scholarly journals Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations

2021 ◽  
Vol 21 (6) ◽  
pp. 4637-4657
Author(s):  
Xiao Lu ◽  
Daniel J. Jacob ◽  
Yuzhong Zhang ◽  
Joannes D. Maasakkers ◽  
Melissa P. Sulprizio ◽  
...  
Keyword(s):  
Information Content ◽  
Oil And Gas ◽  
Joint Inversion ◽  
Gas Emissions ◽  
In Situ Data ◽  
Methane Budget ◽  
The Us ◽  
In Situ Observations ◽  
Methane Sink

Abstract. We use satellite (GOSAT) and in situ (GLOBALVIEWplus CH4 ObsPack) observations of atmospheric methane in a joint global inversion of methane sources, sinks, and trends for the 2010–2017 period. The inversion is done by analytical solution to the Bayesian optimization problem, yielding closed-form estimates of information content to assess the consistency and complementarity (or redundancy) of the satellite and in situ data sets. We find that GOSAT and in situ observations are to a large extent complementary, with GOSAT providing a stronger overall constraint on the global methane distributions, but in situ observations being more important for northern midlatitudes and for relaxing global error correlations between methane emissions and the main methane sink (oxidation by OH radicals). The in-situ-only and the GOSAT-only inversions alone achieve 113 and 212 respective independent pieces of information (DOFS) for quantifying mean 2010–2017 anthropogenic emissions on 1009 global model grid elements, and respective DOFS of 67 and 122 for 2010–2017 emission trends. The joint GOSAT+ in situ inversion achieves DOFS of 262 and 161 for mean emissions and trends, respectively. Thus, the in situ data increase the global information content from the GOSAT-only inversion by 20 %–30 %. The in-situ-only and GOSAT-only inversions show consistent corrections to regional methane emissions but are less consistent in optimizing the global methane budget. The joint inversion finds that oil and gas emissions in the US and Canada are underestimated relative to the values reported by these countries to the United Nations Framework Convention on Climate Change (UNFCCC) and used here as prior estimates, whereas coal emissions in China are overestimated. Wetland emissions in North America are much lower than in the mean WetCHARTs inventory used as a prior estimate. Oil and gas emissions in the US increase over the 2010–2017 period but decrease in Canada and Europe. The joint inversion yields a global methane emission of 551 Tg a−1 averaged over 2010–2017 and a methane lifetime of 11.2 years against oxidation by tropospheric OH (86 % of the methane sink).

scholarly journals Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations

2020 ◽  
Author(s):  
Xiao Lu ◽  
Daniel J. Jacob ◽  
Yuzhong Zhang ◽  
Joannes D. Maasakkers ◽  
Melissa P. Sulprizio ◽  
...  
Keyword(s):  
Joint Inversion ◽  
Bayesian Optimization ◽  
Oh Radicals ◽  
Atmospheric Methane ◽  
Gas Emissions ◽  
The Us ◽  
In Situ Observations ◽  
Oil Gas ◽  
Methane Sink

Abstract. We use satellite (GOSAT) and in situ (GLOBALVIEWplus CH4 ObsPack) observations of atmospheric methane in a joint global inversion of methane sources, sinks, and trends for the 2010–2017 period. The inversion is done by analytical solution to the Bayesian optimization problem, yielding closed-form estimates of information content to assess the consistency and complementarity (or redundancy) of the satellite and in situ datasets. We find that GOSAT and in situ observations are to a large extent complementary, with GOSAT providing a stronger overall constraint on the global methane distributions, but in situ observations being more important for northern mid-latitudes and for relaxing global error correlations between methane emissions and the main methane sink (oxidation by OH radicals). The GOSAT observations achieve 212 independent pieces of information (DOFS) for quantifying mean 2010–2017 anthropogenic emissions on 1009 global model grid elements, and a DOFS of 122 for 2010–2017 emission trends. Adding the in situ data increases the DOFS by about 20–30 %, to 262 and 161 respectively for mean emissions and trends. Our joint inversion finds that oil/gas emissions in the US and Canada are underestimated relative to the values reported by these countries to the United Nations Framework Convention on Climate Change (UNFCCC) and used here as prior estimates, while coal emissions in China are overestimated. Wetland emissions in North America are much lower than in the mean WetCHARTs inventory used as prior estimate. Oil/gas emissions in the US increase over the 2010–2017 period but decrease in Canada and Europe. Our joint GOSAT+in situ inversion yields a global methane emission of 551 Tg a−1 averaged over 2010–2017 and a methane lifetime of 11.2 years against oxidation by tropospheric OH (86 % of the methane sink).

scholarly journals Information – based uncertainty decomposition in dual channel microwave remote sensing of soil moisture

2020 ◽  
Author(s):  
Bonan Li ◽  
Stephen P. Good
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Mutual Information ◽  
Microwave Remote Sensing ◽  
Reference Network ◽  
Brightness Temperatures ◽  
Dual Channel ◽  
The Us ◽  
In Situ Observations

Abstract. NASA's Soil Moisture Active-Passive (SMAP) mission characterizes global spatiotemporal patterns in surface soil moisture using dual L-band microwave retrievals of horizontal, TBh, and vertical, TBv, polarized microwave brightness temperatures through a modeled relationship between vegetation opacity and surface scattering albedo (i.e. tau-omega model). Although this model has been validated against in situ soil moisture measurements across sparse validations sites, there is lack of systematic characterization of where and why SMAP estimates deviate from the in situ observations. Here, soil moisture observations from the US Climate Reference Network are used within a mutual information framework to decompose the overall retrieval uncertainty from SMAPs Modified Dual Channel Algorithm (MDCA) into random uncertainty derived from raw data itself and model uncertainty derived from the model’s inherent structure. The results shown that, on average, 12 % of the uncertainty in SMAP soil moisture estimates is caused by the loss of information in the MDCA model itself while the remainder is induced by inadequacy of TBh and TBv observations. We find the fraction of algorithm induced uncertainty is negatively correlated (pearson r of −0.48) with correlations between in-situ observations and MDCA estimates. A decomposition of mutual information between TBh, TBv and MDCA soil moisture shows that on average 55 % of the mutual information is redundantly shared by TBh and TBv, while the information provided uniquely from both TBh and TBv is 15 %. The fraction of information redundantly provided by TBh and TBv was found to be tightly correlated (pearson r = −0.7) to how well the MDCA output correlated to in situ observations. Thus, MDCA overall quality improves as TBh and TBv provide more redundant information for the MDCA. This suggests the informational redundancy between these remotely sensed observations can be used as independent metric to assess the overall quality of algorithms using these data streams. This study provides a baseline approach that can also be applied to evaluate other remote sensing models and understand informational loss as satellite retrievals are translated to end user products.

scholarly journals Dependence of the Ice Water Content and Snowfall Rate on Temperature, Globally: Comparison of in Situ Observations, Satellite Active Remote Sensing Retrievals, and Global Climate Model Simulations

2017 ◽  
Vol 56 (1) ◽  
pp. 189-215 ◽  
Author(s):  
Andrew Heymsfield ◽  
Martina Krämer ◽  
Norman B. Wood ◽  
Andrew Gettelman ◽  
Paul R. Field ◽  
...  
Keyword(s):  
Water Content ◽  
Global Climate ◽  
Global Climate Model ◽  
Ice Cloud ◽  
In Situ Data ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
In Situ Observations ◽  
Ice Water

AbstractCloud ice microphysical properties measured or estimated from in situ aircraft observations are compared with global climate models and satellite active remote sensor retrievals. Two large datasets, with direct measurements of the ice water content (IWC) and encompassing data from polar to tropical regions, are combined to yield a large database of in situ measurements. The intention of this study is to identify strengths and weaknesses of the various methods used to derive ice cloud microphysical properties. The in situ data are measured with total water hygrometers, condensed water probes, and particle spectrometers. Data from polar, midlatitude, and tropical locations are included. The satellite data are retrieved from CloudSat/CALIPSO [the CloudSat Ice Cloud Property Product (2C-ICE) and 2C-SNOW-PROFILE] and Global Precipitation Measurement (GPM) Level2A. Although the 2C-ICE retrieval is for IWC, a method to use the IWC to get snowfall rates S is developed. The GPM retrievals are for snowfall rate only. Model results are derived using the Community Atmosphere Model (CAM5) and the Met Office Unified Model [Global Atmosphere 7 (GA7)]. The retrievals and model results are related to the in situ observations using temperature and are partitioned by geographical region. Specific variables compared between the in situ observations, models, and retrievals are the IWC and S. Satellite-retrieved IWCs are reasonably close in value to the in situ observations, whereas the models’ values are relatively low by comparison. Differences between the in situ IWCs and those from the other methods are compounded when S is considered, leading to model snowfall rates that are considerably lower than those derived from the in situ data. Anomalous trends with temperature are noted in some instances.

Long-term trends of surface reflectance derived from models, satellite and in-situ observations over polar areas

2020 ◽  
Author(s):  
Christian Lanconelli ◽  
Fabrizio Cappucci ◽  
Bernardo Mota ◽  
Nadine Gobron ◽  
Amelie Driemel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Kendall Test ◽  
Surface Radiation ◽  
In Situ Data ◽  
In Situ Observations

&lt;div&gt; &lt;p&gt;Nowadays, an increasingly amount of remote sensing and in-situ data are extending over decades. They contribute to increase the relevance of long-term studies aimed to deduce the mechanisms underlying the climate change dynamics. The aim of this study is to investigate the coherence between trends of different long-term climate related variables including the surface albedo (A) and land surface temperature (LST) as obtained by remote sensing platforms, models and in-situ observations.&amp;#160;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;Directional-hemispherical and bi-hemispherical broadband surface reflectances as derived from MODIS-MCD43 (v006) and MISR, and the analogous products of the Copernicus Global Land (CGLS) and C3S services derived from SPOT-VEGETATION, PROBA-V and AVHRR (v0 and v1), have been harmonized and, together with the ECMWF ERA-5 model, assessed with respect ground data taken over polar areas, over a temporal window spanning the last 20 years.&amp;#160;&amp;#160;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;The benchmark was established using in-situ measurements provided from the Baseline Surface Radiation Network (BSRN) over four Arctic and four Antarctic sites. The 1-minute resolution datasets of broadband upwelling and down-welling radiation, have been reduced to directional- and bi-hemispherical reflectances, with the same time scale of satellite products (1-day, 10-days, monthly).&amp;#160;&amp;#160;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;A similar approach was used to investigate the fitness for purpose of Land Surface Temperature as derived by MODIS (MOD11), ECMWF ERA-5, with respect to the brightness temperature derived using BSRN measurements over the longwave band.&amp;#160;&amp;#160;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;The entire temporal series are decomposed into seasonal and residual components, and then the presence of monotonic significant trends are assessed using the non-parametric Kendall test. Preliminary results shown a strong correlation between negative albedo trends and positive LST trends, especially in arctic regions.&amp;#160;&lt;/p&gt; &lt;/div&gt;

scholarly journals Reconstruction of the Parker spiral with the Reverse In situ data and MHD APproach - RIMAP

2020 ◽  
Author(s):  
Ruggero Biondo ◽  
Alessandro Bemporad ◽  
Andrea Mignone ◽  
Fabio Reale
Keyword(s):  
Interplanetary Medium ◽  
Small Scale ◽  
Reconstruction Technique ◽  
The Sun ◽  
Plasma Parameters ◽  
In Situ Data ◽  
Mhd Simulations ◽  
Solar Eruptions ◽  
In Situ Observations

The reconstruction of plasma parameters in the interplanetary medium is very important to understand the interplanetary propagation of solar eruptions and for Space Weather application purposes. Because only a few spacecraft are measuring in situ these parameters, reconstructions are currently performed by running complex numerical Magneto-hydrodynamic (MHD) simulations starting from remote sensing observations of the Sun. Current models apply full 3D MHD simulations of the corona or extrapolations of photospheric magnetic fields combined with and semiempirical relationships to derive the plasma parameters on a sphere centered on the Sun (inner boundary). The plasma is then propagated in the interplanetary medium up to the Earth’s orbit and beyond. Nevertheless, this approach requires significant theoretical and computational efforts, and the results are only in partial agreement with the in situ observations. In this paper we describe a new approach to this problem called RIMAP - Reverse In situ data and MHD APproach. The plasma parameters in the inner boundary at 0.1 AU are derived directly from the in situ measurements acquired at 1 AU, by applying a back reconstruction technique to remap them into the inner heliosphere. This remapping is done by using the Weber and Davies solar wind theoretical model to reconstruct the wind flowlines. The plasma is then re-propagated outward from 0.1 AU by running a MHD numerical simulation based on the PLUTO code. The interplanetary spiral reconstructions obtained with RIMAP are not only in a much better agreement with the in situ observations, but are also including many more small-scale longitudinal features in the plasma parameters that are not reproduced with the approaches developed so far.

scholarly journals Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan

2019 ◽  
Vol 11 (6) ◽  
pp. 628 ◽  
Author(s):  
Waheed Ullah ◽  
Guojie Wang ◽  
Gohar Ali ◽  
Daniel Tawia Hagan ◽  
Asher Bhatti ◽  
...  
Keyword(s):  
Primary Source ◽  
Tropical Rainfall Measuring Mission ◽  
Reanalysis Data ◽  
Climate Data ◽  
Satellite Precipitation ◽  
In Situ Data ◽  
The North ◽  
Precipitation Seasonality ◽  
In Situ Observations

Various state-of-the-art gridded satellite precipitation products (GPPs) have been derived from remote sensing and reanalysis data and are widely used in hydrological studies. An assessment of these GPPs against in-situ observations is necessary to determine their respective strengths and uncertainties. GPPs developed from satellite observations as a primary source were compared to in-situ observations, namely the Climate Hazard group Infrared Precipitation with Stations (CHIRPS), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA). These products were compared to in-situ data from 51 stations, spanning 1998–2016, across Pakistan on daily, monthly, annual and interannual time scales. Spatiotemporal climatology was well captured by all products, with more precipitation in the north eastern parts during the monsoon months and vice-versa. Daily precipitation with amount larger than 10 mm showed significant (95%, Kolmogorov-Smirnov test) agreement with the in-situ data, especially TMPA, followed by CHIRPS and MSWEP. At monthly scales, there were significant correlations (R) between the GPPs and in-situ records, suggesting similar dynamics; however, statistical metrics suggested that the performance of these products varies from north towards south. Temporal agreement on an interannual scale was higher in the central and southern parts which followed precipitation seasonality. TMPA performed the best, followed in order by CHIRPS, MSWEP and PERSIANN-CDR.

scholarly journals Emissions from natural gas and oil operations: The airborne METHANE-To-Go field campaign in the Persian/Arabian Gulf region

2020 ◽  
Author(s):  
Heidi Huntrieser ◽  
Anke Roiger ◽  
Daniel Sauer ◽  
Hans Schlager ◽  
Mariano Mertens ◽  
...  
Keyword(s):  
Global Warming ◽  
Natural Gas ◽  
Greenhouse Gas ◽  
Oil And Gas ◽  
Arabian Gulf ◽  
In Situ Measurements ◽  
Gulf Region ◽  
Gas Emissions ◽  
Arabian Gulf Region

&lt;p&gt;About 60% of global methane (CH&lt;sub&gt;4&lt;/sub&gt;) emissions are due to human activities. Since the Paris Agreement was signed in 2016, an increasing effort has been devoted to accelerate the greenhouse-gas-emissions mitigation. Afore in 2014, the Oil and Gas Climate Initiative (OGCI) formed, which is an international industry-led organization including 13 member companies from the oil and gas industry, representing 1/3 of the global operated oil and gas production. The Environmental Defense Fund (EDF) and United Nations Environment Programme (UNEP) funded project METHANE-To-Go aims to focus on trace gas emissions from the natural gas and oil operations in the Persian/Arabian Gulf region, a wealthy region which contains about 50% of the world&amp;#180;s oil reserves. The project is coordinated by the Deutsches Zentrum f&amp;#252;r Luft- und Raumfahrt (DLR) and envisages to carry out airborne in-situ measurements with the German Deutsches Zentrum f&amp;#252;r Luft- und Raumfahrt (DLR) Falcon-20 in autumn 2020 in cooperation with local OGCI partners.&lt;/p&gt;&lt;p&gt;The flaring, venting and combustion processes produce large amounts of CH&lt;sub&gt;4&lt;/sub&gt;, a greenhouse gas that is ~84 times more potent than CO&lt;sub&gt;2&lt;/sub&gt; (measured over a 20-year period) and in focus of current mitigation strategies trying to reduce global warming. However, there is a huge lack of detailed CH&lt;sub&gt;4&lt;/sub&gt; measurements worldwide and especially from the Gulf region. The contribution from this region to the global CH&lt;sub&gt;4&lt;/sub&gt; mass balance is presently unknown. Furthermore, recently a first global satellite-derived SO&lt;sub&gt;2&lt;/sub&gt; emissions inventory was established based on measurements with the Ozone Monitoring Instrument (OMI) on the NASA Aura satellite showing a number of SO&lt;sub&gt;2&lt;/sub&gt; hot spots in the Persian/Arabian Gulf region. The Middle East region was high-lighted as the region with the most missing SO&lt;sub&gt;2&lt;/sub&gt; sources compared to reported sources in the global emission inventories. The petroleum industry operations are mainly responsible for these emissions, since high amounts of H&lt;sub&gt;2&lt;/sub&gt;S are trapped in oil and gas deposits and released during extraction. In recent years, the air quality in this region has worsened dramatically and concurrently global warming is especially strong.&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;The DLR Institute of Atmospheric Physics plan the performance of airborne in-situ measurements to probe the isolated, outstanding emission plumes from the different CH&lt;sub&gt;4&lt;/sub&gt; and SO&lt;sub&gt;2&lt;/sub&gt; sources in the southern part of the Gulf region as mentioned above. A novel dual Quantum Cascade Laser (QCL) instrument based on laser absorption spectroscopy will be deployed to measure CH&lt;sub&gt;4&lt;/sub&gt; and CO, and related trace gases as CO&lt;sub&gt;2&lt;/sub&gt; and C&lt;sub&gt;2&lt;/sub&gt;H&lt;sub&gt;6&lt;/sub&gt;, which can be used to distinguish between different CH&lt;sub&gt;4&lt;/sub&gt; sources (flaring, venting and combustion). An ion-trap chemical ionization mass spectrometer (IT-CIMS) is foreseen for the measurements of SO&lt;sub&gt;2&lt;/sub&gt;. Both instruments operate with a high precision/accuracy and a temporal resolution of 0.5 to 1s, which covers a horizontal distance of roughly 50-200 m during the flight. Measurements of further trace species are also foreseen (e.g. NO, NO&lt;sub&gt;y&lt;/sub&gt;, and aerosols) and simulations with particle dispersion models for flight planning and post analyses (HYSPLIT and the EMAC related model MECO(n)). Furthermore, satellite validation is envisaged with the TROPOMI instrument on Sentinel-5P (focus on CH&lt;sub&gt;4&lt;/sub&gt; and SO&lt;sub&gt;2&lt;/sub&gt;).&lt;/p&gt;

scholarly journals Processing of Ice Cloud In Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties, and Efforts toward Consistency

2017 ◽  
Vol 58 ◽  
pp. 11.1-11.33 ◽  
Author(s):  
Greg M. McFarquhar ◽  
Darrel Baumgardner ◽  
Aaron Bansemer ◽  
Steven J. Abel ◽  
Jonathan Crosier ◽  
...  
Keyword(s):  
Critical Role ◽  
Bulk Water ◽  
Process Data ◽  
Ice Cloud ◽  
In Situ Data ◽  
Cloud Properties ◽  
Imaging Probes ◽  
In Situ Observations ◽  
Processing Algorithms

Abstract In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.

scholarly journals Theoretical study of mixing in liquid clouds – Part 1: Classical concepts

2016 ◽  
Vol 16 (14) ◽  
pp. 9235-9254 ◽  
Author(s):  
Alexei Korolev ◽  
Alex Khain ◽  
Mark Pinsky ◽  
Jeffrey French
Keyword(s):  
Size Distribution ◽  
Theoretical Study ◽  
Classical Concept ◽  
Primary Stage ◽  
Convective Clouds ◽  
Functional Relationships ◽  
In Situ Data ◽  
Microphysical Parameters ◽  
In Situ Observations

Abstract. The present study considers final stages of in-cloud mixing in the framework of classical concept of homogeneous and extreme inhomogeneous mixing. Simple analytical relationships between basic microphysical parameters were obtained for homogeneous and extreme inhomogeneous mixing based on the adiabatic consideration. It was demonstrated that during homogeneous mixing the functional relationships between the moments of the droplets size distribution hold only during the primary stage of mixing. Subsequent random mixing between already mixed parcels and undiluted cloud parcels breaks these relationships. However, during extreme inhomogeneous mixing the functional relationships between the microphysical parameters hold both for primary and subsequent mixing. The obtained relationships can be used to identify the type of mixing from in situ observations. The effectiveness of the developed method was demonstrated using in situ data collected in convective clouds. It was found that for the specific set of in situ measurements the interaction between cloudy and entrained environments was dominated by extreme inhomogeneous mixing.

scholarly journals In situ snow water equivalent observations in the US Arctic

2012 ◽  
Vol 44 (1) ◽  
pp. 21-34 ◽  
Author(s):  
Svetlana Stuefer ◽  
Douglas L. Kane ◽  
Glen E. Liston
Keyword(s):  
Snow Water Equivalent ◽  
Winter Precipitation ◽  
Local Scale ◽  
Arctic Alaska ◽  
The Us ◽  
Snow Water ◽  
In Situ Observations ◽  
Best Fit ◽  
Collection Methods

This paper summarizes 12 years of snow water equivalent (SWE) observations collected in the data-sparse region of Arctic Alaska, United States. The in situ observations are distributed across a 200 × 300 km domain that includes the Kuparuk River watershed from the Brooks Range to the Beaufort Sea coast. Data collection methods and analyses were classified to distinguish between snow observation sites representing regional- and local-scale variability. Average SWE for the entire domain ranges from 92 mm in 2008 to 148 mm in 2011. Regional end-of-winter SWE indicates that both the extreme high SWE in 2009 and 2011 and the extreme low SWE in 2008 occurred during recent and alternating years, suggesting the limitations of 12 years of data for detecting SWE trends. By assimilating the observational datasets into SnowModel, hourly 100 m gridded SWE distributions for the central Alaska Arctic were created to provide a best-fit to the observations where and when they occur. The model simulations highlight how observed SWE data can be used as a surrogate for the more problematic winter precipitation measurements. The resulting SWE distributions are readily available to support ecological and hydrologic studies in this region.

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