scholarly journals A framework for comparing remotely sensed and in-situ CO<sub>2</sub> concentrations

2008 ◽  
Vol 8 (1) ◽  
pp. 1549-1588 ◽  
Author(s):  
R. Macatangay ◽  
T. Warneke ◽  
C. Gerbig ◽  
S. Körner ◽  
R. Ahmadov ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Remotely Sensed ◽  
Infrared Spectrometry ◽  
Remotely Sensed Data ◽  
Solar Absorption ◽  
Mixing Ratios ◽  
In Situ Data ◽  
Global Calibration

Abstract. A framework that allows validating CO2 column averaged volume mixing ratios (VMRs) retrieved from ground-based solar absorption measurements using Fourier transform infrared spectrometry (FTS) against measurements made in-situ (such as from aircrafts and tall towers) has been developed. Since in-situ measurements are done frequently and at high accuracy on the global calibration scale, linking this scale with FTS total column retrievals ultimately provides a calibration scale for remote sensing. FTS, tower and aircraft data were analyzed from measurements during the CarboEurope Regional Experiment Strategy (CERES) from May to June 2005 in Biscarrosse, France. Carbon dioxide VMRs from the MetAir Dimona aircraft, the TM3 global transport model and Observations of the Middle Stratosphere (OMS) balloon based experiments were combined and integrated to compare with FTS measurements. The comparison agrees fairly well with differences resulting from the spatial variability of CO2 around the FTS as measured by the aircraft. Additionally, the Stochastic Time Inverted Lagrangian Transport (STILT) model served as a "transfer standard" between the in-situ data measured at a co-located tower and the remotely sensed data from the FTS. The variability of carbon dioxide VMRs was modeled well by STILT with differences coming partly from uncertainties in the spatial variation of carbon dioxide.

scholarly journals A framework for comparing remotely sensed and in-situ CO<sub>2</sub> concentrations

2008 ◽  
Vol 8 (9) ◽  
pp. 2555-2568 ◽  
Author(s):  
R. Macatangay ◽  
T. Warneke ◽  
C. Gerbig ◽  
S. Körner ◽  
R. Ahmadov ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Remotely Sensed ◽  
Infrared Spectrometry ◽  
Solar Absorption ◽  
Mixing Ratios ◽  
Global Calibration ◽  
Carbon Dioxide Concentrations ◽  
Made In

Abstract. A framework has been developed that allows validating CO2 column averaged volume mixing ratios (VMRs) retrieved from ground-based solar absorption measurements using Fourier transform infrared spectrometry (FTS) against measurements made in-situ (such as from aircrafts and tall towers). Since in-situ measurements are done frequently and at high accuracy on the global calibration scale, linking this scale with FTS total column retrievals ultimately provides a calibration scale for remote sensing. FTS, tower and aircraft data were analyzed from measurements during the CarboEurope Regional Experiment Strategy (CERES) from May to June 2005 in Biscarrosse, France. Carbon dioxide VMRs from the MetAir Dimona aircraft, the TM3 global transport model and Observations of the Middle Stratosphere (OMS) balloon based experiments were combined and integrated to compare with the FTS measurements. The comparison allows for calibrating the retrieved carbon dioxide VMRs from the FTS. The Stochastic Time Inverted Lagrangian Transport (STILT) model was then utilized to identify differences in surface influence regions or footprints between the FTS and the aircraft CO2 concentrations. Additionally, the STILT model was used to compare carbon dioxide concentrations from a tall tower situated in close proximity to the FTS station. The STILT model was then modified to produce column concentrations of CO2 to facilitate comparison with the FTS data. These comparisons were additionally verified by using the Weather Research and Forecasting – Vegetation Photosynthesis and Respiration Model (WRF-VPRM). The differences between the model-tower and the model-FTS were then used to calculate an effective bias of approximately −2.5 ppm between the FTS and the tower. This bias is attributed to the scaling factor used in the FTS CO2 data, which was to a large extent derived from the aircraft measurements made within a 50 km distance from the FTS station: spatial heterogeneity of carbon dioxide in the coastal area caused a low bias in the FTS calibration. Using STILT for comparing remotely sensed CO2 data with tower measurements of carbon dioxide and quantifying this comparison by means of an effective bias, provided a framework or a "transfer standard" that allowed validating the FTS retrievals versus measurements made in-situ.

scholarly journals New approach to evaluate satellite derived XCO<sub>2</sub> over oceans by integrating ship and aircraft observations

2020 ◽  
Author(s):  
Astrid Müller ◽  
Hiroshi Tanimoto ◽  
Takafumi Sugita ◽  
Toshinobu Machida ◽  
Shin-ichiro Nakaoka ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Satellite Observations ◽  
Reference Dataset ◽  
Model Calculations ◽  
New Approach ◽  
Mixing Ratios ◽  
In Situ Data

Abstract. Satellite observations provide spatially-resolved global estimates of column-averaged mixing ratios of CO2 (XCO2) over the Earth's surface. The accuracy of these datasets can be validated against reliable standards in some areas, but other areas remain inaccessible. To date, limited reference data over oceans hinders successful uncertainty quantification or bias correction efforts, and precludes reliable conclusions about changes in the carbon cycle in some regions. Here, we propose a new approach to analyze and evaluate seasonal, interannual and latitudinal variations of XCO2 over oceans by integrating cargo-ship (SOOP, Ship Of Opportunity) and commercial aircraft (CONTRAIL, Comprehensive Observation Network for Trace gases by Airliner) observations with the aid of state-of-the art atmospheric chemistry-transport model calculations. The consistency of the in situ based column-averaged CO2 dataset (in situ XCO2) with satellite estimates was analyzed over the Western Pacific between 2014 and 2017, and its utility as reference dataset evaluated. Our results demonstrate that the new dataset accurately captures seasonal and interannual variations of CO2. Retrievals of XCO2 over the ocean from GOSAT (Greenhouse gases observing satellite: NIES v02.75, National Institute for Environmental Studies; ACOS v7.3, Atmospheric CO2 Observation from Space) and OCO-2 (Orbiting Carbon Observatory, v9r) observations show a negative bias of about 1 parts per million (ppm) in northern midlatitudes, which was attributed to measurement uncertainties of the satellite observations. The NIES retrieval had higher consistency with in situ XCO2 at midlatitudes as compared to the other retrievals. At low latitudes, it shows many fewer valid data and high scatter, such that ACOS and OCO-2 appear to provide a better representation of the carbon cycle. At different times, the seasonal cycles of all three retrievals show positive phase shifts of one month relative to the in situ data. The study indicates that even if the retrievals complement each other, remaining uncertainties limit the accurate interpretation of spatiotemporal changes in CO2 fluxes. A continuous long-term XCO2 dataset with wide latitudinal coverage based on the new approach has a great potential as a robust reference dataset for XCO2 and can help to better understand changes in the carbon cycle in response to climate change using satellite observations.

Estimating emissions of methane and carbon dioxide sources using analytical Bayesian inversion system based on WRF-GHG tagged tracer simulations

2020 ◽  
Author(s):  
Michał Gałkowski ◽  
Julia Marshall ◽  
Frank-Thomas Koch ◽  
Jinxuan Chen ◽  
Alina Fiehn ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Anthropogenic Sources ◽  
Bayesian Inversion ◽  
Emission Rates ◽  
Atmospheric Measurements ◽  
Mixing Ratios ◽  
In Situ Data ◽  
Ventilation Shaft ◽  
Research Aircraft

&lt;p&gt;During May and June 2018, the intensive campaign CoMet (Carbon dioxide and Methane mission) made atmospheric measurements of greenhouse gases over Europe, with the upper Silesian coal basin (USCB) in southern Poland as a specific focus area. CoMet aimed at characterising the distribution of CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; over significant regional sources with the use of a fleet of research aircraft, as well as to validate remote sensing measurements from state-of-the-art instrumentation installed on-board against a set of independent in-situ observations.&lt;/p&gt;&lt;p&gt;In order to link atmospheric mixing ratios to source emission rates, high-resolution simulations with WRF-GHG v 3.9.1.1. (10 km x10 km Europe + nested 2 km x 2 km domain over the USCB), driven by short-term meteorological forecasts from the ECMWF IFS model and forecasts from CAMS (Copernicus Atmospheric Monitoring Service) for initial and lateral tracer boundary conditions were performed. Biogenic fluxes of CO2 were calculated online using the VPRM model driven by MODIS indices. Anthropogenic emissions over Europe were taken from the database of TNO, Department of Climate, Air and Sustainability (7 km x 7 km), augmented with an internal emissions database developed within CoMet that uses coal mine ventilation shaft emission measurements in combination with recent updates of the E-PRTR (European Pollutant Release and Transfer Register).&lt;/p&gt;&lt;p&gt;Tagged tracers were used to simulate a robust set of over 100 distinct anthropogenic sources of CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; from the study area, and these forward simulations were then used as the transport operator in an analytical Bayesian inversion system. Here we discuss the results of an analysis performed with the use of selected in-situ data measured over the course of the three-week campaign, including results and sensitivity tests.&lt;/p&gt;

scholarly journals Brief communication "Determination of urban growth in catchment areas in Cyprus using multi-temporal remotely sensed data: risk assessment study"

2010 ◽  
Vol 10 (11) ◽  
pp. 2235-2240 ◽  
Author(s):  
D. G. Hadjimitsis
Keyword(s):  
Risk Assessment ◽  
Catchment Area ◽  
Image Data ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Aerial Photos ◽  
Area Of Interest ◽  
Catchment Areas ◽  
Multi Temporal

Abstract. The aim of this study is to quantify the actual urbanization activity near the catchment area in the urban area of interest located in the vicinity of the Agriokalamin River area of Kissonerga Village in Paphos District. Remotely sensed data such as aerial photos, Landsat-5/7 TM/ETM+ and Quickbird image data have been used to track the urbanization activity from 1963 to 2008. In-situ GPS measurements have been used to locate in-situ the boundaries of the catchment area. The results clearly illustrate that tremendous urban development has taken place ranging from 0.9 to 33% from 1963 to 2008, respectively. A flood risk assessment and hydraulic analysis were also performed.

scholarly journals Remote Sensing Approaches and Related Techniques to Map and Study Landslides

2020 ◽  
Author(s):  
Ram L. Ray ◽  
Maurizio Lazzari ◽  
Tolulope Olutimehin
Keyword(s):  
Remote Sensing ◽  
Hazard Assessment ◽  
Remote Sensing Data ◽  
Remotely Sensed ◽  
Landslide Monitoring ◽  
In Situ Observation ◽  
Remotely Sensed Data ◽  
Sensing Data ◽  
Stability Model

Landslide is one of the costliest and fatal geological hazards, threatening and influencing the socioeconomic conditions in many countries globally. Remote sensing approaches are widely used in landslide studies. Landslide threats can also be investigated through slope stability model, susceptibility mapping, hazard assessment, risk analysis, and other methods. Although it is possible to conduct landslide studies using in-situ observation, it is time-consuming, expensive, and sometimes challenging to collect data at inaccessible terrains. Remote sensing data can be used in landslide monitoring, mapping, hazard prediction and assessment, and other investigations. The primary goal of this chapter is to review the existing remote sensing approaches and techniques used to study landslides and explore the possibilities of potential remote sensing tools that can effectively be used in landslide studies in the future. This chapter also provides critical and comprehensive reviews of landslide studies focus¬ing on the role played by remote sensing data and approaches in landslide hazard assessment. Further, the reviews discuss the application of remotely sensed products for landslide detection, mapping, prediction, and evaluation around the world. This systematic review may contribute to better understanding the extensive use of remotely sensed data and spatial analysis techniques to conduct landslide studies at a range of scales.

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