3D forest model-assisted validation of the Sentinel-2 SNAP fAPAR product

2020 ◽  
Author(s):  
Niall Origo ◽  
Joanne Nightingale ◽  
Kim Calders ◽  
Mathias Disney
Keyword(s):  
Energy Balance ◽  
Carbon Cycle ◽  
Global Climate ◽  
Data Uncertainty ◽  
Plant Canopy ◽  
Validation Data ◽  
Uncertainty Estimates ◽  
The Impact ◽  
Sentinel 2

<p>fAPAR is a radiometric quantity describing the fraction of photosynthetically active radiation (PAR) absorbed by a plant canopy. It is an important component of carbon cycle and energy balance models and has been named as one of the 50 Global Climate Observing System (GCOS) essential climate variables (ECVs). Space agencies such as the ESA and NASA produce satellite fAPAR products in order to address the need for spatially explicit global data to address environmental and climate change issues. Given the derived nature of satellite fAPAR products it is essential to independently verify the results they produce. In order to do this, validation sites (or networks of sites) are needed that directly correspond to the measurands. Further to this, in order to understand divergences between product and validation data, uncertainty information should be provided with all measurement results.</p><p>The canopy radiative transfer models which are used in satellite-derived fAPAR products implement simplistic assumptions about the state of the plant canopy and illumination conditions in order to retrieve an fAPAR estimate in a computationally feasible time. This contribution assesses the impact of the assumptions made by the Sentinel-2 SNAP-derived fAPAR and includes it in a validation of the product over a field site (Wytham Woods, UK), which also has concurrent fAPAR measurements. This is achieved using a 3D model of Wytham Woods which is used to simulate biases associated with specific assumption types. These are used to convert the in situ measurements to the same quantity assumed by the satellite product. The measurement network which provides the fAPAR data is also traceable to SI through sensor calibrations and has associated uncertainty estimates. To our knowledge, these latter points have not been implemented in the biophysical product validation literature, which may explain some of the large discrepancies seen between validation and satellite-derived fAPAR data.</p><p>The ultimate aim of this work is to demonstrate a validation framework for derived biophysical variables such as fAPAR which properly considers the quantity estimated by the satellite and that measured by the in situ sensors, whilst providing metrologically derived uncertainties on the in situ data. This will help to properly inform users as to the quality of the data and determine whether the GCOS requirements set for fAPAR are attainable, ultimately improving carbon cycle and energy balance estimates.</p>

scholarly journals The impact of the 2015/2016 El Niño on global photosynthesis using satellite remote sensing

2018 ◽  
Vol 373 (1760) ◽  
pp. 20170409 ◽  
Author(s):  
Xiangzhong Luo ◽  
Trevor F. Keenan ◽  
Joshua B. Fisher ◽  
Juan-Carlos Jiménez-Muñoz ◽  
Jing M. Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Cycle ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Carbon Sink ◽  
Global Climate ◽  
Prognostic Models ◽  
Positive Anomaly ◽  
The Impact

The El Niño-Southern Oscillation exerts a large influence on global climate regimes and on the global carbon cycle. Although El Niño is known to be associated with a reduction of the global total land carbon sink, results based on prognostic models or measurements disagree over the relative contribution of photosynthesis to the reduced sink. Here, we provide an independent remote sensing-based analysis on the impact of the 2015–2016 El Niño on global photosynthesis using six global satellite-based photosynthesis products and a global solar-induced fluorescence (SIF) dataset. An ensemble of satellite-based photosynthesis products showed a negative anomaly of −0.7 ± 1.2 PgC in 2015, but a slight positive anomaly of 0.05 ± 0.89 PgC in 2016, which when combined with observations of the growth rate of atmospheric carbon dioxide concentrations suggests that the reduction of the land residual sink was likely dominated by photosynthesis in 2015 but by respiration in 2016. The six satellite-based products unanimously identified a major photosynthesis reduction of −1.1 ± 0.52 PgC from savannahs in 2015 and 2016, followed by a highly uncertain reduction of −0.22 ± 0.98 PgC from rainforests. Vegetation in the Northern Hemisphere enhanced photosynthesis before and after the peak El Niño, especially in grasslands (0.33 ± 0.13 PgC). The patterns of satellite-based photosynthesis ensemble mean were corroborated by SIF, except in rainforests and South America, where the anomalies of satellite-based photosynthesis products also diverged the most. We found the inter-model variation of photosynthesis estimates was strongly related to the discrepancy between moisture forcings for models. These results highlight the importance of considering multiple photosynthesis proxies when assessing responses to climatic anomalies. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

scholarly journals Retrieving Total and Inorganic Suspended Sediments in Amazon Floodplain Lakes: A Multisensor Approach

2019 ◽  
Vol 11 (15) ◽  
pp. 1744 ◽  
Author(s):  
Daniel Maciel ◽  
Evlyn Novo ◽  
Lino Sander de Carvalho ◽  
Cláudio Barbosa ◽  
Rogério Flores Júnior ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Correction ◽  
Suspended Sediments ◽  
Floodplain Lakes ◽  
Empirical Modeling ◽  
Landsat 8 ◽  
Amazon Floodplain ◽  
The Impact ◽  
Sentinel 2

Remote sensing imagery are fundamental to increasing the knowledge about sediment dynamics in the middle-lower Amazon floodplains. Moreover, they can help to understand both how climate change and how land use and land cover changes impact the sediment exchange between the Amazon River and floodplain lakes in this important and complex ecosystem. This study investigates the suitability of Landsat-8 and Sentinel-2 spectral characteristics in retrieving total (TSS) and inorganic (TSI) suspended sediments on a set of Amazon floodplain lakes in the middle-lower Amazon basin using in situ Remote Sensing Reflectance (Rrs) measurements to simulate Landsat 8/OLI (Operational Land Imager) and Sentinel 2/MSI (Multispectral Instrument) bands and to calibrate/validate several TSS and TSI empirical algorithms. The calibration was based on the Monte Carlo Simulation carried out for the following datasets: (1) All-Dataset, consisting of all the data acquired during four field campaigns at five lakes spread over the lower Amazon floodplain (n = 94); (2) Campaign-Dataset including samples acquired in a specific hydrograph phase (season) in all lakes. As sample size varied from one season to the other, n varied from 18 to 31; (3) Lake-Dataset including samples acquired in all seasons at a given lake with n also varying from 17 to 67 for each lake. The calibrated models were, then, applied to OLI and MSI scenes acquired in August 2017. The performance of three atmospheric correction algorithms was also assessed for both OLI (6S, ACOLITE, and L8SR) and MSI (6S, ACOLITE, and Sen2Cor) images. The impact of glint correction on atmosphere-corrected image performance was assessed against in situ glint-corrected Rrs measurements. After glint correction, the L8SR and 6S atmospheric correction performed better with the OLI and MSI sensors, respectively (Mean Absolute Percentage Error (MAPE) = 16.68% and 14.38%) considering the entire set of bands. However, for a given single band, different methods have different performances. The validated TSI and TSS satellite estimates showed that both in situ TSI and TSS algorithms provided reliable estimates, having the best results for the green OLI band (561 nm) and MSI red-edge band (705 nm) (MAPE < 21%). Moreover, the findings indicate that the OLI and MSI models provided similar errors, which support the use of both sensors as a virtual constellation for the TSS and TSI estimate over an Amazon floodplain. These results demonstrate the applicability of the calibration/validation techniques developed for the empirical modeling of suspended sediments in lower Amazon floodplain lakes using medium-resolution sensors.

scholarly journals Analyzing the Uncertainty of Degree Confluence Project for Validating Global Land-Cover Maps Using Reference Data-Based Classification Schemes

2020 ◽  
Vol 12 (16) ◽  
pp. 2589
Author(s):  
Tana Qian ◽  
Tsuguki Kinoshita ◽  
Minoru Fujii ◽  
Yuhai Bao
Keyword(s):  
Land Cover ◽  
Reference Data ◽  
Data Uncertainty ◽  
Validation Data ◽  
Classification Schemes ◽  
Reference Information ◽  
Global Land Cover ◽  
Global Land ◽  
Land Cover Maps ◽  
The Impact

Global land-cover products play an important role in assisting the understanding of climate-related changes and the assessment of progress in the implementation of international initiatives for the mitigation of, and adaption to, climate change. However, concerns over the accuracies of land-cover products remain, due to the issue of validation data uncertainty. The volunteer-based Degree Confluence Project (DCP) was created in 1996, and it has been used to provide useful ground-reference information. This study aims to investigate the impact of DCP-based validation data uncertainty and the thematic issues on map accuracies. We built a reference dataset based on the DCP-interpreted dataset and applied a comparison for three existing global land-cover maps and DCP dataset-based probability maps under different classification schemes. The results of the obtained confusion matrices indicate that the uncertainty, including the number of classes and the confusion in mosaic classes, leads to a decrease in map accuracy. This paper proposes an informative classification scheme that uses a matrix structure of unaggregated land-cover and land-use classes, and has the potential to assist in the land-cover interpretation and validation processes. The findings of this study can potentially serve as a guide to select reference data and choose/define appropriate classification schemes.

scholarly journals The impact of sensors for satellite derived bathymetry within the Canadian Arctic

GEOMATICA ◽  
2020 ◽  
Vol 74 (2) ◽  
pp. 46-64
Author(s):  
Ryan Ahola ◽  
René Chénier ◽  
Mesha Sagram ◽  
Bradley Horner
Keyword(s):  
Optical Sensors ◽  
Landsat 8 ◽  
Sea Floor ◽  
Arctic Regions ◽  
Canadian Context ◽  
Multiple Band ◽  
Survey Accuracy ◽  
The Impact ◽  
Sentinel 2

Canada’s coastline presents challenges for charting. Within Arctic regions, in situ surveying presents risks to surveyors, is time consuming and costly. To better meet its mandate, the Canadian Hydrographic Service (CHS) has been investigating the potential of remote sensing to complement traditional charting techniques. Much of this work has focused on evaluating the effectiveness of empirical satellite derived bathymetry (SDB) techniques within the Canadian context. With greater knowledge of applying SDB techniques within Canadian waters, CHS is now interested in understanding how characteristics of optical sensors can impact SDB results. For example, how does the availability of different optical bands improve or hinder SDB estimates? What is the impact of spatial resolution on SDB accuracy? Do commercial satellites offer advantages over freely available data? Through application of a multiple band modelling technique to WorldView-2, Pléiades, PlanetScope, SPOT, Sentinel-2, and Landsat-8 imagery obtained over Cambridge Bay, Nunavut, this paper provides insight into these questions via comparisons with in situ survey data. Result highlights in the context of these questions include the following: Similarities between sensors: Overall linear error at 90% (LE90) results for each sensor ranged from 0.88 to 1.91 m relative to in situ depths, indicating consistency in the accuracy of SDB estimates from the examined satellites. Most estimates achieved Category of Zone of Confidence level C accuracy, the suggested minimum survey accuracy level for incorporating SDB information into navigational charts. SDB coverage: Between sensors, differences in the area of the sea floor that could be measured by SDB were apparent, as were differences in the ability of each sensor to properly represent spatial bathymetry characteristics. Sensor importance: Though relationships between SDB accuracy and sensor resolution were found, significant advantages or disadvantages for particular sensors were not identified, suggesting that other factors may play a more important role for SDB image selection (e.g., sea floor visibility, sediments, waves). Findings from this work will help inform SBD planning activities for hydrographic offices and SDB researchers alike.

scholarly journals Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France)

2017 ◽  
Vol 21 (11) ◽  
pp. 5693-5708 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Tiphaine Tallec ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Surface ◽  
Agricultural Landscapes ◽  
Surface Model ◽  
Spatial And Temporal Variability ◽  
Area Index ◽  
The Impact ◽  
Sentinel 2

Abstract. Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA) land surface model included in the EXternalized SURface (SURFEX) modeling platform. The study focuses on the effect of the leaf area index (LAI) spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m). The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km). An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE). Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE) in the simulated evapotranspiration. This finding is attributable to a better description of LAI evolution processes with Formosat-2 data, which further modify soil water content and drainage of soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels with simulations using Formosat-2 data in comparison to the reference simulation values. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.

High-resolution assessment of the Valgu event: conodont diversity and δ18Ophos during the early Telychian (Silurian) in the Baltic Basin

2020 ◽  
Author(s):  
Monica Alejandra Gomez Correa ◽  
Emilia Jarochowska ◽  
Peep Männik ◽  
Axel Munnecke ◽  
Michael Joachimski
Keyword(s):  
Carbon Cycle ◽  
Sea Level ◽  
Global Climate ◽  
Baltic Basin ◽  
Sea Level Fluctuations ◽  
Core Section ◽  
Storm Wave ◽  
The Baltic ◽  
A Minor ◽  
The Impact

&lt;p&gt;The influence of global climate and oceanographic system dynamics over biological patterns throughout Earth&amp;#8217;s history is one of the main concerns in paleobiology. Periods that record changes in biodiversity of various magnitude are of particular interest in this field. Previous studies of major Silurian bioevents (e.g. Ireviken, Mulde and Lau) suggest that these events affected different faunas and have been correlated with positive carbon isotope (&amp;#948;&lt;sup&gt;13&lt;/sup&gt;C&lt;sub&gt;carb&lt;/sub&gt;) excursions and positive shifts in oxygen isotopes (&amp;#948;&lt;sup&gt;18&lt;/sup&gt;O&lt;sub&gt;phos&lt;/sub&gt;) ratios, suggesting there was a disturbance in the carbon cycle, a drop in temperature, and potential glaciations. However, the impact of the biological events has not been fully assessed, and the influence of climate change remains unclear.&lt;/p&gt;&lt;p&gt;Here, we focus on the Valgu event, a minor episode of proposed environmental and faunistic changes in the early Telychian, which has been recognized in Baltica and Laurentia paleocontinents by changes in conodont succession and a positive excursion in &amp;#948;&lt;sup&gt;13&lt;/sup&gt;C&lt;sub&gt;carb&lt;/sub&gt;. In this study, we assess a limestone-marl alternation core section in Estonia deposited below the storm wave base during the Valgu event. We test for a substantial decrease in the biodiversity of conodont communities, for extent perturbation in the carbon cycle, manifest in a positive &amp;#948;&lt;sup&gt;13&lt;/sup&gt;C&lt;sub&gt;carb&lt;/sub&gt; excursion, and an abrupt positive &amp;#948;&lt;sup&gt;18&lt;/sup&gt;O&lt;sub&gt;phos&lt;/sub&gt; shift, which might be indicative of rapid cooling and a rapid sea-level fall typical for glacio-eustatic cycles. To this aim, we measured bulk-rock &amp;#948;&lt;sup&gt;13&lt;/sup&gt;C&lt;sub&gt;carb&lt;/sub&gt; as well as &amp;#948;&lt;sup&gt;18&lt;/sup&gt;O&lt;sub&gt;phos&lt;/sub&gt; in monogeneric conodont samples and analyzed the conodont diversity from the event interval.&lt;/p&gt;&lt;p&gt;The lower part of the investigated section is characterized by shallow-water bioclastic limestones containing green algae. On top of this facies, a pronounced hardground indicates a gap in deposition and marks the boundary between the bioclastic limestones and the overlying sediments composed of nodular limestones and marls, which were deposited below the storm wave base. They show a positive carbon shift of ca. 1.4 &amp;#8240; during the Valgu interval, but no indication of an extreme change in the conodont biodiversity is evident. Likewise, the &amp;#948;&lt;sup&gt;18&lt;/sup&gt;O&lt;sub&gt;phos&lt;/sub&gt; in conodonts remains constant in the section, arguing against cooling or glacially-driven sea-level fluctuations as drivers for the observed changes.&lt;/p&gt;

Satellite-derived shorelines reveal fascinating dynamics for the last three decades on Danube Delta coast

2021 ◽  
Author(s):  
Florin Tatui ◽  
Georgiana Anghelin ◽  
Sorin Constantin
Keyword(s):  
Satellite Images ◽  
High Energy ◽  
Data Availability ◽  
Danube Delta ◽  
Dune System ◽  
Temporal Scales ◽  
Wide Range ◽  
The Impact ◽  
Sentinel 2

&lt;p&gt;Shoreline, as the interface between the upper shoreface and the beach-dune system, is sensitive to all changes from both the underwater and sub-aerial parts of the beach at a wide range of temporal scales (seconds to decades), making it a good indicator for coastal health. While more traditional techniques of shoreline monitoring present some shortcomings (low temporal resolution for photointerpretation, reduced spatial extension for video-based techniques, high costs for DGPS in-situ data acquisition), freely available satellite images can provide information for large areas (tens/hundreds of km) at very good temporal scales (days).&lt;/p&gt;&lt;p&gt;We employed a shoreline detection workflow for the dynamic environment of the Danube Delta coast (Black Sea). We focused on an index-based approach using the Automated Water Extraction Index (AWEI). A fully automated procedure was deployed for data processing and the waterline was estimated at sub-pixel level with an adapted image thresholding technique. For validation purposes, 5 Sentinel-2 and 5 Landsat based results were compared with both in-situ (D)GPS measurements and manually digitized shoreline positions from very high-resolution satellite images (Pleiades &amp;#8211; 0.5 m and Spot 7 &amp;#8211; 1.5 m). The overall accuracy of the methodology, expressed as mean absolute error, was found to be of approximately 7.5 m for Sentinel-2 and 4.7 m for Landsat data, respectively.&lt;/p&gt;&lt;p&gt;More than 200 Landsat (5 and 8) and Sentinel-2 images were processed and the corresponding satellite-derived shorelines between 1990 and 2020 were analysed for the whole Romanian Danube Delta coast (130 km). This high number of shorelines allowed us the discrimination of different patterns of coastline dynamic and behaviour which could not have been possible using usual surveying techniques: the extent of accumulation areas induced by the 2005-2006 historical river floods, the impact of different high-energy storms and the subsequent beach recovery after these events, the alongshore movement of erosional processes in accordance with the dominant direction of longshore sediment transport, multi-annual differences in both erosional and accumulation trends. Moreover, a very important result of our analysis is the zonation of Danube Delta coast based on multi-annual trends of shoreline dynamics at finer alongshore spatial resolution than before. This has significant implications for future studies dealing with different scenarios of Danube Delta response to projected sea level rise and increased storminess.&lt;/p&gt;&lt;p&gt;The presented approach and resulting products offer optimal combination of data availability, accuracy and frequency necessary to meet the monitoring and management needs of the increasing number of stakeholders involved in the coastal zone protection activities.&lt;/p&gt;

scholarly journals Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design

2017 ◽  
Vol 14 (20) ◽  
pp. 4755-4766 ◽  
Author(s):  
Thomas Kaminski ◽  
Peter Julian Rayner
Keyword(s):  
Carbon Cycle ◽  
Network Design ◽  
Observational Data ◽  
Data Streams ◽  
Surface Fluxes ◽  
Modelling Framework ◽  
Independent Information ◽  
The Impact ◽  
Global Carbon

Abstract. Various observational data streams have been shown to provide valuable constraints on the state and evolution of the global carbon cycle. These observations have the potential to reduce uncertainties in past, current, and predicted natural and anthropogenic surface fluxes. In particular such observations provide independent information for verification of actions as requested by the Paris Agreement. It is, however, difficult to decide which variables to sample, and how, where, and when to sample them, in order to achieve an optimal use of the observational capabilities. Quantitative network design (QND) assesses the impact of a given set of existing or hypothetical observations in a modelling framework. QND has been used to optimise in situ networks and assess the benefit to be expected from planned space missions. This paper describes recent progress and highlights aspects that are not yet sufficiently addressed. It demonstrates the advantage of an integrated QND system that can simultaneously evaluate a multitude of observational data streams and assess their complementarity and redundancy.

The key role of aerosol-radiation-interactions on cloud formation and precipitation in the Amazon

2021 ◽  
Author(s):  
Lixia Liu ◽  
Yafang Cheng ◽  
Siwen Wang ◽  
Chao Wei ◽  
Mira Pöhlker ◽  
...  
Keyword(s):  
Energy Balance ◽  
Radiative Forcing ◽  
Amazon Basin ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Cloud Formation ◽  
Emission Rates ◽  
Liquid Water Path ◽  
Aerosol Loading ◽  
The Impact

&lt;p&gt;Biomass burning (BB) aerosols can influence regional and global climate through interactions with radiation, clouds, and precipitation. Here, we investigate the impact of BB aerosols on the energy balance and hydrological cycle over the Amazon Basin during the dry season. We performed WRF-Chem simulations for a range of different BB emission scenarios to explore and characterize nonlinear effects and individual contributions from aerosol&amp;#8211;radiation interactions (ARIs) and aerosol&amp;#8211;cloud interactions (ACIs). For scenarios representing the lower and upper limits of BB emission estimates for recent years (2002&amp;#8211;2016), we obtained total regional BB aerosol radiative forcings of -0.2 and 1.5Wm&lt;sup&gt;-2&lt;/sup&gt;, respectively, showing that the influence of BB aerosols on the regional energy balance can range from modest cooling to strong warming. We find that ACIs dominate at low BB emission rates and low aerosol optical depth (AOD), leading to an increased cloud liquid water path (LWP) and negative radiative forcing, whereas ARIs dominate at high BB emission rates and high AOD, leading to a reduction of LWP and positive radiative forcing. In all scenarios, BB aerosols led to a decrease in the frequency of occurrence and rate of precipitation, caused primarily by ACI effects at low aerosol loading and by ARI effects at high aerosol loading. Overall, our results show that ACIs tend to saturate at high aerosol loading, whereas the strength of ARIs continues to increase and plays a more important role in highly polluted episodes and regions. This should hold not only for BB aerosols over the Amazon, but also for other light-absorbing aerosols such as fossil fuel combustion aerosols in industrialized and densely populated areas. The importance of ARIs at high aerosol loading highlights the need for accurately characterizing aerosol optical properties in the investigation of aerosol effects on clouds, precipitation, and climate.&lt;/p&gt;

scholarly journals Cross-track Infrared Sounder (CrIS) satellite observations of tropospheric ammonia

2015 ◽  
Vol 8 (3) ◽  
pp. 1323-1336 ◽  
Author(s):  
M. W. Shephard ◽  
K. E. Cady-Pereira
Keyword(s):  
Boundary Layer ◽  
Central Valley ◽  
Satellite Observations ◽  
Retrieval Algorithm ◽  
Mountainous Regions ◽  
Uncertainty Estimates ◽  
Cross Track ◽  
The Impact ◽  
Retrieval Bias

Abstract. Observations of atmospheric ammonia are important in understanding and modelling the impact of ammonia on both human health and the natural environment. We present a detailed description of a robust retrieval algorithm that demonstrates the capabilities of utilizing Cross-track Infrared Sounder (CrIS) satellite observations to globally retrieval ammonia concentrations. Initial ammonia retrieval results using both simulated and real observations show that (i) CrIS is sensitive to ammonia in the boundary layer with peak vertical sensitivity typically around ~ 850–750 hPa (~ 1.5 to 2.5 km), which can dip down close to the surface (~ 900 hPa) under ideal conditions, (ii) it has a minimum detection limit of ~ 1 ppbv (peak profile value typically at the surface), and (iii) the information content can vary significantly with maximum values of ~ 1 degree-of-freedom for signal. Comparisons of the retrieval with simulated "true" profiles show a small positive retrieval bias of 6% with a standard deviation of ~ ± 20% (ranging from ± 12 to ± 30% over the vertical profile). Note that these uncertainty estimates are considered as lower bound values as no potential systematic errors are included in the simulations. The CrIS NH3 retrieval applied over the Central Valley in CA, USA, demonstrates that CrIS correlates well with the spatial variability of the boundary layer ammonia concentrations seen by the nearby Quantum Cascade-Laser (QCL) in situ surface and the Tropospheric Emission Spectrometer (TES) satellite observations as part of the DISCOVER-AQ campaign. The CrIS and TES ammonia observations show quantitatively similar retrieved boundary layer values that are often within the uncertainty of the two observations. Also demonstrated is CrIS's ability to capture the expected spatial distribution in the ammonia concentrations, from elevated values in the Central Valley from anthropogenic agriculture emissions, to much lower values in the unpolluted or clean surrounding mountainous regions. These initial results demonstrate the capabilities of the CrIS satellite to measure ammonia.

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