  
Branden Walker ◽  
Darin Desilets
Keyword(s):  
Water Resource Management ◽  
Snow Water Equivalent ◽  
Pearson Correlation ◽  
Cosmic Ray ◽  
Snow Accumulation ◽  
The Arctic ◽  
Southern Ontario ◽  
Sensing Applications ◽  
The Impact

Abstract. The Arctic is warming at two to three times the rate of the global average, significantly impacting snow accumulation and melt. Unfortunately, conventional methods to measure snow water equivalent (SWE), a key aspect of the Arctic snow cover, have numerous limitations that hinder our ability to document annual cycles, the impact of climate change, or to test predictive models. As a result, there is an urgent need for improved methods that measure Arctic SWE; allow for continuous, unmanned measurements over the entire winter; and allow measurements that are representative of spatially variable, Arctic snow covers. In-situ, or invasive, cosmic ray neutron sensors (CRNSs) may fill this observational gap, but few studies have tested these types of sensors or considered their applicability at remote sites in the Arctic. During the winters of 2016/17 and 2017/18 we tested an in-situ CRNS system at two locations in Canada; a cold, low- to high-SWE environment in the Canadian Arctic and at a warm, low-SWE landscape in Southern Ontario that allowed easier access for validation purposes. CRNS moderated neutron counts were compared to manual snow survey SWE values obtained during both winter seasons. Pearson correlation coefficients ranged from −0.89 to −0.98, while regression analyses provided R2 values from 0.79 to 0.96. RMSE of the CRNS-measured SWE averaged 2 mm at the southern Ontario site and ranged from 28 to 40 mm at the Arctic site. These data show that in-situ CRNS instruments are able to continuously measure SWE with sufficient accuracy, and have important applications for measuring SWE in a variety of environments, including remote Arctic locations. These sensors can provide important SWE data for testing snow and hydrological models, water resource management applications, and the validation of remote-sensing applications.

scholarly journals Snow water equivalent measurement in the Arctic based on cosmic ray neutron attenuation

2021 ◽  
Vol 15 (11) ◽  
pp. 5227-5239
Author(s):  
Anton Jitnikovitch ◽  
Philip Marsh ◽  
Branden Walker ◽  
Darin Desilets
Keyword(s):  
Water Resource Management ◽  
Snow Water Equivalent ◽  
Cosmic Ray ◽  
The Arctic ◽  
Sensing Applications ◽  
Neutron Attenuation ◽  
Snow Water ◽  
Remote Sites ◽  
Neutron Sensors

Abstract. Grounded in situ, or invasive, cosmic ray neutron sensors (CRNSs) may allow for continuous, unattended measurements of snow water equivalent (SWE) over complete winter seasons and allow for measurements that are representative of spatially variable Arctic snow covers, but few studies have tested these types of sensors or considered their applicability at remote sites in the Arctic. During the winters of 2016/2017 and 2017/2018 we tested a grounded in situ CRNS system at two locations in Canada: a cold, low- to high-SWE environment in the Canadian Arctic and at a warm, low-SWE landscape in southern Ontario that allowed easier access for validation purposes. Five CRNS units were applied in a transect to obtain continuous data for a single significant snow feature; CRNS-moderated neutron counts were compared to manual snow survey SWE values obtained during both winter seasons. The data indicate that grounded in situ CRNS instruments appear able to continuously measure SWE with sufficient accuracy utilizing both a linear regression and nonlinear formulation. These sensors can provide important SWE data for testing snow and hydrological models, water resource management applications, and the validation of remote sensing applications.

scholarly journals The Coastal Observing System for Northern and Arctic Seas (COSYNA)

Ocean Science ◽  
2017 ◽  
Vol 13 (3) ◽  
pp. 379-410 ◽  
Author(s):  
Burkard Baschek ◽  
Friedhelm Schroeder ◽  
Holger Brix ◽  
Rolf Riethmüller ◽  
Thomas H. Badewien ◽  
...  
Keyword(s):  
Real Time ◽  
The Arctic ◽  
Arctic Seas ◽  
The Public ◽  
The North ◽  
Data Products ◽  
The North Sea ◽  
Arctic Coast ◽  
The Impact

Abstract. The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the German Bight in the North Sea as a prime example of a heavily used coastal area, and Svalbard as an example of an Arctic coast that is under strong pressure due to global change.The COSYNA automated observing and modelling system is designed to monitor real-time conditions and provide short-term forecasts, data, and data products to help assess the impact of anthropogenically induced change. Observations are carried out by combining satellite and radar remote sensing with various in situ platforms. Novel sensors, instruments, and algorithms are developed to further improve the understanding of the interdisciplinary interactions between physics, biogeochemistry, and the ecology of coastal seas. New modelling and data assimilation techniques are used to integrate observations and models in a quasi-operational system providing descriptions and forecasts of key hydrographic variables. Data and data products are publicly available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public.

Area-representative validation of remotely sensed high resolution soil moisture using a cosmic-ray neutron sensor

2020 ◽  
Author(s):  
Dragana Panic ◽  
Isabella Pfeil ◽  
Andreas Salentinig ◽  
Mariette Vreugdenhil ◽  
Wolfgang Wagner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Root Zone ◽  
Spatial Scales ◽  
Temporal Frequency ◽  
Cosmic Ray ◽  
Irrigation Scheduling ◽  
Water Index ◽  
The Impact

<p>Reliable measurements of soil moisture (SM) are required for many applications worldwide, e.g., for flood and drought forecasting, and for improving the agricultural water use efficiency (e.g., irrigation scheduling). For the retrieval of large-scale SM datasets with a high temporal frequency, remote sensing methods have proven to be a valuable data source. (Sub-)daily SM is derived, for example, from observations of the Advanced Scatterometer (ASCAT) since 2007. These measurements are available on spatial scales of several square kilometers and are in particular useful for applications that do not require fine spatial resolutions but long and continuous time series. Since the launch of the first Sentinel-1 satellite in 2015, the derivation of SM at a spatial scale of 1 km has become possible for every 1.5-4 days over Europe (SSM1km) [1]. Recently, efforts have been made to combine ASCAT and Sentinel-1 to a Soil Water Index (SWI) product, in order to obtain a SM dataset with daily 1 km resolution (SWI1km) [2]. Both datasets are available over Europe from the Copernicus Global Land Service (CGLS, https://land.copernicus.eu/global/). As the quality of such a dataset is typically best over grassland and agricultural areas, and degrades with increasing vegetation density, validation is of high importance for the further development of the dataset and for its subsequent use by stakeholders.</p><p>Traditionally, validation studies have been carried out using in situ SM sensors from ground networks. Those are however often not representative of the area-wide satellite footprints. In this context, cosmic-ray neutron sensors (CRNS) have been found to be valuable, as they provide integrated SM estimates over a much larger area (about 20 hectares), which comes close to the spatial support area of the satellite SM product. In a previous study, we used CRNS measurements to validate ASCAT and S1 SM over an agricultural catchment, the Hydrological Open Air Laboratory (HOAL), in Petzenkirchen, Austria. The datasets were found to agree, but uncertainties regarding the impact of vegetation were identified.</p><p>In this study, we validated the SSM1km, SWI1km and a new S1-ASCAT SM product, which is currently developed at TU Wien, using CRNS. The new S1-ASCAT-combined dataset includes an improved vegetation parameterization, trend correction and snow masking. The validation has been carried out in the HOAL and on a second site in Marchfeld, Austria’s main crop producing area. As microwaves only penetrate the upper few centimeters of the soil, we applied the soil water index concept [3] to obtain soil moisture estimates of the root zone (approximately 0-40 cm) and thus roughly corresponding to the depth of the CRNS measurements. In the HOAL, we also incorporated in-situ SM from a network of point-scale time-domain-transmissivity sensors distributed within the CRNS footprint. The datasets were compared to each other by calculating correlation metrics. Furthermore, we investigated the effect of vegetation on both the satellite and the CRNS data by analyzing detailed information on crop type distribution and crop water content.</p><p>[1] Bauer-Marschallinger et al., 2018a: https://doi.org/10.1109/TGRS.2018.2858004<br>[2] Bauer-Marschallinger et al., 2018b: https://doi.org/10.3390/rs10071030<br>[3] Wagner et al., 1999: https://doi.org/10.1016/S0034-4257(99)00036-X</p>

scholarly journals Denitrification by large NAT particles: the impact of reduced settling velocities and hints on particle characteristics

2014 ◽  
Vol 14 (20) ◽  
pp. 11525-11544 ◽  
Author(s):  
W. Woiwode ◽  
J.-U. Grooß ◽  
H. Oelhaf ◽  
S. Molleker ◽  
S. Borrmann ◽  
...  
Keyword(s):  
Stratospheric Ozone ◽  
Spherical Particles ◽  
Lagrangian Model ◽  
The Arctic ◽  
Reference Scenario ◽  
Climate Interactions ◽  
Stratospheric Clouds ◽  
The Impact ◽  
Good Agreement

Abstract. Vertical redistribution of HNO3 through large HNO3-containing particles associated with polar stratospheric clouds (PSCs) plays an important role in the chemistry of the Arctic winter stratosphere. During the RECONCILE (Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions) campaign, apparently very large NAT (nitric acid trihydrate) particles were observed by the airborne in situ probe FSSP-100 (Molleker et al., 2014). Our analysis shows that the FSSP-100 observations associated with the flight on 25 January 2010 cannot easily be explained assuming compact spherical NAT particles due to much too short growing time at temperatures below the existence temperature of NAT (TNAT). State-of-the-art simulations using CLaMS (Chemical Lagrangian Model of the Stratosphere; Grooß et al., 2014) suggest considerably smaller particles. We consider the hypothesis that the simulation reproduces the NAT particle masses in a realistic way, but that real NAT particles may have larger apparent sizes compared to compact spherical particles, e.g. due to non-compact morphology or aspheric shape. Our study focuses on the consequence that such particles would have reduced settling velocities compared to compact spheres, altering the vertical redistribution of HNO3. Utilising CLaMS simulations, we investigate the impact of reduced settling velocities of NAT particles on vertical HNO3 redistribution and compare the results with observations of gas-phase HNO3 by the airborne Fourier transform spectrometer MIPAS-STR associated with two RECONCILE flights. The MIPAS-STR observations confirm conditions consistent with denitrification by NAT particles for the flight on 25 January 2010 and show good agreement with the simulations within the limitations of the comparison. Best agreement is found if settling velocities between 100 and 50% relative to compact spherical particles are considered (slight preference for the 70% scenario). In contrast, relative settling velocities of 30% result in too weak vertical HNO3 redistribution. Sensitivity simulations considering temperature biases of ±1 K and multiplying the simulated nucleation rates by factors of 0.5 and 2.0 affect the comparisons to a similar extent, but result in no effective improvement compared to the reference scenario. Our results show that an accurate knowledge of the settling velocities of NAT particles is important for quantitative simulations of vertical HNO3 redistribution.

scholarly journals Permafrost Variability over the Northern Hemisphere Based on the MERRA-2 Reanalysis

2018 ◽  
Author(s):  
Jing Tao ◽  
Randal D. Koster ◽  
Rolf H. Reichle ◽  
Barton A. Forman ◽  
Yuan Xue ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Snow Accumulation ◽  
In Situ Measurements ◽  
Active Layer Thickness ◽  
Permafrost Region ◽  
Meteorological Forcing ◽  
Northern Alaska

Abstract. This study introduces and evaluates a comprehensive, model-generated dataset of Northern Hemisphere permafrost conditions. Surface meteorological forcing fields from the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) reanalysis data were used to drive an improved version of the land component of MERRA-2 in middle-to-high northern latitudes from 1980 to 2017. The resulting simulated permafrost distribution across the Northern Hemisphere captures well the observed extent of continuous permafrost except in Western Siberia, which is permafrost-free in the simulation. Noticeable discrepancies also appear along the southern edge of the permafrost region where sporadic and isolated permafrost types dominate. The evaluation of the simulated active layer thickness (ALT) climatology against in-situ measurements demonstrates reasonable skill except in Mongolia. In northern Alaska, both ALT retrievals from airborne remote sensing for 2015 and the corresponding simulated ALT exhibit reasonable accuracy vs. in-situ measurements. However, the remotely sensed ALT retrievals generally demonstrate lower levels of spatial variability than both the observed and simulated ALT. Controls on the spatial variability of ALT are examined with idealized numerical experiments focusing on northern Alaska; meteorological forcing and soil type are found to have dominant impacts on the spatial variability of ALT, with vegetation also playing a role through its modulation of snow accumulation. A correlation analysis further reveals that accumulated air temperature and maximum snow water equivalent (SWE) explain most of the year-to-year variability of ALT nearly everywhere over the model-simulated permafrost regions. Simulated ALT trends from 1980 to 2017 indicate that some permafrost areas are experiencing significant degradation, with ALT increasing up to 0.5 cm/year.

scholarly journals Application of machine learning techniques for regional bias correction of snow water equivalent estimates in Ontario, Canada

2020 ◽  
Vol 24 (10) ◽  
pp. 4887-4902
Author(s):  
Fraser King ◽  
Andre R. Erler ◽  
Steven K. Frey ◽  
Christopher G. Fletcher
Keyword(s):  
Machine Learning ◽  
Linear Regression ◽  
Water Resource Management ◽  
Snow Water Equivalent ◽  
Bias Reduction ◽  
Machine Learning Techniques ◽  
Spatial Coverage ◽  
Snow Water ◽  
In Situ Observations

Abstract. Snow is a critical contributor to Ontario's water-energy budget, with impacts on water resource management and flood forecasting. Snow water equivalent (SWE) describes the amount of water stored in a snowpack and is important in deriving estimates of snowmelt. However, only a limited number of sparsely distributed snow survey sites (n=383) exist throughout Ontario. The SNOw Data Assimilation System (SNODAS) is a daily, 1 km gridded SWE product that provides uniform spatial coverage across this region; however, we show here that SWE estimates from SNODAS display a strong positive mean bias of 50 % (16 mm SWE) when compared to in situ observations from 2011 to 2018. This study evaluates multiple statistical techniques of varying complexity, including simple subtraction, linear regression and machine learning methods to bias-correct SNODAS SWE estimates using absolute mean bias and RMSE as evaluation criteria. Results show that the random forest (RF) algorithm is most effective at reducing bias in SNODAS SWE, with an absolute mean bias of 0.2 mm and RMSE of 3.64 mm when compared with in situ observations. Other methods, such as mean bias subtraction and linear regression, are somewhat effective at bias reduction; however, only the RF method captures the nonlinearity in the bias and its interannual variability. Applying the RF model to the full spatio-temporal domain shows that the SWE bias is largest before 2015, during the spring melt period, north of 44.5∘ N and east (downwind) of the Great Lakes. As an independent validation, we also compare estimated snowmelt volumes with observed hydrographs and demonstrate that uncorrected SNODAS SWE is associated with unrealistically large volumes at the time of the spring freshet, while bias-corrected SWE values are highly consistent with observed discharge volumes.

scholarly journals Assimilation of IASI satellite CO fields into a global chemistry transport model for validation against aircraft measurements

2012 ◽  
Vol 12 (10) ◽  
pp. 4493-4512 ◽  
Author(s):  
A. Klonecki ◽  
M. Pommier ◽  
C. Clerbaux ◽  
G. Ancellet ◽  
J.-P. Cammas ◽  
...  
Keyword(s):  
Transport Model ◽  
Source Region ◽  
Specific Treatment ◽  
Arctic Region ◽  
The Arctic ◽  
Chemistry Transport Model ◽  
Mixing Ratios ◽  
High Concentrations ◽  
The Impact

Abstract. This work evaluates the IASI CO product against independent in-situ aircraft data from the MOZAIC program and the POLARCAT aircraft campaign. The validation is carried out by analysing the impact of assimilation of eight months of IASI CO columns retrieved for the period of May to December 2008 into the global chemistry transport model LMDz-INCA. A modelling system based on a sub-optimal Kalman filter was developed and a specific treatment that takes into account the representativeness of observations at the scale of the model grid is applied to the IASI CO columns and associated errors before their assimilation in the model. Comparisons of the assimilated CO profiles with in situ CO measurements indicate that the assimilation leads to a considerable improvement of the model simulations in the middle troposphere as compared with a control run with no assimilation. Model biases in the simulation of background values are reduced and improvement in the simulation of very high concentrations is observed. The improvement is due to the transport by the model of the information present in the IASI CO retrievals. Our analysis also shows the impact of assimilation of CO on the representation of transport into the Arctic region during the POLARCAT summer campaign. A considerable increase in CO mixing ratios over the Asian source region was observed when assimilation was used leading to much higher values of CO during the cross-pole transport episode. These higher values are in good agreement with data from the POLARCAT flights that sampled this plume.

Investigating chemical composition of the troposphere over the Russian Arctic using the "Optik" Tu-134 aircraft laboratory

2020 ◽  
Author(s):  
Boris D. Belan ◽  
Pavel N. Antokhin ◽  
Mikhail Yu. Arshinov ◽  
Sergey B. Belan ◽  
Denis K. Davydov ◽  
...  
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
General Scheme ◽  
Water Area ◽  
Kara Sea ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Aerosol Composition ◽  
The Impact

<p>The need to undertake a comprehensive investigation of the atmospheric composition over the Russian segment of the Arctic is caused by a serious lack and irregularity in obtaining observational data from this regio of the Earth. In addition, a comparison of the aircraft in-situ measurements with satellite data retrieved for the Kara Sea region in 2017 revealed large uncertainties in determining the vertical distribution of greenhouse gas concentrations using remote sensing methods. The development and improvement of the last ones needs at least their periodic verification by means of undertaking precise in-situ aircraft measurements.</p><p>The general scheme of the proposed experiment is as follows (map is attached): flight from Novosibirsk to Naryan-Mar via Sabetta. From Naryan-Mar, flight to a water area of the Bering Sea (up to 1000 km). Flight from Naryan-Mar to Sabetta. From here, flight to a water area of the Kara Sea (up to 1000 km). Then, flight to Tiksi. Flight from Tiksi to a water area of the Laptev Sea (up to 1000 km). Flight to Chokurdakh or Chersky. From there, flight to a water area of the East Siberian Sea (up to 1000 km). Flight to Cape Schmidt. Flight to a water area of the Chukchi Sea (up to 1000 km). Return route: Cape Shmidt–Chersky (or Chokurdah)–Yakutsk–Bratsk–Novosibirsk. It will take about 100 hours of flying time to implement the entire aircraft campaign. Campaign period is about 2-3 weeks. It is better to undertake the campaign during summer when the ocean is open. Flights over the land surface are assumed to be undertaken from 0.5 km to 11 km above ground level while above the sea from 0.2 km to 11 km. The flight profile is variable from the maximum possible height to the minimum allowed one. Vertical profiles of gas and aerosol composition will be obtained, including black carbon and organic components, as well as basic meteorological quantities.</p><p>Satellite data will be verified that do not yet provide acceptable accuracy. For the first time, unique information will be obtained over the least explored region of the Arctic, which is crucial for the whole planet in terms of climate formation and the impact of global warming.</p>

scholarly journals The Coastal Observing System for Northern and Arctic Seas (COSYNA)

2016 ◽  
Author(s):  
B. Baschek ◽  
F. Schroeder ◽  
H. Brix ◽  
R. Riethmüller ◽  
T. H. Badewien ◽  
...  
Keyword(s):  
Real Time ◽  
The Arctic ◽  
Arctic Seas ◽  
The Public ◽  
The North ◽  
Data Products ◽  
The North Sea ◽  
Arctic Coast ◽  
The Impact

Abstract. The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the arctic coasts in a changing environment. Particular focus is given to the German Bight in the North Sea as a prime example for a heavily used coastal area, and Svalbard as an example of an arctic coast that is under strong pressure due to global change. The automated observing and modelling system COSYNA is designed to monitor real time conditions, provide short-term forecasts and data products, and to assess the impact of anthropogenically induced change. Observations are carried out combining satellite and radar remote sensing with various in situ platforms. Novel sensors, instruments, and algorithms are developed to further improve the understanding of the interdisciplinary interactions between physics, biogeochemistry, and the ecology of coastal seas. New modelling and data assimilation techniques are used to integrate observations and models in a quasi-operational system providing descriptions and forecasts of key hydrographic variables. Data and data products are publically available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public.

scholarly journals Datation de surfaces geomorphologiques reperes par le 10 Be produit in-situ; implications tectoniques et climatiques

2001 ◽  
Vol 172 (2) ◽  
pp. 223-236 ◽  
Author(s):  
Lionel L. Siame ◽  
Regis Braucher ◽  
Didier L. Bourles ◽  
Olivier Bellier ◽  
Michel Sebrier
Keyword(s):  
Cosmic Rays ◽  
Nuclear Physics ◽  
Active Faults ◽  
Active Regions ◽  
Cosmic Ray ◽  
Tectonic Activity ◽  
Slip Rates ◽  
Tectonically Active ◽  
The Impact

Abstract The evolution of continental landforms is mainly modulated by the impact of climatic and tectonic processes. Because of their distinctive morphology and the periodicity of their deposition, climatically induced landforms such as alluvial fans or terraces are well suited to infer rates of tectonic and continental climatic processes. Within tectonically active regions, an important step consists in dating displaced geomorphic features to calculate slip rates on active faults. Dating is probably the most critical tool because it is generally much more simpler to measure deformation resulting from tectonic activity than it is to accurately date when that deformation occurred. Recent advances in analytical chemistry and nuclear physics (accelerator mass spectrometry) now allow quantitative abundance measurements of the extremely rare isotopes produced by the interaction of cosmic rays with surface rocks and soils, the so-called in situ-produced cosmogenic nuclides ( 3 He, 10 Be, 21 Ne, 26 Al, 36 Cl), and allow to directly date the duration that a landform has been exposed to cosmic rays at the Earth's surface [Lal, 1991; Nishiizumi et al., 1993; Cerling and Craig, 1994; Clark et al., 1995]. In fact, the abundance of these cosmonuclides is proportional to landscape stability and, under favorable circumstances, their abundance within surface rocks can be used as a proxy for erosion rate or exposure age. These cosmonuclides thus provide geomorphologists with the opportunity to constrain rates of landscape evolution. This paper presents a new approach that combines cosmic ray exposure (CRE) dating using in situ-produced 10 Be and geomorphic as well as structural analyses. This approach has been applied on two active strike-slip and reverse faults located in the Andean foreland of western Argentina. These two case studies illustrate how CRE dating using in situ-produced 10 Be is particularly well suited for geomorphic studies that aim to estimate the respective control of climate and tectonics on morphogenesis.

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