Tropical temperature altitude amplification in the hiatus period (1998-2012)

In the period 1998-2012 there was a stagnation in temperature rise, despite the GHGs radiation forcing is increased (hiatus period). According to Global Circulation Models simulations, expected response on the rise of GHGs forcing is tropical temperature altitude amplification - temperature increases faster in higher troposphere than in lower troposphere. In this paper, two satellite data sets, UAH MSU and RSS, were used to test altitude temperature amplification in tropic (20?N-20?S) in the hiatus period. We compared data from satellite data sets from lower troposphere (TLT) and middle troposphere (TMT) in general and particularly for land and ocean (for UAH MSU). The results from both satellite measurements showed the presence of hiatus, i.e. slowdown of the temperature rise in the period 1998-2012 compared to period 1979-2012 (UAH MSU) and temperature fall for RSS data. Smaller increase, i.e. temperature fall over ocean showed that hiatus is an ocean phenomenon above all. Data for UAH MSU showed that temperature altitude amplification in tropic was not present either for period 1979-2012, or 1998-2012. RSS data set also do not show temperature altitude amplification either for longer (1979-2012), or for shorter period (1998-2012). RSS data for successive 15-year periods from 1979-1993 till 1998-2012 does not show tropical temperature altitude amplification and in one case negative trend is registered in TLT and in two cases in TMT. In general, our results do not show presence of temperature altitude amplification in tropic in the hiatus period.

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Global carbon monoxide products from combined AIRS, TES and MLS measurements on A-train satellites

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-103-2014 ◽

2014 ◽

Vol 14 (1) ◽

pp. 103-114 ◽

Cited By ~ 11

Author(s):

J. X. Warner ◽

R. Yang ◽

Z. Wei ◽

F. Carminati ◽

A. Tangborn ◽

...

Keyword(s):

Carbon Monoxide ◽

Data Fusion ◽

Satellite Data ◽

Lower Troposphere ◽

Data Sets ◽

Data Set ◽

Upper Troposphere ◽

In Situ Data ◽

Spatial Coverage

Abstract. This study tests a novel methodology to add value to satellite data sets. This methodology, data fusion, is similar to data assimilation, except that the background model-based field is replaced by a satellite data set, in this case AIRS (Atmospheric Infrared Sounder) carbon monoxide (CO) measurements. The observational information comes from CO measurements with lower spatial coverage than AIRS, namely, from TES (Tropospheric Emission Spectrometer) and MLS (Microwave Limb Sounder). We show that combining these data sets with data fusion uses the higher spectral resolution of TES to extend AIRS CO observational sensitivity to the lower troposphere, a region especially important for air quality studies. We also show that combined CO measurements from AIRS and MLS provide enhanced information in the UTLS (upper troposphere/lower stratosphere) region compared to each product individually. The combined AIRS–TES and AIRS–MLS CO products are validated against DACOM (differential absorption mid-IR diode laser spectrometer) in situ CO measurements from the INTEX-B (Intercontinental Chemical Transport Experiment: MILAGRO and Pacific phases) field campaign and in situ data from HIPPO (HIAPER Pole-to-Pole Observations) flights. The data fusion results show improved sensitivities in the lower and upper troposphere (20–30% and above 20%, respectively) as compared with AIRS-only version 5 CO retrievals, and improved daily coverage compared with TES and MLS CO data.

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Two years of Ozone radio soundings over Cotonou as part of AMMA: overview

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-11221-2009 ◽

2009 ◽

Vol 9 (3) ◽

pp. 11221-11268 ◽

Cited By ~ 3

Author(s):

V. Thouret ◽

M. Saunois ◽

A. Minga ◽

A. Mariscal ◽

B. Sauvage ◽

...

Keyword(s):

West Africa ◽

Biomass Burning ◽

Lower Stratosphere ◽

Lower Troposphere ◽

Data Sets ◽

Wet Season ◽

Data Set ◽

In Situ Data ◽

Multidisciplinary Analysis ◽

First Time

Abstract. As part of the African Monsoon Multidisciplinary Analysis (AMMA) program, a total of 98 ozone vertical profiles over Cotonou, Benin, have been measured during a 26 month period (December 2004–January 2007). These regular measurements broadly document the seasonal and inter annual variability of ozone in both the troposphere and the lower stratosphere over West Africa for the first time. This data set is complementary to the MOZAIC observations made from Lagos between 0 and 12 km during the period 1998–2004. Both data sets highlight the unique way in which West Africa is impacted by two biomass burning seasons: in December–February (dry season) due to burning in the Sahelian band and in June–August (wet season) due to burning in southern Africa. High inter annual variabilities between Cotonou and Lagos data sets and within each data set are observed and are found to be a major characteristic of this region. In particular, the dry and wet seasons are discussed in order to set the data of the Special Observing Periods (SOPs) into a climatological context. Compared to other dry and wet seasons, the dry and wet season campaigns took place in rather high ozoneenvironments. During the sampled wet seasons, southern intrusions of biomass burning were particularly frequent with concentrations up to 120 ppbv of ozone in the lower troposphere. An insight into the ozone distribution in the upper troposphere and the lower stratosphere (up to 26 km) is given. The first tropospheric columns of ozone based on in-situ data in this region are assessed. They compare well with satellite products on seasonal and inter annual time-scales, provided that the layer below 850 Pa where the remote instrument is less sensitive to ozone, is removed.

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Are there urban signatures in the tropospheric ozone column products derived from satellite measurements?

Atmospheric Chemistry and Physics ◽

10.5194/acp-10-5213-2010 ◽

2010 ◽

Vol 10 (11) ◽

pp. 5213-5222 ◽

Cited By ~ 32

Author(s):

J. Kar ◽

J. Fishman ◽

J. K. Creilson ◽

A. Richter ◽

J. Ziemke ◽

...

Keyword(s):

Tropospheric Ozone ◽

Lower Troposphere ◽

Data Sets ◽

Ozone Monitoring Instrument ◽

Satellite Measurements ◽

Ratio Distribution ◽

Total Column Ozone ◽

Scanning Imaging ◽

Column Ozone ◽

Ozone Column

Abstract. In view of the proposed geostationary satellite missions to monitor air quality from space, it is important to first assess the capability of the current suite of satellite instruments to provide information on the urban scale pollution. We explore the possibility of detecting urban signatures in the tropospheric column ozone data derived from Total Ozone Mapping Spectrometer (TOMS)/Solar Backscattered Ultraviolet (SBUV) and Ozone Monitoring Instrument (OMI)/Microwave Limb Sounder (MLS) satellite data. We find that distinct isolated plumes of tropospheric ozone near several large and polluted cities around the world may be detected in these data sets. The ozone plumes generally correspond with the tropospheric column NO2 plumes around these cities as observed by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument. Similar plumes are also seen in tropospheric mean ozone mixing ratio distribution after accounting for the surface and tropopause pressure variations. The total column ozone retrievals indicate fairly significant sensitivity to the lower troposphere over the polluted land areas, which might help explain these detections. These results indicate that ultraviolet (UV) measurements may, in principle, be able to capture the urban signatures and may have implications for future missions using geostationary satellites.

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An overview of two years of ozone radio soundings over Cotonou as part of AMMA

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-6157-2009 ◽

2009 ◽

Vol 9 (16) ◽

pp. 6157-6174 ◽

Cited By ~ 39

Author(s):

V. Thouret ◽

M. Saunois ◽

A. Minga ◽

A. Mariscal ◽

B. Sauvage ◽

...

Keyword(s):

West Africa ◽

Biomass Burning ◽

Lower Stratosphere ◽

Lower Troposphere ◽

Data Sets ◽

Wet Season ◽

Data Set ◽

In Situ Data ◽

Multidisciplinary Analysis ◽

First Time

Abstract. As part of the African Monsoon Multidisciplinary Analysis (AMMA) program, a total of 98 ozone vertical profiles over Cotonou, Benin, have been measured during a 26 month period (December 2004–January 2007). These regular measurements broadly document the seasonal and interannual variability of ozone in both the troposphere and the lower stratosphere over West Africa for the first time. This data set is complementary to the MOZAIC observations made from Lagos between 0 and 12 km during the period 1998–2004. Both data sets highlight the unique way in which West Africa is impacted by two biomass burning seasons: in December–February (dry season) due to burning in the Sahelian band and in June-August (wet season) due to burning in southern Africa. High interannual variabilities between Cotonou and Lagos data sets and within each data set are observed and are found to be a major characteristic of this region. In particular, the dry and wet seasons are discussed in order to set the data of the Special Observing Periods (SOPs) into a climatological context. Compared to other dry and wet seasons, the 2006 dry and wet season campaigns took place in rather high ozone environments. During the sampled wet seasons, southern intrusions of biomass burning were particularly frequent with concentrations up to 120 ppbv of ozone in the lower troposphere. An insight into the ozone distribution in the upper troposphere and the lower stratosphere (up to 26 km) is given. The first tropospheric columns of ozone based on in-situ data over West Africa are assessed. They compare well with satellite products on seasonal and interannual time-scales, provided that the layer below 850 hPa where the remote instrument is less sensitive to ozone, is removed.

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Some experimental constraints for spectral parameters used in the Warner and McIntyre gravity wave parameterization scheme

Atmospheric Chemistry and Physics ◽

10.5194/acp-6-4361-2006 ◽

2006 ◽

Vol 6 (12) ◽

pp. 4361-4381 ◽

Cited By ~ 49

Author(s):

M. Ern ◽

P. Preusse ◽

C. D. Warner

Keyword(s):

Gravity Wave ◽

Spectral Power ◽

Initial Guess ◽

Parameterization Scheme ◽

Satellite Measurements ◽

Spectral Parameters ◽

Global Circulation ◽

Parameterization Schemes ◽

Global Circulation Models ◽

Global Parameters

Abstract. In order to incorporate the effect of gravity waves (GWs) on the atmospheric circulation most global circulation models (GCMs) employ gravity wave parameterization schemes. To date, GW parameterization schemes in GCMs are used without experimental validation of the set of global parameters assumed for the GW launch spectrum. This paper focuses on the Warner and McIntyre GW parameterization scheme. Ranges of parameters compatible with absolute values of gravity wave momentum flux (GW-MF) derived from CRISTA-1 and CRISTA-2 satellite measurements are deduced for several of the parameters and the limitations of both model and measurements are discussed. The findings presented in this paper show that the initial guess of spectral parameters provided by by Warner and McIntyre (2001) are some kind of compromise with respect to agreement of absolute values and agreement of the horizontal structures found in both measurements and model results. Better agreement can be achieved by using a vertical wavenumber launch spectrum with a wider saturated spectral range and reduced spectral power in the unsaturated part. However, even with this optimized set of global launch parameters not all features of the measurements are matched. This indicates that for further improvement spatial and seasonal variations of the launch parameters should be included in GW parameterization schemes.

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Comparisons of Satellite and Modeled Surface Temperature and Chlorophyll Concentrations in the Baltic Sea with In Situ Data

Remote Sensing ◽

10.3390/rs13153049 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3049

Author(s):

Malgorzata Stramska ◽

Marta Konik ◽

Paulina Aniskiewicz ◽

Jaromir Jakacki ◽

Miroslaw Darecki

Keyword(s):

Baltic Sea ◽

Satellite Data ◽

In Situ Measurements ◽

Data Sets ◽

The Baltic Sea ◽

Data Set ◽

In Situ Data ◽

The Baltic ◽

Good Agreement

Among the most frequently used satellite data are surface chlorophyll concentration (Chl) and temperature (SST). These data can be degraded in some coastal areas, for example, in the Baltic Sea. Other popular sources of data are reanalysis models. Before satellite or model data can be used effectively, they should be extensively compared with in situ measurements. Herein, we present results of such comparisons. We used SST and Chl from model reanalysis and satellites, and in situ data measured at eight open Baltic Sea stations. The data cover time interval from 1 January 1998 to 31 December 2019, but some satellite data were not always available. Both the model and the satellite SST data had good agreement with in situ measurements. In contrast, satellite and model estimates of Chl concentrations presented large errors. Modeled Chl presented the lowest bias and the best correlation with in situ data from all Chl data sets evaluated. Chl estimates from a regionally tuned algorithm (SatBaltic) had smaller errors in comparison with other satellite data sets and good agreement with in situ data in summer. Statistics were not as good for the full data set. High uncertainties found in chlorophyll satellite algorithms for the Baltic Sea highlight the importance of continuous regional validation of such algorithms with in situ data.

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Gap-Filling of NDVI Satellite Data Using Tucker Decomposition: Exploiting Spatio-Temporal Patterns

Remote Sensing ◽

10.3390/rs13194007 ◽

2021 ◽

Vol 13 (19) ◽

pp. 4007

Author(s):

Andri Freyr Þórðarson ◽

Andreas Baum ◽

Mónica García ◽

Sergio M. Vicente-Serrano ◽

Anders Stockmarr

Keyword(s):

Missing Data ◽

Iberian Peninsula ◽

Satellite Data ◽

Simulated Data ◽

Principal Component ◽

Decomposition Methods ◽

Data Sets ◽

Gap Filling ◽

Data Set ◽

Spatio Temporal

Remote sensing satellite images in the optical domain often contain missing or misleading data due to overcast conditions or sensor malfunctioning, concealing potentially important information. In this paper, we apply expectation maximization (EM) Tucker to NDVI satellite data from the Iberian Peninsula in order to gap-fill missing information. EM Tucker belongs to a family of tensor decomposition methods that are known to offer a number of interesting properties, including the ability to directly analyze data stored in multidimensional arrays and to explicitly exploit their multiway structure, which is lost when traditional spatial-, temporal- and spectral-based methods are used. In order to evaluate the gap-filling accuracy of EM Tucker for NDVI images, we used three data sets based on advanced very-high resolution radiometer (AVHRR) imagery over the Iberian Peninsula with artificially added missing data as well as a data set originating from the Iberian Peninsula with natural missing data. The performance of EM Tucker was compared to a simple mean imputation, a spatio-temporal hybrid method, and an iterative method based on principal component analysis (PCA). In comparison, imputation of the missing data using EM Tucker consistently yielded the most accurate results across the three simulated data sets, with levels of missing data ranging from 10 to 90%.

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3D Iterative Spatiotemporal Filtering for Classification of Multitemporal Satellite Data Sets

Photogrammetric Engineering & Remote Sensing ◽

10.14358/pers.86.1.23 ◽

2020 ◽

Vol 86 (1) ◽

pp. 23-31

Author(s):

Hessah Albanwan ◽

Rongjun Qin ◽

Xiaohu Lu ◽

Mao Li ◽

Desheng Liu ◽

...

Keyword(s):

Satellite Data ◽

Surface Model ◽

Data Sets ◽

Temporal Data ◽

Change Analysis ◽

Data Set ◽

Distribution Maps ◽

Multi Temporal ◽

Class Probability ◽

The Individual

The current practice in land cover/land use change analysis relies heavily on the individually classified maps of the multi-temporal data set. Due to varying acquisition conditions (e.g., illumination, sensors, seasonal differences), the classification maps yielded are often inconsistent through time for robust statistical analysis. 3D geometric features have been shown to be stable for assessing differences across the temporal data set. Therefore, in this article we investigate the use of a multi-temporal orthophoto and digital surface model derived from satellite data for spatiotemporal classification. Our approach consists of two major steps: generating per-class probability distribution maps using the random-forest classifier with limited training samples, and making spatiotemporal inferences using an iterative 3D spatiotemporal filter operating on per-class probability maps. Our experimental results demonstrate that the proposed methods can consistently improve the individual classification results by 2%–6% and thus can be an important postclassification refinement approach.

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Application of spectral analysis techniques to the intercomparison of aerosol data – Part 4: Synthesized analysis of multisensor satellite and ground-based AOD measurements using combined maximum covariance analysis

Atmospheric Measurement Techniques ◽

10.5194/amt-7-2531-2014 ◽

2014 ◽

Vol 7 (8) ◽

pp. 2531-2549 ◽

Cited By ~ 12

Author(s):

J. Li ◽

B. E. Carlson ◽

A. A. Lacis

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Satellite Data ◽

Covariance Analysis ◽

Data Sets ◽

Data Set ◽

Maximum Covariance Analysis ◽

Source Regions ◽

Cross Covariance ◽

Aerosol Source

Abstract. In this paper, we introduce the usage of a newly developed spectral decomposition technique – combined maximum covariance analysis (CMCA) – in the spatiotemporal comparison of four satellite data sets and ground-based observations of aerosol optical depth (AOD). This technique is based on commonly used principal component analysis (PCA) and maximum covariance analysis (MCA). By decomposing the cross-covariance matrix between the joint satellite data field and Aerosol Robotic Network (AERONET) station data, both parallel comparison across different satellite data sets and the evaluation of the satellite data against the AERONET measurements are simultaneously realized. We show that this new method not only confirms the seasonal and interannual variability of aerosol optical depth, aerosol-source regions and events represented by different satellite data sets, but also identifies the strengths and weaknesses of each data set in capturing the variability associated with sources, events or aerosol types. Furthermore, by examining the spread of the spatial modes of different satellite fields, regions with the largest uncertainties in aerosol observation are identified. We also present two regional case studies that respectively demonstrate the capability of the CMCA technique in assessing the representation of an extreme event in different data sets, and in evaluating the performance of different data sets on seasonal and interannual timescales. Global results indicate that different data sets agree qualitatively for major aerosol-source regions. Discrepancies are mostly found over the Sahel, India, eastern and southeastern Asia. Results for eastern Europe suggest that the intense wildfire event in Russia during summer 2010 was less well-represented by SeaWiFS (Sea-viewing Wide Field-of-view Sensor) and OMI (Ozone Monitoring Instrument), which might be due to misclassification of smoke plumes as clouds. Analysis for the Indian subcontinent shows that here SeaWiFS agrees best with AERONET in terms of seasonality for both the Gangetic Basin and southern India, while on interannual timescales it has the poorest agreement.

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Assessment of the interannual variability and influence of the QBO and upwelling on tracer–tracer distributions of N<sub>2</sub>O and O<sub>3</sub> in the tropical lower stratosphere

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-3619-2013 ◽

2013 ◽

Vol 13 (7) ◽

pp. 3619-3641 ◽

Cited By ~ 8

Author(s):

F. Khosrawi ◽

R. Müller ◽

J. Urban ◽

M. H. Proffitt ◽

G. Stiller ◽

...

Keyword(s):

Interannual Variability ◽

Satellite Data ◽

General Circulation ◽

Climate Model ◽

Potential Temperature ◽

Michelson Interferometer ◽

Data Sets ◽

Satellite Measurements ◽

Quasi Biennial Oscillation ◽

Model Simulations

Abstract. A modified form of tracer–tracer correlations of N2O and O3 has been used as a tool for the evaluation of atmospheric photochemical models. Applying this method, monthly averages of N2O and O3 are derived for both hemispheres by partitioning the data into altitude (or potential temperature) bins and then averaging over a fixed interval of N2O. In a previous study, the method has been successfully applied to the evaluation of two chemical transport models (CTMs) and one chemistry–climate model (CCM) using a 1 yr climatology derived from the Odin Sub-Millimetre Radiometer (Odin/SMR). However, the applicability of a 1 yr climatology of monthly averages of N2O and O3 has been questioned due to the inability of some CCMs to simulate a specific year for the evaluation of CCMs. In this study, satellite measurements from Odin/SMR, the Aura Microwave Limb Sounder (Aura/MLS), the Michelson Interferometer for Passive Atmospheric Sounding on ENVISAT (ENVISAT/MIPAS), and the Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA-1 and CRISTA-2) as well as model simulations from the Whole Atmosphere Community Climate Model (WACCM) are considered. By using seven to eight years of satellite measurements derived between 2003 and 2010 from Odin/SMR, Aura/MLS, ENVISAT/MIPAS and six years of model simulations from WACCM, the interannual variability of lower stratospheric monthly averages of N2O and O3 is assessed. It is shown that the interannual variability of the monthly averages of N2O and O3 is low, and thus can be easily distinguished from model deficiencies. Furthermore, it is investigated why large differences are found between Odin/SMR observations and model simulations from the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA) and the atmospheric general circulation model ECHAM5/Messy1 for the Northern and Southern Hemisphere tropics (0° to 30° N and 0° to −30° S, respectively). The differences between model simulations and observations are most likely caused by an underestimation of the quasi-biennial oscillation and tropical upwelling by the models as well as due to biases and/or instrument noise from the satellite instruments. A realistic consideration of the QBO in the model reduces the differences between model simulation and observations significantly. Finally, an intercomparison between Odin/SMR, Aura/MLS, ENVISAT/MIPAS and WACCM was performed. The comparison shows that these data sets are generally in good agreement, although some known biases of the data sets are clearly visible in the monthly averages. Nevertheless, the differences caused by the uncertainties of the satellite data sets are sufficiently small and can be clearly distinguished from model deficiencies. Thus, the method applied in this study is not only a valuable tool for model evaluation, but also for satellite data intercomparisons.

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