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We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products https://doi.org/10.15770/EUM_SAF_AC_0048, AC SAF, 2023a; monthly products https://doi.org/10.15770/EUM_SAF_AC_0049, AC SAF, 2023b). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.

Water vapor plays an important role in the greenhouse effect, rendering it an atmospheric constituent that requires continuous and global monitoring by different types of remote sensing instruments. The TROPOspheric Monitoring Instrument Sentinel-5 Precursor (TROPOMI/S5P) Total Column Water Vapor (TCWV) is a new product retrieved from the visible blue spectral range (435–455 nm), using an algorithm that was originally developed for the GOME-2/MetOp sensors. For the purposes of this work, 2.5 years of continuous satellite observations at high spatial resolution are validated against co-located (in space and in time) precipitable water Level 2.0 (quality-assured) ground-based measurements from the NASA AERONET (AErosol RObotic NETwork). The network uses Cimel Sun photometers located at approximately 1300 stations globally to monitor precipitable water among other products. Based on data availability, 369 of the stations were used in this study. The two datasets, satellite- and ground-based, were co-located, and the relative differences of the comparisons were calculated and statistically analyzed. The Pearson correlation coefficient of the two products is found to be 0.91, and the mean bias of the overall relative percentage differences is of the order of −2.7 %. For the Northern Hemisphere midlatitudes (30–60∘ N), where the density of the ground-based stations is high, the mean relative bias was found to be −1.8 %, while in the tropics (±15∘) the TROPOMI TCWV product has a relative dry bias of up to −10 %. The effect of various algorithm and geophysical parameters, such as air mass factor, solar zenith angle, clouds and albedo, is also presented and discussed. It was found that the cloud properties affect the validation results, leading the TCWV to a dry bias of −20 % for low cloud heights (cloud top pressure (CTP) >800 hPa). Moreover, cloud albedo introduces a wet bias of 15 % when it is below 0.3 and a dry bias up to −25 % when the clouds are more reflective. Overall, the TROPOMI/S5P TCWV product, on a global scale and for moderate albedo and cloudiness, agrees well at -2.7±4.9 % with the AERONET observations but probably within about −8 % to −13 % with respect to the “truth”.

We present results from the Munich Nitrogen dioxide (NO2) Imaging Campaign (MuNIC), where NO2 near-surface concentrations (NSCs) and vertical column densities (VCDs) were measured with stationary, mobile, and airborne in situ and remote sensing instruments in Munich, Germany. The most intensive day of the campaign was 7 July 2016, when the NO2 VCD field was mapped with the Airborne Prism Experiment (APEX) imaging spectrometer. The spatial distribution of APEX VCDs was rather smooth, with a horizontal gradient between lower values upwind and higher values downwind of the city center. The NO2 map had no pronounced source signatures except for the plumes of two combined heat and power (CHP) plants. The APEX VCDs have a fair correlation with mobile multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations from two vehicles conducted on the same afternoon (r=0.55). In contrast to the VCDs, mobile NSC measurements revealed high spatial and temporal variability along the roads, with the highest values in congested areas and tunnels. The NOx emissions of the two CHP plants were estimated from the APEX observations using a mass-balance approach. The NOx emission estimates are consistent with CO2 emissions determined from two ground-based Fourier transform infrared (FTIR) instruments operated near one CHP plant. The estimates are higher than the reported emissions but are probably overestimated because the uncertainties are large, as conditions were unstable and convective with low and highly variable wind speeds. Under such conditions, the application of mass-balance approaches is problematic because they assume steady-state conditions. We conclude that airborne imaging spectrometers are well suited for mapping the spatial distribution of NO2 VCDs over large areas. The emission plumes of point sources can be detected in the APEX observations, but accurate flow fields are essential for estimating emissions with sufficient accuracy. The application of airborne imaging spectrometers for studying NSCs is less straightforward and requires us to account for the non-trivial relationship between VCDs and NSCs.

Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.

The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (the Netherlands) in September 2016 with the aim of assessing the consistency of multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of tropospheric species (NO2, HCHO, O3, HONO, CHOCHO and O4). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, long-path DOAS, direct-sun DOAS, Sun photometer and meteorological instruments). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO2, HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations, with the focus on aerosol optical thicknesses (AOTs), trace gas vertical column densities (VCDs) and trace gas surface concentrations. The algorithms are based on three different techniques: six use the optimal estimation method, two use a parameterized approach and one algorithm relies on simplified radiative transport assumptions and analytical calculations. To assess the agreement among the inversion algorithms independent of inconsistencies in the trace gas slant column density acquisition, participants applied their inversion to a common set of slant columns. Further, important settings like the retrieval grid, profiles of O3, temperature and pressure as well as aerosol optical properties and a priori assumptions (for optimal estimation algorithms) have been prescribed to reduce possible sources of discrepancies. The profiling results were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions; however, these are sometimes at different altitudes and of different magnitudes. Under clear-sky conditions, the root-mean-square differences (RMSDs) among the results of individual participants are in the range of 0.01–0.1 for AOTs, (1.5–15) ×1014molec.cm-2 for trace gas (NO2, HCHO) VCDs and (0.3–8)×1010molec.cm-3 for trace gas surface concentrations. These values compare to approximate average optical thicknesses of 0.3, trace gas vertical columns of 90×1014molec.cm-2 and trace gas surface concentrations of 11×1010molec.cm-3 observed over the campaign period. The discrepancies originate from differences in the applied techniques, the exact implementation of the algorithms and the user-defined settings that were not prescribed. For the comparison against supporting observations, the RMSDs increase to a range of 0.02–0.2 against AOTs from the Sun photometer, (11–55)×1014molec.cm-2 against trace gas VCDs from direct-sun DOAS observations and (0.8–9)×1010molec.cm-3 against surface concentrations from the long-path DOAS instrument. This increase in RMSDs is most likely caused by uncertainties in the supporting data, spatiotemporal mismatch among the observations and simplified assumptions particularly on aerosol optical properties made for the MAX-DOAS retrieval. As a side investigation, the comparison was repeated with the participants retrieving profiles from their own differential slant column densities (dSCDs) acquired during the campaign. In this case, the consistency among the participants degrades by about 30 % for AOTs, by 180 % (40 %) for HCHO (NO2) VCDs and by 90 % (20 %) for HCHO (NO2) surface concentrations. In former publications and also during this comparison study, it was found that MAX-DOAS vertically integrated aerosol extinction coefficient profiles systematically underestimate the AOT observed by the Sun photometer. For the first time, it is quantitatively shown that for optimal estimation algorithms this can be largely explained and compensated by considering biases arising from the reduced sensitivity of MAX-DOAS observations to higher altitudes and associated a priori assumptions.

We present an improved TROPOspheric Monitoring Instrument (TROPOMI) retrieval of formaldehyde (HCHO) over China. The new retrieval optimizes the slant column density (SCD) retrieval and air mass factor (AMF) calculation for TROPOMI observations of HCHO over China. Retrieval of HCHO differential SCDs (DSCDs) is improved using the basic optical differential spectroscopy (BOAS) technique resulting in lower noise and smaller random error, while AMFs are improved with a priori HCHO profiles from a higher resolution regional chemistry transport model. Compared to the operational product, the new TROPOMI HCHO retrieval shows better agreement with ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements in Beijing. The improvements are mainly related to the AMF calculation with more precise a priori profiles in winter. Using more precise a priori profiles in general reduces HCHO vertical column densities (VCDs) by 52.37 % (± 27.09 %) in winter. Considering the aerosol effect in AMF calculation reduces the operational product by 11.46 % (± 1.48 %) and our retrieval by 17.61 % (± 1.92 %) in winter. The improved and operational HCHO are also used to investigate the spatial–temporal characteristics of HCHO over China. The result shows that both improved and operational HCHO VCDs reach maximum in summer and minimum in winter. High HCHO VCDs mainly located over populated areas, i.e., Sichuan Basin and central and eastern China, indicate a significant contribution of anthropogenic emissions. The hotspots are more obvious on the map of the improved HCHO retrieval than the operational product. The result indicates that the improved TROPOMI HCHO retrieval is more suitable for the analysis of regional- and city-scale pollution in China.

In many cities around the world the overall air quality is improving, but at the same time nitrogen dioxide (NO2) trends show stagnating values and in many cases could not be reduced below air quality standards recommended by the World Health Organization (WHO). Many large cities have built monitoring stations to continuously measure different air pollutants. While most stations follow defined rules in terms of measurement height and distance to traffic emissions, the question remains of how representative are those point measurements for the city-wide air quality. The question of the spatial coverage of a point measurement is important because it defines the area of influence and coverage of monitoring networks, determines how to assimilate monitoring data into model simulations or compare to satellite data with a coarser resolution, and is essential to assess the impact of the acquired data on public health. In order to answer this question, we combined different measurement data sets consisting of path-averaging remote sensing data and in situ point measurements in stationary and mobile setups from a measurement campaign that took place in Munich, Germany, in June and July 2016. We developed an algorithm to strip temporal from spatial patterns in order to construct a consistent NO2 pollution map for Munich. Continuous long-path differential optical absorption spectroscopy (LP DOAS) measurements were complemented with mobile cavity-enhanced (CE) DOAS, chemiluminescence (CL) and cavity attenuated phase shift (CAPS) instruments and were compared to monitoring stations and satellite data. In order to generate a consistent composite map, the LP DOAS diurnal cycle has been used to normalize for the time of the day dependency of the source patterns, so that spatial and temporal patterns can be analyzed separately. The resulting concentration map visualizes pollution hot spots at traffic junctions and tunnel exits in Munich, providing insights into the strong spatial variations. On the other hand, this database is beneficial to the urban planning and the design of control measures of environment pollution. Directly comparing on-street mobile measurements in the vicinity of monitoring stations resulted in a difference of 48 %. For the extrapolation of the monitoring station data to street level, we determined the influence of the measuring height and distance to the street. We found that a measuring height of 4 m, at which the Munich monitoring stations measure, results in 16 % lower average concentrations than a measuring height of 1.5 m, which is the height of the inlet of our mobile measurements and a typical pedestrian breathing height. The horizontal distance of most stations to the center of the street of about 6 m also results in an average reduction of 13 % compared to street level concentration. A difference of 21 % in the NO2 concentrations remained, which could be an indication that city-wide measurements are needed for capturing the full range and variability of concentrations for assessing pollutant exposure and air quality in cities.

We present the inter-comparison of delta slant column densities (SCDs) and vertical profiles of nitrous acid (HONO) derived from measurements of different multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments and using different inversion algorithms during the Second Cabauw Inter-comparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) in September 2016 at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). The HONO vertical profiles, vertical column densities (VCDs), and near-surface volume mixing ratios are compared between different MAX-DOAS instruments and profile inversion algorithms for the first time. Systematic and random discrepancies of the HONO results are derived from the comparisons of all data sets against their median values. Systematic discrepancies of HONO delta SCDs are observed in the range of ±0.3×1015 molec. cm−2, which is half of the typical random discrepancy of 0.6×1015 molec. cm−2. For a typical high HONO delta SCD of 2×1015 molec. cm−2, the relative systematic and random discrepancies are about 15 % and 30 %, respectively. The inter-comparison of HONO profiles shows that both systematic and random discrepancies of HONO VCDs and near-surface volume mixing ratios (VMRs) are mostly in the range of ∼±0.5×1014 molec. cm−2 and ∼±0.1 ppb (typically ∼20 %). Further we find that the discrepancies of the retrieved HONO profiles are dominated by discrepancies of the HONO delta SCDs. The profile retrievals only contribute to the discrepancies of the HONO profiles by ∼5 %. However, some data sets with substantially larger discrepancies than the typical values indicate that inappropriate implementations of profile inversion algorithms and configurations of radiative transfer models in the profile retrievals can also be an important uncertainty source. In addition, estimations of measurement uncertainties of HONO dSCDs, which can significantly impact profile retrievals using the optimal estimation method, need to consider not only DOAS fit errors, but also atmospheric variability, especially for an instrument with a DOAS fit error lower than ∼3×1014 molec. cm−2. The MAX-DOAS results during the CINDI-2 campaign indicate that the peak HONO levels (e.g. near-surface VMRs of ∼0.4 ppb) often appeared in the early morning and below 0.2 km. The near-surface VMRs retrieved from the MAX-DOAS observations are compared with those measured using a co-located long-path DOAS instrument. The systematic differences are smaller than 0.15 and 0.07 ppb during early morning and around noon, respectively. Since true HONO values at high altitudes are not known in the absence of real measurements, in order to evaluate the abilities of profile inversion algorithms to respond to different HONO profile shapes, we performed sensitivity studies using synthetic HONO delta SCDs simulated by a radiative transfer model with assumed HONO profiles. The tests indicate that the profile inversion algorithms based on the optimal estimation method with proper configurations can reproduce the different HONO profile shapes well. Therefore we conclude that the features of HONO accumulated near the surface derived from MAX-DOAS measurements are expected to represent the ambient HONO profiles well.

We present two-dimensional scanning Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of nitrogen dioxide (NO2) and formaldehyde (HCHO) in Munich. Vertical columns and vertical distribution profiles of aerosol extinction coefficient, NO2 and HCHO are retrieved from the 2D MAX-DOAS observations. The measured surface aerosol extinction coefficients and NO2 mixing ratios derived from the retrieved profiles are compared to in situ monitoring data, and the surface NO2 mixing ratios show a good agreement with in situ monitoring data with a Pearson correlation coefficient (R) of 0.91. The aerosol optical depths (AODs) show good agreement as well (R = 0.80) when compared to sun photometer measurements. Tropospheric vertical column densities (VCDs) of NO2 and HCHO derived from the MAX-DOAS measurements are also used to validate Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) satellite observations. Monthly averaged data show a good correlation; however, satellite observations are on average 30 % lower than the MAX-DOAS measurements. Furthermore, the MAX-DOAS observations are used to investigate the spatiotemporal characteristic of NO2 and HCHO in Munich. Analysis of the relations between aerosol, NO2 and HCHO shows higher aerosol-to-HCHO ratios in winter, which reflects a longer atmospheric lifetime of secondary aerosol and HCHO during winter. The analysis also suggests that secondary aerosol formation is the major source of these aerosols in Munich.

We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Metop satellites. The blue band algorithm allows the retrieval of water vapor from sensors which do not cover longer wavelengths, such as the Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel-5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical columns using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from the chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME-2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing it to the operational product retrieved in the red spectral band, sun photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

We present a new aerosol extinction profile retrieval algorithm for multi-axis differential optical absorption spectrometer (MAX-DOAS) measurements at high-altitude sites. The algorithm is based on the lookup table method. It is applied to retrieve aerosol extinction profiles from the long-term MAX-DOAS measurements (February 2012 to February 2016) at the Environmental Research Station Schneefernerhaus (UFS), Germany (47.417∘ N, 10.980∘ E), which is located near the summit of Zugspitze at an altitude of 2650 m. The lookup table consists of simulated O4 differential slant column densities (DSCDs) corresponding to numerous possible aerosol extinction profiles. The sensitivities of O4 absorption to several parameters were investigated for the design and parameterization of the lookup table. In the retrieval, simulated O4 DSCDs for each possible profile are derived by interpolating the lookup table to the observation geometries. The cost functions are calculated for each aerosol profile in the lookup table based on the simulated O4 DSCDs, the O4 DSCD observations, and the measurement uncertainties. Valid profiles are selected from all the possible profiles according to the cost function, and the optimal solution is defined as the weighted mean of all the valid profiles. A comprehensive error analysis is performed to better estimate the total uncertainty. Based on the assumption that the lookup table covers all possible profiles under clear-sky conditions, we determined a set of O4 DSCD scaling factors for different elevation angles and wavelengths. The profiles retrieved from synthetic measurement data can reproduce the synthetic profile. The results also show that the retrieval is insensitive to measurement noise, indicating the retrieval is robust and stable. The aerosol optical depths (AODs) retrieved from the long-term measurements were compared to coinciding and co-located sun photometer observations. High correlation coefficients (R) of 0.733 and 0.798 are found for measurements at 360 and 477 nm, respectively. However, especially in summer, the sun photometer AODs are systematically higher than the MAX-DOAS retrievals by a factor of ∼2. The discrepancy might be related to the limited measurement range of the MAX-DOAS and is probably also related to the decreased sensitivity of the MAX-DOAS measurements at higher altitudes. The MAX-DOAS measurements indicate the aerosol extinction decreases with increasing altitude during all seasons, which agrees with the co-located ceilometer measurements. Our results also show maximum AOD and maximum Ångström exponent in summer, which is consistent with observations at an AERONET station located ∼43 km from the UFS.

We present different methods for in-field elevation calibration of MAX-DOAS (Multi AXis Differential Optical Absorption Spectroscopy) instruments that were applied and inter-compared during the second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2). One necessary prerequisite of consistent MAX-DOAS retrievals is a precise and accurate calibration of the elevation angles of the different measuring systems. Therefore, different methods for this calibration were applied to several instruments during the campaign, and the results were inter-compared. This work first introduces and explains the different methods, namely far- and near-lamp measurements, white-stripe scans, horizon scans and sun scans, using data and results for only one (mainly the Max Planck Institute for Chemistry) instrument. In the second part, the far-lamp measurements and the horizon scans are examined for all participating groups. Here, the results for both methods are first inter-compared for the different instruments; secondly, the two methods are compared amongst each other. All methods turned out to be well-suited for the calibration of the elevation angles of MAX-DOAS systems, with each of them having individual advantages and drawbacks. Considering the results of this study, the systematic uncertainties of the methods can be estimated as ±0.05∘ for the far-lamp measurements and the sun scans, ±0.25∘ for the horizon scans, and around ±0.1∘ for the white-stripe and near-lamp measurements. When comparing the results of far-lamp and horizon-scan measurements, a spread of around 0.9∘ in the elevation calibrations is found between the participating instruments for both methods. This spread is of the order of a typical field of view (FOV) of a MAX-DOAS instrument and therefore affecting the retrieval results. Further, consistent (wavelength dependent) offsets of 0.32∘ and 0.40∘ between far-lamp measurements and horizon scans are found, which can be explained by the fact that, despite the flat topography around the measurement site, obstacles such as trees might mark the visible horizon during daytime. The observed wavelength dependence can be explained by surface albedo effects. Lastly, the results are discussed and recommendations for future campaigns are given.

In this paper, we present long-term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground-based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate ozone monitoring instrument (OMI) satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by ∼30 % with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. An age-weighted backward-propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward-propagated HCHO data do not show a strong spatial correlation with the OMI HCHO observations. The result shows that the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %–50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants over the Yangtze River Delta as well as the effect of emission control measures during large international events, which are important for the future design of air pollution control policies.

In this study the consistency between MAX-DOAS measurements and radiative transfer simulations of the atmospheric O4 absorption is investigated on 2 mainly cloud-free days during the MAD-CAT campaign in Mainz, Germany, in summer 2013. In recent years several studies indicated that measurements and radiative transfer simulations of the atmospheric O4 absorption can only be brought into agreement if a so-called scaling factor () is applied to the measured O4 absorption. However, many studies, including those based on direct sunlight measurements, came to the opposite conclusion, that there is no need for a scaling factor. Up to now, there is no broad consensus for an explanation of the observed discrepancies between measurements and simulations. Previous studies inferred the need for a scaling factor from the comparison of the aerosol optical depths derived from MAX-DOAS O4 measurements with that derived from coincident sun photometer measurements. In this study a different approach is chosen: the measured O4 absorption at 360 nm is directly compared to the O4 absorption obtained from radiative transfer simulations. The atmospheric conditions used as input for the radiative transfer simulations were taken from independent data sets, in particular from sun photometer and ceilometer measurements at the measurement site. This study has three main goals: first all relevant error sources of the spectral analysis, the radiative transfer simulations and the extraction of the input parameters used for the radiative transfer simulations are quantified. One important result obtained from the analysis of synthetic spectra is that the O4 absorptions derived from the spectral analysis agree within 1 % with the corresponding radiative transfer simulations at 360 nm. Based on the results from sensitivity studies, recommendations for optimised settings for the spectral analysis and radiative transfer simulations are given. Second, the measured and simulated results are compared for 2 selected cloud-free days with similar aerosol optical depths but very different aerosol properties. On 18 June, measurements and simulations agree within their (rather large) uncertainties (the ratio of simulated and measured O4 absorptions is found to be 1.01±0.16). In contrast, on 8 July measurements and simulations significantly disagree: for the middle period of that day the ratio of simulated and measured O4 absorptions is found to be 0.82±0.10, which differs significantly from unity. Thus, for that day a scaling factor is needed to bring measurements and simulations into agreement. Third, recommendations for further intercomparison exercises are derived. One important recommendation for future studies is that aerosol profile data should be measured at the same wavelengths as the MAX-DOAS measurements. Also, the altitude range without profile information close to the ground should be minimised and detailed information on the aerosol optical and/or microphysical properties should be collected and used. The results for both days are inconsistent, and no explanation for a O4 scaling factor could be derived in this study. Thus, similar but more extended future studies should be performed, including more measurement days and more instruments. Also, additional wavelengths should be included.

In this paper we present an investigation of the spatial and temporal variability of street-level concentrations of NO2 in Hong Kong as an example of a densely populated megacity with heavy traffic. For the study we use a combination of open-path remote sensing and in situ measurement techniques that allows us to separate temporal changes and spatial patterns and analyse them separately. Two measurement campaigns have been conducted, one in December 2010 and one in March 2017. Each campaign lasted for a week which allowed us to examine diurnal cycles, weekly patterns as well as spatially resolved long-term changes. We combined a long-path differential optical absorption spectroscopy (DOAS) instrument with a cavity-enhanced DOAS and applied several normalizations to the data sets in order to make the different measurement routes comparable. For the analysis of long-term changes we used the entire unfiltered data set and for the comparison of spatial patterns we filtered out the accumulation of NO2 when stopping at traffic lights for focusing on the changes of NO2 spatial distribution instead of comparing traffic flow patterns. For the generation of composite maps the diurnal cycle has been normalized by scaling the mobile data with coinciding citywide path-averaged measurement results. An overall descending trend from 2010 to 2017 could be observed, consistent with the observations of the Ozone Monitoring Instrument (OMI) and the Environment Protection Department (EPD) air quality monitoring network data. However, long-term difference maps show pronounced spatial structures with some areas, e.g. around subway stations, revealing an increasing trend. We could also show that the weekend effect, which for the most part of Hong Kong shows reduced NO2 concentrations on Sundays and to a lesser degree on Saturdays, is reversed around shopping malls. Our study shows that spatial differences have to be considered when discussing citywide trends and can be used to put local point measurements into perspective. The resulting data set provides a better insight into on-road NO2 characteristics in Hong Kong, which helps to identify heavily polluted areas and represents a useful database for urban planning and the design of pollution control measures.

In this study, we use sunphotometer (AERONET) data as reference to evaluate MODIS, Himawari-08, and MERRA-2 aerosol products over China. AERONET data from Beijing, Xianghe, Xuzhou, Taihu and Hong Kong are used. The results indicate that aerosol optical depths (AODs) obtained from MODIS, Himawari-08, and MERRA-2 from 2015-2017 over China are consistent with the AERONET observations. The accuracy of these AOD products shows a spatial and temporal variation. MODIS aerosol products tend to overestimate the AODs at Beijing, Xianghe and Xuzhou, with stronger overestimation in winter. For Taihu and Hong Kong, MODIS only overestimates the AODs in winter. Himawari-08 and MERRA-2 underestimate the AODs in autumn over almost all stations except Taihu.

In this paper, we present a comparison of model simulations of aerosol profiles with measurements of the ceilometer network operated by the German Weather Service (DWD) over 1 year from September 2015 to August 2016. The aerosol forecasts are produced by the Copernicus Atmosphere Monitoring Service (CAMS) using the aerosol module developed within the Global and regional Earth-system Monitoring using Satellite and in-situ data (GEMS) and Monitoring Atmospheric Composition and Climate (MACC) projects and coupled into the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS). As the model output provides mass mixing ratios of different types of aerosol, whereas the ceilometers do not, it is necessary to determine a common physical quantity for the comparison. We have chosen the attenuated backscatter β∗ for this purpose. The β∗ profiles are calculated from the mass mixing ratios of the model output assuming the inherent aerosol microphysical properties. Comparison of the attenuated backscatter averaged between an altitude of 0.2 km (typical overlap range of ceilometers) and 1 km in general shows similar annual average values. However, the standard deviation of the difference between model and observation is larger than the average in 8 out of 12 sites.To investigate possible reasons for the differences, we have examined the role of the hygroscopic growth of particles and the particle shape. Our results show that using a more recent particle growth model would result in a ∼ 22 % reduction of particle backscatter for sea salt aerosols, corresponding to a 10 % reduction of the total backscatter signal on average. Accounting for nonspherical dust particles in the model would reduce attenuated backscatter of dust particles by ∼ 30 %. As the concentration of dust aerosol is in general very low in Germany, a significant effect on the total backscatter signal is restricted to dust episodes. In summary, consideration of both effects tends to improve the agreement between model and observations but without leading to a perfect consistency.In addition, a strong Saharan dust event was investigated to study the agreement of the spatiotemporal distribution of particles. It was found that the arrival time of the dust layer and its vertical extent very well agree between model and ceilometer measurements for several stations. This underlines the potential of a network of ceilometers to validate the dispersion of aerosol layers.

Abstract The segmentation of moving objects in image sequence can be formulated as a background subtraction problem—the separation of objects from the background in each image frame. The background scene is learned and modeled. A pixelwise process is employed to classify each pixel as an object or background based on its similarity with the background model. The segmentation is challenging due to the occurrence of dynamic elements such as illumination change and background motions. We propose a framework for object segmentation with a novel feature for background representation and new mechanisms for updating the background model. A ternary pattern is employed to characterize the local texture. The pattern and photometric features are used for background modeling. The classification of pixel is performed based on the perceptual similarity between the current pixel and the background model. The segmented object is refined by taking into account the spatial consistency of the image feature. For the background model update, we propose two mechanisms that are able to adapt to abrupt background change and also merge new background elements into the model. We compare our framework with various background subtraction algorithms on video datasets.

In this paper, we present ship-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements of tropospheric trace gases' distribution along the Yangtze River during winter 2015. The measurements were performed along the Yangtze River between Shanghai and Wuhan, covering major industrial areas in eastern China. Tropospheric vertical column densities (VCDs) of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) were retrieved using the air mass factor calculated by the radiative transfer model. Enhanced tropospheric NO2 and SO2 VCDs were detected over downwind areas of industrial zones over the Yangtze River. In addition, spatial distributions of atmospheric pollutants are strongly affected by meteorological conditions; i.e., positive correlations were found between concentration of pollutants and wind speed over these areas, indicating strong influence of transportation of pollutants from high-emission upwind areas along the Yangtze River. Comparison of tropospheric NO2 VCDs between ship-based MAX-DOAS and Ozone Monitoring Instrument (OMI) satellite observations shows good agreement with each other, with a Pearson correlation coefficient (R) of 0.82. In this study, the NO2 ∕ SO2 ratio was used to estimate the relative contributions of industrial sources and vehicle emissions to ambient NO2 levels. Analysis results of the NO2 ∕ SO2 ratio show a higher contribution of industrial NO2 emissions in Jiangsu Province, while NO2 levels in Jiangxi and Hubei provinces are mainly related to vehicle emissions. These results indicate that different pollution control strategies should be applied in different provinces. In addition, multiple linear regression analysis of ambient carbon monoxide (CO) and odd oxygen (Ox) indicated that the primary emission and secondary formation of HCHO contribute 54.4 ± 3.7 % and 39.3 ± 4.3 % to the ambient HCHO, respectively. The largest contribution from primary emissions in winter suggested that photochemically induced secondary formation of HCHO is reduced due to lower solar irradiance in winter. Our findings provide an improved understanding of major pollution sources along the eastern part of the Yangtze River which are useful for designing specific air pollution control policies.

Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) and lidar measurements were performed in Shanghai, China, during May 2016 to investigate the vertical distribution of summertime atmospheric pollutants. In this study, vertical profiles of aerosol extinction coefficient, nitrogen dioxide (NO2) and formaldehyde (HCHO) concentrations were retrieved from MAX-DOAS measurements using the Heidelberg Profile (HEIPRO) algorithm, while vertical distribution of ozone (O3) was obtained from an ozone lidar. Sensitivity study of the MAX-DOAS aerosol profile retrieval shows that the a priori aerosol profile shape has significant influences on the aerosol profile retrieval. Aerosol profiles retrieved from MAX-DOAS measurements with Gaussian a priori profile demonstrate the best agreements with simultaneous lidar measurements and vehicle-based tethered-balloon observations among all a priori aerosol profiles. Tropospheric NO2 vertical column densities (VCDs) measured with MAX-DOAS show a good agreement with OMI satellite observations with a Pearson correlation coefficient (R) of 0.95. In addition, measurements of the O3 vertical distribution indicate that the ozone productions do not only occur at surface level but also at higher altitudes (about 1.1 km). Planetary boundary layer (PBL) height and horizontal and vertical wind field information were integrated to discuss the ozone formation at upper altitudes. The results reveal that enhanced ozone concentrations at ground level and upper altitudes are not directly related to horizontal and vertical transportation. Similar patterns of O3 and HCHO vertical distributions were observed during this campaign, which implies that the ozone productions near the surface and at higher altitudes are mainly influenced by the abundance of volatile organic compounds (VOCs) in the lower troposphere.

In this study, we present a quantitative estimation of the impacts of biomass burning emissions from different source regions to the local air quality in Hong Kong in 2014 using global chemistry transport model simulations, sun photometer measurements, satellite observations and local monitoring network data. This study focuses on two major biomass burning pollutants, black carbon aerosols and carbon monoxide (CO). The model simulations of atmospheric black carbon and CO show excellent agreement with sun photometer aerosol optical depth (AOD) measurements, satellite CO columns observations and local monitoring stations data. From the model simulation results, we estimated that biomass burning contributes 12 % of total black carbon and 16 % of atmospheric CO in Hong Kong on annual average. South East Asia shows the largest influence to the black carbon and CO levels in Hong Kong, accounts for 11 % of the total atmospheric black carbon and 8 % of CO. Biomass burning in North East Asia and Africa also show significant impacts to Hong Kong. Elevated levels of atmospheric black carbon aerosols and CO were observed during springtime (March and April) which is mainly due to the enhancement of biomass burning contributions. Black carbon and CO originating from biomass burning sources are estimated to contribute 40 % of atmospheric black carbon and 28 % of CO in Hong Kong during March 2014. An investigation focusing on the biomass burning pollution episode during springtime suggests the intensified biomass burning activities in the Indochinese Peninsula are the major sources of black carbon and CO in Hong Kong during the time.

We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2) products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO2 slant column density (SCD) retrieval and (2) higher-resolution (1° latitude and 1.25° longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry–transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by ∼ 10–40 %) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite- and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots.

The mixing layer height (MLH) is a measure for the vertical turbulent exchange within the boundary layer, which is one of the controlling factors for the dilution of pollutants emitted near the ground. Based on continuous MLH measurements with a Vaisala CL51 ceilometer and measurements from an air quality network, the relationship between MLH and near-surface pollutant concentrations has been investigated. In this context the uncertainty of the MLH retrievals and the representativeness of ground-based in situ measurements are crucial. We have investigated this topic by using data from the BAERLIN2014 campaign in Berlin, Germany, conducted from June to August 2014. To derive the MLH, three versions of the proprietary software BL-VIEW and a novel approach COBOLT were compared. It was found that the overall agreement is reasonable if mean diurnal cycles are considered. The main advantage of COBOLT is the continuous detection of the MLH with a temporal resolution of 10 min and a lower number of cases when the residual layer is misinterpreted as mixing layer. We have calculated correlations between MLH as derived from the different retrievals and concentrations of pollutants (PM10, O3 and NOx) for different locations in the metropolitan area of Berlin. It was found that the correlations with PM10 are quite different for different sites without showing a clear pattern, whereas the correlation with NOx seems to depend on the vicinity of emission sources in main roads. In the case of ozone as a secondary pollutant, a clear correlation was found. We conclude that the effects of the heterogeneity of the emission sources, chemical processing and mixing during transport exceed the differences due to different MLH retrievals. Moreover, it seems to be unrealistic to find correlations between MLH and near-surface pollutant concentrations representative for a city like Berlin (flat terrain), in particular when traffic emissions are dominant. Nevertheless it is worthwhile to use advanced MLH retrievals for ceilometer data, for example as input to dispersion models and for the validation of chemical transport models.

Lipase class 3 is part of the triacylglycerol lipase family involved in lipid degradation, esterification, and transesterification processes in plants. In this study, a lipase class 3 gene and promoter from oil palm (Elaeis guineensis Jacq.) were isolated and characterized by Northern blot, Southern blot, oil palm genome sequence, and transient expression GUS assay. The full-length lipase class 3 (FLL1) deduced polypeptide encoded 483 amino acids and was identical to that deduced from lipase (EgLip1) cDNA (GI: 409994625). It contained the lipase consensus sequence, GxSxG motif, and a putative catalytic triad and had a 3-dimensional protein model similar to that of a lipase from Giberella zeae with a 50 % identity. The Northern blot and reverse transcription polymerase chain reaction (RT-PCR) show that FLL1 was predominantly expressed in the mesocarp and the expression increased as fruits reached maturity. A lower expression was detected in germinated seedlings and especially in roots. The expression of FLL1 was also enhanced in the mesocarp of cold treated fruits. A high oil accumulation in the mesocarp during fruit development makes this tissue a suitable target for a genetic modification, hence the isolation of the FLL1 promoter. The transient expression of the β-glucuronidase (GUS) gene driven by the FLL1 promoter detected the GUS expression in mesocarp slices, especially in vascular bundles. This suggests the potential role of using the promoter as tool to direct the expression of a transgene to the mesocarp of transgenic oil palm.

Mobile passive differential optical absorption spectroscopy measurements of SO2 and NO2 were performed in the Guangzhou eastern area (GEA) during the Guangzhou Asian Games 2010 from November 2010 to December 2010. The observations were carried out between 10:00 to 13:00 (local time, i.e., during daylight). Spatial and temporal distributions of SO2 and NO2 in this area were obtained and emission sources were determined using wind field data. The NO2 vertical column densities were found to agree with Ozone Monitoring Instrument values. The correlation coefficient (referred to as R2) was 0.88 after cloud filtering within a specific ground pixel. During the Guangzhou Asian Games and Asian Paralympics (Para) Games, the SO2 and NOx emissions in the area were quantified using averaged wind speed and wind direction. For times outside the games the average SO2 emission was estimated to be 9.50 ± 0.90 tons per hour and the average NOx emission was estimated to be 5.87 ± 3.46 tons per hour. During the phases of the Asian and Asian Para Games, the SO2 and NOx emissions were reduced by 53.50% and 43.50%, respectively, compared to the usual condition. We also investigated the influence of GEA on Guangzhou University Town, the main venue located northwest of the GEA, and found that SO2 concentrations here were about tripled by emissions from the GEA.

In this paper, we present an optimized analysis algorithm for non-dispersive infrared (NDIR) to in situ monitor stack emissions. The proposed algorithm simultaneously compensates for nonlinear absorption and cross interference among different gases. We present a mathematical derivation for the measurement error caused by variations in interference coefficients when nonlinear absorption occurs. The proposed algorithm is derived from a classical one and uses interference functions to quantify cross interference. The interference functions vary proportionally with the nonlinear absorption. Thus, interference coefficients among different gases can be modeled by the interference functions whether gases are characterized by linear or nonlinear absorption. In this study, the simultaneous analysis of two components (CO2 and CO) serves as an example for the validation of the proposed algorithm. The interference functions in this case can be obtained by least-squares fitting with third-order polynomials. Experiments show that the results of cross interference correction are improved significantly by utilizing the fitted interference functions when nonlinear absorptions occur. The dynamic measurement ranges of CO2 and CO are improved by about a factor of 1.8 and 3.5, respectively. A commercial analyzer with high accuracy was used to validate the CO and CO2 measurements derived from the NDIR analyzer prototype in which the new algorithm was embedded. The comparison of the two analyzers show that the prototype works well both within the linear and nonlinear ranges.

In this study we present the first long term measurements of atmospheric nitrogen dioxide (NO2) using a LED based Long Path Differential Optical Absorption Spectroscopy (LP-DOAS) instrument. This instrument is measuring continuously in Hong Kong since December 2009, first in a setup with a 550 m absorption path and then with a 3820 m path at about 30 m to 50 m above street level. The instrument is using a high power blue light LED with peak intensity at 450 nm coupled into the telescope using a Y-fibre bundle. The LP-DOAS instrument measures NO2 levels in the Kowloon Tong and Mongkok district of Hong Kong and we compare the measurement results to mixing ratios reported by monitoring stations operated by the Hong Kong Environmental Protection Department in that area. Hourly averages of coinciding measurements are in reasonable agreement (R = 0.74). Furthermore, we used the long-term data set to validate the Ozone Monitoring Instrument (OMI) NO2 data product. Monthly averaged LP-DOAS and OMI measurements correlate well (R = 0.84) when comparing the data for the OMI overpass time. We analyzed weekly patterns in both data sets and found that the LP-DOAS detects a clear weekly cycle with a reduction on weekends during rush hour peaks, whereas OMI is not able to observe this weekly cycle due to its fix overpass time (13:30–14:30 LT – local time).

At high latitudes in the upper mesosphere, horizontal wind oscillations have been observed with periods around 10h. Waves with such a period are generated in our Numerical Spectral Model (NSM), and they are identified as planetary-scale inertio gravity waves (IGW). These IGWs have periods between 9 and 11h and appear above 60km in the zonal mean (m=0), as well as in m=1 to 4, propagating eastward and westward. Under the influence of the Coriolis force, the amplitudes of the waves propagating westward are larger at high latitudes than those propagating eastward. The waves grow in magnitude at least up to about 100km and have vertical wavelengths around 25km. Applying a running window of 15 days for spectral analysis, the amplitudes in the wind field are typically between 10 and 20m/s and can reach 30m/s in the westward propagating component for m=1 at the poles. In the temperature perturbations, the wave amplitudes above 100km are typically 5K and as large as 10K for m=0 at the poles. The IGWs are intermittent but reveal systematic seasonal variations, with the largest amplitudes occurring generally in late winter and spring. Numerical experiments show that such waves are also generated without excitation of the migrating tides. The amplitudes and periods then are similar, indicating that the tides are not essential to generate the waves. However, the seasonal variations without tides are significantly different, which leads to the conclusion that non linear interactions between the semidiurnal tide and planetary waves must contribute to the excitation of the IGWs. Directly or indirectly through the planetary waves, the IGWs are apparently excited by the instabilities that arise in the zonal mean circulation. When the solar heating is turned off for m=0, both the PWs and IGWs essentially disappear. That the IGWs and PWs have common roots in their excitation mechanism is also indicated by the striking similarity of their seasonal variations in the lower mesosphere. Compared to the PWs, however, the planetary-scale IGWs propagate zonally with much larger phase speeds. In contrast to the PWs, the IGWs thus are not affected much by interactions with the background zonal winds whose seasonal variations drastically change with altitude in the mesosphere. Since the IGWs can propagate through the mesosphere without much interaction, except for viscous dissipation, one should then expect that they reach the thermosphere above with significant and measurable amplitudes.

The Numerical Spectral Model (NSM) extends from the ground into the thermosphere and incorporates Hines' Doppler Spread Parameterization for small-scale gravity waves (GWs). In the present version of the model we account for a tropospheric heat source in the zonal mean (m=0), which reproduces qualitatively the observed zonal jets near the tropopause and the accompanying reversal in the latitudinal temperature variations. In the study presented here, we discuss the planetary waves (PWs) that are solely generated internally, i.e. without the explicit excitation sources related to tropospheric convection or topography. Our analysis shows that PWs are not produced when the zonally averaged heat source into the atmosphere is artificially suppressed, and that the PWs are generally weaker when the tropospheric source is not applied. Instabilities associated with the zonal mean temperature, pressure and wind fields, which still need to be explored, are exciting PWs that have amplitudes in the mesosphere comparable to those observed. Three classes of PWs are generated in the NSM. (1) Rossby type PWs, which slowly propagate westward relative to the mean zonal flow, are carried by the winds so that they appear (from the ground) to propagate, respectively, eastward and westward in the winter and summer hemispheres below 80km. Depending on the zonal wave number and magnitudes of the zonal winds, and under the influence of the equatorial oscillations, these PWs typically have periods between 2 and 20 days. Their horizontal wind amplitudes can exceed 40 m/s in the lower mesosphere. (2) Rossby-gravity waves, which propagate westward at low latitudes and have periods around 2 days for zonal wave numbers m=2 to 4. (3) Eastward propagating equatorial Kelvin waves, which are generated in the upper mesosphere with periods between 1 and 3 days depending on m. A survey of the PWs reveals that the largest wind amplitudes tend to occur below 80km in the winter hemisphere; but above that altitude the amplitudes are larger in the summer hemisphere where the winds can approach 50m/s. This pattern in the seasonal variations also appears in the baroclinity of the zonal mean (m=0). The nonmigrating tides in the mesosphere are significantly larger for the model with the tropospheric heat source, in which PWs are apparently generated by the instabilities that arise around the tropopause.