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2021 ◽  
Vol 21 (24) ◽  
pp. 18465-18497
Author(s):  
Catherine Hardacre ◽  
Jane P. Mulcahy ◽  
Richard J. Pope ◽  
Colin G. Jones ◽  
Steven T. Rumbold ◽  
...  

Abstract. In this study we evaluate simulated surface SO2 and sulfate (SO42-) concentrations from the United Kingdom Earth System Model (UKESM1) against observations from ground-based measurement networks in the USA and Europe for the period 1987–2014. We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and SO42- in both Europe and the USA over the period 1987–2014. However, in the polluted regions of the eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by a factor of 3 while under-predicting surface SO42- concentrations by 25 %–35 %. In the cleaner western USA, the model over-predicts both surface SO2 and SO42- concentrations by factors of 12 and 1.5 respectively. We find that UKESM1’s bias in surface SO2 and SO42- concentrations is variable according to region and season. We also evaluate UKESM1 against total column SO2 from the Ozone Monitoring Instrument (OMI) using an updated data product. This comparison provides information about the model's global performance, finding that UKESM1 over-predicts total column SO2 over much of the globe, including the large source regions of India, China, the USA, and Europe as well as over outflow regions. Finally, we assess the impact of a more realistic treatment of the model's SO2 dry deposition parameterization. This change increases SO2 dry deposition to the land and ocean surfaces, thus reducing the atmospheric loading of SO2 and SO42-. In comparison with the ground-based and satellite observations, we find that the modified parameterization reduces the model's over-prediction of surface SO2 concentrations and total column SO2. Relative to the ground-based observations, the simulated surface SO42- concentrations are also reduced, while the simulated SO2 dry deposition fluxes increase.


2021 ◽  
Author(s):  
Christian Borger ◽  
Steffen Beirle ◽  
Thomas Wagner

Abstract. We present a long-term data set of 1° × 1° monthly mean total column water vapour (TCWV) based on global measurements of the Ozone Monitoring Instrument (OMI) covering the time range from January 2005 to December 2020. In comparison to the retrieval algorithm of Borger et al. (2020) several modifications and filters have been applied accounting for instrumental issues (such as OMI's "row-anomaly") or the inferior quality of solar reference spectra. For instance, to overcome the problems of low quality reference spectra, the daily solar irradiance spectrum is replaced by an annually varying mean Earthshine radiance obtained in December over Antarctica. For the TCWV data set only measurements are taken into account for which the effective cloud fraction < 20 %, the AMF > 0.1, the ground pixel is snow- and ice-free, and the OMI row is not affected by the "row-anomaly" over the complete time range of the data set. The individual TCWV measurements are then gridded to a regular 1° × 1° lattice, from which the monthly means are calculated. In a comprehensive validation study we demonstrate that the OMI TCWV data set is in good agreement to reference data sets of ERA5, RSS SSM/I, and ESA CCI Water Vapour CDR-2: over ocean ordinary least squares (OLS) as well as orthogonal distance regressions (ODR) indicate slopes close to unity with very small offsets and high correlation coefficients of around 0.98. However, over land, distinctive positive deviations are obtained especially within the tropics with relative deviations of approximately +10 % likely caused by uncertainties in the retrieval input data (surface albedo, cloud information) due to frequent cloud contamination in these regions. Nevertheless, a temporal stability analysis proves that the OMI TCWV data set is consistent with the temporal changes of the reference data sets and shows no significant deviation trends. Since the TCWV retrieval can be easily applied to further satellite missions, additional TCWV data sets can be created from past missions such as GOME-1 or SCIAMACHY, which under consideration of systematic differences (e.g. due to different observation times) can be combined with the OMI TCWV data set in order to create a data record that would cover a time span from 1995 to the present. Moreover, the TCWV retrieval will also work for all missions dedicated to NO2 in future such as Sentinel-5 on MetOp-SG. The MPIC OMI total column water vapour (TCWV) climate data record is available at https://doi.org/10.5281/zenodo.5776718 (Borger et al., 2021b).


MAUSAM ◽  
2021 ◽  
Vol 67 (4) ◽  
pp. 939-945
Author(s):  
T. MUKHERJEE ◽  
A. DAS ◽  
S. K. MIDYA

2021 ◽  
Author(s):  
Ayomide Victor Arowolo ◽  
Ayodeji Oluleye

Abstract The focus of this study is to evaluate the influence of Intertropical Discontinuity (ITD) on the variation of Total column ozone (TCO). Relevant information is supplied on the temporal and spatial variability of TCO along the ITD zone, which is an important factor influencing the earth's atmosphere. Several studies over the years have established the relationship and influence several atmospheric processes have on TCO. However, the relationship between Intertropical discontinuity and TCO over West Africa has a gap. This study tends to examine the influence ITD has on TCO variation using the West Africa region as a case study. The study used Wind, ozone and dewpoint temperature data for the period between 1980-2019. To assess the variability and trend over the study region, several statistical methods were used, including Pearson correlation, Mann-Kendall, and linear regression model. The Mann-Kendall test shows an increasing trend throughout the months over the study region. Spatial analysis also revealed that regions North of the ITD has a higher concentration of TCO that the southern region of the ITD. however, ITD influence was more visible during the wet month of June to August (JJA) as the highest concentration of TCO was observed during this period across all latitude but more deviation was observed between latitude 100N to 180N, while the least occurrence is observed when ITD is at its minimum position in the month of December to February (DJF). The ACRV shows that 140N exhibit the highest variation with a value of 4.84, while the deviation is also at its highest with value of 13.65. The monthly position of ITD for Forty years was also analysed to observe the monthly deviation along the ITD region forty years and the spatial distribution of TCO was analysed from January to December. It’s of note that during the cause of this study, ozone hole which is designated by concentration less than or equal to 220DU was not recorded. The highest and the lowest value of TCO is 295DU and 227DU respectively with an average range of 68DU.


2021 ◽  
Author(s):  
John Worden ◽  
Daniel Cusworth ◽  
Zhen Qu ◽  
Yi Yin ◽  
Yuzhong Zhang ◽  
...  

Abstract. We present 2019 global methane (CH4) emissions and uncertainties, by sector, at 1-degree and country-scale resolution based on a Bayesian integration of satellite data and inventories. Globally, we find that agricultural and fire emissions are 227 +/− 19 Tg CH4/yr, waste is 50 +/− 7 Tg CH4/yr , anthropogenic fossil emissions are 82 +/− 12 Tg CH4/yr, and natural wetland/aquatic emissions are 180 +/− 10 Tg CH4/yr. These estimates are intended as a pilot dataset for the Global Stock Take in support of the Paris Agreement. However, differences between the emissions reported here and widely-used bottom-up inventories should be used as a starting point for further research because of potential systematic errors of these satellite based emissions estimates. Calculation of emissions and uncertainties: We first apply a standard optimal estimation (OE) approach to quantify CH4 fluxes using Greenhouse Gases Observing Satellite (GOSAT) total column CH4 concentrations and the GEOS-Chem global chemistry transport model. Second, we use a new Bayesian algorithm that projects these posterior fluxes to emissions by sector to 1 degree and country-scale resolution. This algorithm can also quantify uncertainties from measurement as well as smoothing error, which is due to the spatial resolution of the top-down estimate combined with the assumed structure in the prior emission uncertainties. Detailed Results: We find that total emissions for approximately 58 countries can be resolved with this observing system based on the degrees-of-freedom for signal (DOFS) metric that can be calculated with our Bayesian flux estimation approach. We find the top five emitting countries (Brazil, China, India, Russia, USA) emit about half of the global anthropogenic budget, similar to our choice of prior emissions. However, posterior emissions for these countries are mostly from agriculture, waste and fires (~129 Tg CH4/yr) with ~45 Tg CH4/yr from fossil emissions, as compared to prior inventory estimates of ~88 and 60 Tg CH4/yr respectively, primarily because the satellite observed concentrations are larger than expected in regions with substantive livestock activity. Differences are outside of 1-sigma uncertainties between prior and posterior for Brazil, India, and Russia but are consistent for China and the USA. The new Bayesian algorithm to quantify emissions from fluxes also allows us to “swap priors” if better informed or alternative priors and/or their covariances are available for testing. For example, recent bottom-up literature supposes greatly increased values for wetland/aquatic as well as fossil emissions. Swapping in priors that reflect these increased emissions results in posterior wetland emissions or fossil emissions that are inconsistent (differences greater than calculated uncertainties) with these increased bottom-up estimates, primarily because constraints related to the methane sink only allow total emissions across all sectors of ~560 Tg CH4/yr and because the satellite based estimate well constrains the spatially distinct fossil and wetland emissions. Given that this observing system consisting of GOSAT data and the GEOS-Chem model can resolve much of the different sectoral and country-wide emissions, with ~402 DOFS for the whole globe, our results indicate additional research is needed to identify the causes of discrepancies between these top-down and bottom-up results for many of the emission sectors reported here. In particular, the impact of systematic errors in the methane retrievals and transport model employed should be assessed where differences exist. However, our results also suggest that significant attention must be provided to the location and magnitude of emissions used for priors in top-down inversions; for example, poorly characterized prior emissions in one region and/or sector can affect top-down estimates in another because of the limited spatial resolution of these top-down estimates. Satellites such as the Tropospheric Monitoring Instrument (TROPOMI) and those in formulation such as the Copernicus CO2M, Methane-Sat, or Carbon Mapper offer the promise of much higher resolution fluxes relative to GOSAT assuming they can provide data with comparable or better accuracy, thus potentially reducing this uncertainty from poorly characterized emissions. These higher resolution estimates can therefore greatly improve the accuracy of emissions by reducing smoothing error. Fluxes calculated from other sources can also in principal be incorporated in the Bayesian estimation framework demonstrated here for the purpose of reducing uncertainty and improving the spatial resolution and sectoral attribution of subsequent methane emissions estimates.


2021 ◽  
Vol 14 (12) ◽  
pp. 7545-7563
Author(s):  
Nick Gorkavyi ◽  
Nickolay Krotkov ◽  
Can Li ◽  
Leslie Lait ◽  
Peter Colarco ◽  
...  

Abstract. The 21 June 2019 eruption of the Raikoke volcano (Kuril Islands, Russia; 48∘ N, 153∘ E) produced significant amounts of volcanic aerosols (sulfate and ash) and sulfur dioxide (SO2) gas that penetrated into the lower stratosphere. The dispersed SO2 and sulfate aerosols in the stratosphere were still detectable by multiple satellite sensors for many months after the eruption. For this study of SO2 and aerosol clouds we use data obtained from two of the Ozone Mapping and Profiler Suite sensors on the Suomi National Polar-orbiting Partnership satellite: total column SO2 from the Nadir Mapper and aerosol extinction profiles from the Limb Profiler as well as other satellite data sets. We evaluated the limb viewing geometry effect (the “arch effect”) in the retrieval of the LP standard aerosol extinction product at 674 nm. It was shown that the amount of SO2 decreases with a characteristic period of 8–18 d and the peak of stratospheric aerosol optical depth recorded at a wavelength of 674 nm lags the initial peak of SO2 mass by 1.5 months. Using satellite observations and a trajectory model, we examined the dynamics of an unusual atmospheric feature that was observed, a stratospheric coherent circular cloud of SO2 and aerosol from 18 July to 22 September 2019.


MAUSAM ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 663-668
Author(s):  
A. L. LONDHE ◽  
S. D. PATIL ◽  
B. PADMA KUMARI ◽  
D. B. JADHAV

’kq"d vkSj vknzZ ekulwu o"kkZsa ds nkSjku Vh-lh-vks- forj.k dk v/;;u djus ds fy, Hkkjrh; {ks+= esa o"kZ 1982]1983]1987 ,oa 1988 ds dqy dkWye vkstksu ¼Vh-lh-vks-½ ds ekfld vkSlr dk mi;ksx fd;k x;k gS A bl ’kks/k&Ik= esa mDr o"kksZa ds Hkkjr ds 13 LVs’kuksa ds Vh-lh-vks- vkadM+ksa dk v/;;u fd;k x;k gSA ’kq"d vkSj vknzZ ekulwu o"kksZa ds nkSjku Vh-lh-vks- forj.k dh rqyuk ls ;g irk pyk gS fd Vh-lh-vks- ds eku vknZz o"kksZa dh rqyuk esa ’kq"d o"kksZa esa vf/kd ik, x, gSaA Vh-lh-vks- esa ifjorZu gksuk ’kq"d ,oa vknzZ o"kksZa ds nkSjku laoguh; xfrfof/k esa fHkUurk dks ekuk tk ldrk gSA ’kq"d ¼vknzZ½ o"kksZa ds nkSjku laogu esa deh ¼o`f)½ Vh-lh-vks- dh ek=k dks c<+krh ?kVkrh gSA ’kq"d ,oa vknzZ o"kksZa ds chp ds ekulwu ds eghuksa ds nkSjku Vh-lh-vks- ds egRo dh tk¡p djus ds fy, lkaf[;dh; Vh--VsLV dk iz;ksx fd;k x;k gSA ;g varj nene dks NksM+dj vU; lHkh LVs’kuksa ds fy, lkaf[;dh; n`f"V ls 5 izfr’kr rd egRoiw.kZ gSA ,slk dgk tk ldrk gS fd Hkkjr esa xzh"edkyhu ekulwu eghuksa ds nkSjku vks-,y-vkj- rFkk Vh-lh-vks- ds chp vPNs laca/k jgs gSa D;ksafd bl vof/k ds nkSjku laogu dkQh izcy jgk gS A Monthly mean total column ozone (TCO) over Indian region for the years 1982, 1983, 1987 and 1988 has been utilized to study the TCO distribution during dry and wet monsoon years. TCO data for 13 Indian stations for the above years have been considered in the study. Comparison of TCO distribution during dry and wet monsoon years suggested that TCO values are found higher during dry years than those in wet years. The changes in TCO may be attributed to difference in convective activity during dry and wet years. The suppressed (enhanced) convection during dry (wet) years may lead to increase (decrease) in TCO.   The statistical t-test is applied to test the significance of TCO difference during monsoon months between dry and wet years. The difference is statistically significant at 5% level of confidence for all stations except Dumdum. It can be said that the relation between OLR and TCO holds good during Indian summer monsoon months, as convection is stronger during this period.


2021 ◽  
Vol 893 (1) ◽  
pp. 012010
Author(s):  
Sumaryati ◽  
D F Andarini ◽  
N Cholianawati ◽  
A Indrawati

Abstract East Nusa Tenggara is one of the provinces in Indonesia that has big forest fires following some provinces in Kalimantan and Sumatra. However, forest fires in East Nusa Tenggara have less attention in forest fires discussion in Indonesia. This study aims to analyze forest fires in East Nusa Tenggara and their impact on reducing visibility and increasing carbon monoxide (CO) from 2015 to 2019. In this study, hotspot, forest fire area, Oceanic Niño Index, visibility, and CO total column data were used to analyze the forest fires using a statistical comparison method in East Nusa Tenggara, Kalimantan, and Sumatra. The result shows that the number of hotspots in East Nusa Tenggara less than in Kalimantan and Sumatra for the same forest fire area. The forest fires in East Nusa Tenggara do not harm the atmospheric environment significantly. East Nusa Tenggara dominantly consists of savanna areas with no peatland, hence, the forest biomass burning produces less smoke and CO. Furthermore, the forest fire in East Nusa Tenggara has not an impact on decreasing visibility and increasing CO total column, in contrast, visibility in Sumatra and Kalimantan has fallen to 6 km from the annual average, and CO total column rise three times of normal condition during peak fire.


2021 ◽  
Vol 13 (19) ◽  
pp. 3987
Author(s):  
Ukkyo Jeong ◽  
Hyunkee Hong

Atmospheric carbon monoxide (CO) significantly impacts climate change and human health, and has become the focus of increased air quality and climate research. Since 2018, the Troposphere Monitoring Instrument (TROPOMI) has provided total column amounts of CO (CTROPOMI) with a high spatial resolution to monitor atmospheric CO. This study compared and assessed the accuracy of CTROPOMI measurements using surface in-situ measurements (SKME) obtained from an extensive ground-based network over South Korea, where CO level is persistently affected by both local emissions and trans-boundary transport. Our analysis reveals that the TROPOMI effectively detected major emission sources of CO over South Korea and efficiently complemented the spatial coverage of the ground-based network. In general, the correlations between CTROPOMI and SKME were lower than those for NO2 reported in a previous study, and this discrepancy was partly attributed to the lower spatiotemporal variability. Moreover, vertical CO profiles were sampled from the ECMWF CAMS reanalysis data (EAC4) to convert CTROPOMI to surface mixing ratios (STROPOMI). STROPOMI showed a significant underestimation compared with SKME by approximately 40%, with a moderate correlation of approximately 0.51. The low biases of STROPOMI were more significant during the winter season, which was mainly attributed to the underestimation of the EAC4 CO at the surface. This study can contribute to the assessment of satellite and model data for monitoring surface air quality and greenhouse gas emissions.


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