scholarly journals Double cores of the Ozone Low in the vertical direction over the Asian continent in satellite data sets

2019 ◽  
Vol 3 (2) ◽  
pp. 93-101 ◽  
Author(s):  
Zhou Tang ◽  
◽  
Dong Guo ◽  
YuCheng Su ◽  
ChunHua Shi ◽  
...  
Keyword(s):  
Satellite Data ◽  
Vertical Direction ◽  
Data Sets ◽  
Asian Continent

scholarly journals Inter-comparison of CO measurements from TROPOMI, ACE-FTS, and a high-Arctic ground-based FTS

2021 ◽  
Author(s):  
Tyler Wizenberg ◽  
Kimberly Strong ◽  
Kaley Walker ◽  
Erik Lutsch ◽  
Tobias Borsdorff ◽  
...  
Keyword(s):  
Satellite Data ◽  
Polar Region ◽  
High Arctic ◽  
Equatorial Region ◽  
The Arctic ◽  
Data Sets ◽  
Positive Bias ◽  
Clear Sky ◽  
Global Comparison ◽  
The Mean

Abstract. ACE/TROPOMI Abstract for AMT submission The TROPOspheric Monitoring Instrument (TROPOMI) provides a daily, spatially-resolved (initially 7 × 7 km2, upgraded to 7 × 5.6 km2 in August 2019) global data set of CO columns, however, due to the relative sparseness of reliable ground-based data sources, it can be challenging to characterize the validity and accuracy of satellite data products in remote regions such as the high Arctic. In these regions, satellite inter-comparisons can supplement model- and ground-based validation efforts and serve to verify previously observed differences. In this paper, we compare the CO products from TROPOMI, the Atmospheric Chemistry Experiment (ACE) Fourier Transform Spectrometer (FTS), and a high-Arctic ground-based FTS located at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut (80.05° N, 86.42° W). A global comparison of TROPOMI reference profiles scaled by the retrieved total column with ACE-FTS CO partial columns for the period from 10 November 2017 to 31 May 2020 displays excellent agreement between the two data sets (R = 0.93), and a small relative bias of −0.68 ± 0.25 % (bias ± standard error). Additional comparisons were performed within five latitude bands; the north Polar region (60° N to 90° N), northern Mid-latitudes (20° N to 60° N), the Equatorial region (20° S to 20° N), southern Mid-latitudes (60° S to 20° S), and the south Polar region (90° S to 60° S). Latitudinal comparisons of the TROPOMI and ACE-FTS CO datasets show strong correlations ranging from R = 0.93 (southern Mid-latitudes) to R = 0.85 (Equatorial region) between the CO products, but display a dependence of the mean differences on latitude. Positive mean biases of 7.92 ± 0.58 % and 7.98 ± 0.51 % were found in the northern and southern Polar regions, respectively, while a negative bias of −9.16 ± 0.55 % was observed in the Equatorial region. To investigate whether these differences are introduced by cloud contamination which is reflected in the TROPOMI averaging kernel shape, the latitudinal comparisons were repeated for cloud-covered pixels and clear-sky pixels only, and for the unsmoothed and smoothed cases. Clear-sky pixels were found to be biased higher with poorer correlations on average than clear+cloudy scenes and cloud-covered scenes only. Furthermore, the latitudinal dependence on the biases was observed in both the smoothed and unsmoothed cases. To provide additional context to the global comparisons of TROPOMI with ACE-FTS in the Arctic, both satellite data sets were compared against measurements from the ground-based PEARL-FTS. Comparisons of TROPOMI with smoothed PEARL-FTS total columns in the period of 3 March 2018 to 27 March 2020 display a strong correlation (R = 0.88), however a positive mean bias of 14.3 ± 0.16 % was also found. A partial column comparison of ACE-FTS with the PEARL-FTS in the period from 25 February 2007 to 18 March 2020 shows good agreement (R = 0.82), and a mean positive bias of 9.83 ± 0.22 % in the ACE-FTS product relative to the ground-based FTS. The magnitude and sign of the mean relative differences are consistent across all inter-comparisons in this work, as well as with recent ground-based validation efforts, suggesting that current TROPOMI CO product exhibits a positive bias in the high-Arctic region. However, the observed bias is within the TROPOMI mission accuracy requirement of ±15 %, providing further confirmation that the data quality in these remote high-latitude regions meets this specification.

Satellite Remote Sensing of Cirrus

Cirrus ◽  
2002 ◽  
Author(s):  
Patrick Minnis
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Climate Models ◽  
Cirrus Clouds ◽  
Data Sets ◽  
Visible Radiation ◽  
Accurate Identification ◽  
Spatial And Temporal Scales ◽  
Sensing Systems ◽  
Particle Size And Shape

The determination of cirrus properties over large spatial and temporal scales will, in most instances, require the use of satellite data. Global coverage at resolutions as fine as several meters are attainable with instruments on Landsat, and temporal coverage at 1-min intervals is now available with the latest Geostationary Operational Environmental Satellite (GOES) imagers. Extracting information about cirrus clouds from these satellite data sets is often difficult because of variations in background, similarities to other cloud types, and the frequently semitransparent nature of cirrus clouds. From the surface, cirrus clouds are readily discerned by the human observer via the patterns of scattered visible radiation from the sun, moon, and stars. The relatively uniform background presented by the sky facilitates cloud detection and the familiar textures, structures, and apparent altitude of cirrus distinguish it from other cloud types. From satellites, cirrus can also be detected from scattered visible radiation, but the demands of accurate identification for different surface backgrounds over the entire diurnal cycle and quantification of the cirrus properties require the analysis of radiances scattered or emitted over a wide range of the electromagnetic spectrum. Many of these spectra and high-resolution satellite data can be used to understand certain aspects of cirrus clouds in particular situations. Intensive study of well-measured cases can yield a wealth of information about cirrus properties on fine scales (e.g., Minnis et al. 1990; Westphal et al. 1996). Production of a global climatology of cirrus clouds, however, requires compromises in spatial, temporal, and spectral coverage (e.g., Schiffer and Rossow 1983). This chapter summarizes both the state of the art and the potential for future passive remote sensing systems to aid the understanding of cirrus processes and to acquire sufficient statistics for constraining and refining weather and climate models. Theoretically, many different aspects of cirrus can be determined from passive sensing systems. A limited number of quantities are the focus of most efforts to describe cirrus clouds. These include the areal coverage, top and base altitude or pressure, thickness, top and base temperatures, optical depth, effective particle size and shape, vertical ice water path, and size, shape and spacing of the cloud cells.

scholarly journals Asian water tower evinced in total column water vapor: a comparison among multiple satellite and reanalysis data sets

2019 ◽  
Vol 54 (1-2) ◽  
pp. 231-245 ◽  
Author(s):  
Yin Zhao ◽  
Tianjun Zhou
Keyword(s):  
Water Vapor ◽  
Satellite Data ◽  
Annual Cycle ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Data Sets ◽  
Important Indicator ◽  
Ensemble Mean ◽  
Asian Water ◽  
Total Column

Abstract The total column water vapor (TCWV) over the Tibetan Plateau (TP) is one important indicator of the Asian water tower, and the changes in the TCWV are vital to the climate and ecosystem in downstream regions. However, the observational data is insufficient to understand the changes in the TCWV due to the high elevation of the TP. Satellite and reanalysis data can be used as substitutes, but their quality needs to be evaluated. In this study, based on a homogenized radiosonde data set, a comprehensive evaluation of the TCWV over the TP derived from two satellite data sets (AIRS-only and AIRS/AMSU) and seven existing reanalysis data sets (MERRA, MERRA2, NCEP1, NCEP2, CFSR, ERA-I, JRA55) is performed in the context of the climatology, annual cycle and interannual variability. Both satellite data sets reasonably reproduce the characteristics of the TCWV over the TP. All reanalysis data sets perform well in reproducing the annual mean climatology of the TCWV over the TP (R = 0.99), except for NCEP1 (R = 0.96) and NCEP2 (R = 0.92). ERA-I is more reliable in capturing the spatial pattern of the annual cycle (R = 0.94), while NCEP1 shows the lowest skill (R = 0.72). JRA55 performs best in capturing the features of the interannual coherent variation (EOF1, R = 0.97). The skill-weighted ensemble mean of the reanalysis data performs better than the unweighted ensemble mean and most of the single reanalysis data sets. The evaluation provides essential information on both the strengths and weaknesses of the major satellite and reanalysis data sets in measuring the total column water vapor over the TP.

scholarly journals INVENTÁRIO DE CARBONO EM FRAGMENTO DE FLORESTA OMBRÓFILA MISTA POR DETECÇÃO REMOTA

FLORESTA ◽  
2014 ◽  
Vol 44 (4) ◽  
pp. 697
Author(s):  
Henrique Luis Godinho Cassol ◽  
Dejanira Luderitz Saldanha ◽  
Tatiana Mora Kuplich
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Empirical Relationship ◽  
Data Sets ◽  
Above Ground Biomass ◽  
Continuous Forest ◽  
Using Data ◽  
Continuous Forest Inventory ◽  
Radiometric Data ◽  
Carbon Inventory

O trabalho teve como objetivo inventariar o carbono de um fragmento de Floresta Ombrófila Mista utilizando dados provenientes de sensores de média resolução espacial. Uma cena dos sensores ASTER, LISS e TM foi empregada na obtenção dos dados radiométricos (espectrais), e os dados de biomassa e carbono (biofísicos) foram oriundos de parcelas de inventário florestal contínuo em São João do Triunfo, PR. A metodologia consistiu em estabelecer a relação empírica entre esses conjuntos de dados por meio de equações lineares de regressão. À exceção do sensor TM, que apresentou resultado insatisfatório, o uso dos dados oriundos dos sensores LISS e ASTER foi adequado para se inventariar o carbono florestal por detecção remota, com erros inferiores aos estabelecidos nas campanhas de inventários tradicionais (α < 0,05).Palavras-chave: Estoque de carbono; sensoriamento remoto; ASTER; TM; LISS. AbstractCarbon inventory in a fragment of Mixed Ombrophylous Forest by remote sensing. The research aims to make inventory of carbon of a fragment of Araucaria Forest using data from medium spatial resolution sensors. Satellite data from ASTER, TM and LISS were used to obtain the radiometric data. The above ground biomass and carbon data (biophysical data) were derived from the continuous forest inventory located in São João do Triunfo, PR. The methodology consisted of establishing the empirical relationship between spectral and biophysical data sets using linear regression. Except for the TM data, which showed unsatisfactory results, the use of ASTER and LISS satellite data was suited to forest carbon inventory by remote sensing, with errors lower than those set in traditional inventory campaigns (α < 0,05).Keywords: Carbon stock; remote sensing; ASTER; TM; LISS.

scholarly journals Global lightning NO<sub>x</sub> production estimated by an assimilation of multiple satellite data sets

2014 ◽  
Vol 14 (7) ◽  
pp. 3277-3305 ◽  
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo ◽  
C. Zhang
Keyword(s):  
Satellite Data ◽  
Production Efficiency ◽  
Transport Model ◽  
Chemical System ◽  
No Production ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Independent Observations ◽  
Sensitivity Studies

Abstract. The global source of lightning-produced NOx (LNOx) is estimated by assimilating observations of NO2, O3, HNO3, and CO measured by multiple satellite measurements into a chemical transport model. Included are observations from the Ozone Monitoring Instrument (OMI), Microwave Limb Sounder (MLS), Tropospheric Emission Spectrometer (TES), and Measurements of Pollution in the Troposphere (MOPITT) instruments. The assimilation of multiple chemical data sets with different vertical sensitivity profiles provides comprehensive constraints on the global LNOx source while improving the representations of the entire chemical system affecting atmospheric NOx, including surface emissions and inflows from the stratosphere. The annual global LNOx source amount and NO production efficiency are estimated at 6.3 Tg N yr−1 and 310 mol NO flash−1, respectively. Sensitivity studies with perturbed satellite data sets, model and data assimilation settings lead to an error estimate of about 1.4 Tg N yr−1 on this global LNOx source. These estimates are significantly different from those estimated from a parameter inversion that optimizes only the LNOx source from NO2 observations alone, which may lead to an overestimate of the source adjustment. The total LNOx source is predominantly corrected by the assimilation of OMI NO2 observations, while TES and MLS observations add important constraints on the vertical source profile. The results indicate that the widely used lightning parameterization based on the C-shape assumption underestimates the source in the upper troposphere and overestimates the peak source height by up to about 1 km over land and the tropical western Pacific. Adjustments are larger over ocean than over land, suggesting that the cloud height dependence is too weak over the ocean in the Price and Rind (1992) approach. The significantly improved agreement between the analyzed ozone fields and independent observations gives confidence in the performance of the LNOx source estimation.

scholarly journals A study of the direct and indirect effects of aerosols using global satellite data sets of aerosol and cloud parameters

2003 ◽  
Vol 108 (D22) ◽  
Author(s):  
Miho Sekiguchi ◽  
Teruyuki Nakajima ◽  
Kentaroh Suzuki ◽  
Kazuaki Kawamoto ◽  
Akiko Higurashi ◽  
...  
Keyword(s):  
Satellite Data ◽  
Indirect Effects ◽  
Data Sets ◽  
Direct And Indirect Effects ◽  
Cloud Parameters

Precise climate monitoring using complementary satellite data sets

Nature ◽  
2000 ◽  
Vol 403 (6768) ◽  
pp. 414-416 ◽  
Author(s):  
Frank J. Wentz ◽  
Matthias Schabel
Keyword(s):  
Satellite Data ◽  
Data Sets ◽  
Climate Monitoring

Standard Ozone Profiles from Balloon and Satellite Data Sets

1983 ◽  
Vol 22 (12) ◽  
pp. 2012-2022 ◽  
Author(s):  
K. F. Klenk ◽  
P. K. Bhartia ◽  
E. Hilsenrath ◽  
A. J. Fleig
Keyword(s):  
Satellite Data ◽  
Data Sets

Spatial variation and temporal trends of solar radiation over Morocco based on ground observations and CMSAF data records.

2020 ◽  
Author(s):  
Sara Moutia
Keyword(s):  
Solar Radiation ◽  
Satellite Data ◽  
Sunshine Duration ◽  
Temporal Trends ◽  
General Tendency ◽  
Data Sets ◽  
Alternative Source ◽  
In Situ Observations ◽  
Source Of Information

&lt;p&gt;The main advantage of remote sensing products is that they are reasonably good in terms of temporal and special coverage, and they are available in a near real time. Therefore, an understanding of the strengths and weaknesses of satellite data is useful to choose it as an alternative source of information with acceptable accuracy. &amp;#160;On the first hand, this study assesses an Inter-comparison between CMSAF Sunshine Duration (SD) data records and ground observations of 30 data sets from 1983 to 2015. the correlation is very significant and the satellite data fits very closely to in situ observations. On the other hand, trend analysis is applied to SD and Solar Incoming Direct radiation (SID) data, a number of stations show a statistically significant decreasing trend in SD and also SID shows a decreasing trend over Morocco in most of regions especially in summer. The results indicate a general tendency of decrease in incoming solar radiation mostly during summer which could be of some concern for solar energy.&lt;/p&gt;

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