scholarly journals Strato-mesospheric carbon monoxide profiles above Kiruna, Sweden (67.8 ° N, 20.4 ° E), since 2008

2017 ◽  
Vol 9 (1) ◽  
pp. 77-89 ◽  
Author(s):  
Niall J. Ryan ◽  
Mathias Palm ◽  
Uwe Raffalski ◽  
Richard Larsson ◽  
Gloria Manney ◽  
...  
Keyword(s):  
Time Series ◽  
Carbon Monoxide ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Atmospheric Temperature ◽  
Temperature Data ◽  
Data Sets ◽  
Data Set ◽  
Co Concentrations

Abstract. This paper presents the retrieval and validation of a self-consistent time series of carbon monoxide (CO) above Kiruna using measurements from the Kiruna Microwave Radiometer (KIMRA). The data set currently spans the years 2008–2015, and measurements are ongoing at Kiruna. The spectra are inverted using an optimal estimation method to retrieve altitude profiles of CO concentrations in the atmosphere within an average altitude range of 48–84 km. Atmospheric temperature data from the Special Sensor Microwave Imager/Sounder aboard the US Air Force meteorological satellite DMSP-F18, are used in the inversion of KIMRA spectra between January 2011 and May 2014. This KIMRA CO data set is compared with CO data from the Microwave Limb Sounder aboard the Aura satellite: there is a maximum bias for KIMRA of  ∼  0.65 ppmv at 68 km (corresponding to 14.7 % of the mean CO value at 68 km) and a maximum relative bias of 22 % (0.44 ppmv) at 60 km. Standard deviations of the differences between profiles are similar in magnitude to the estimated uncertainties in the profiles. Correlations between the instruments are within 0.87 and 0.94. These numbers indicate agreement between the instruments. To expand the CO data set outside of the lifetime of DMSP-F18, another inversion setup was used that incorporates modelled temperatures from the European Centre for Medium-Range Weather Forecasts. The effect on the retrieved CO profiles when using a different temperature data set in the inversion was assessed. A comparison of the two overlapping KIMRA CO data sets shows a positive bias of  <  5 % in the extended data set and a correlation  >  0.98 between the lower retrievable altitude limit and 82.5 km. The extended data set shows a larger range ( ≤  6 %) of CO concentrations that is not explained by random error estimates. Measurements are continuing and the extended KIMRA CO time series currently spans 2008–2015, with gaps corresponding to non-operation and summer periods when CO concentrations below  ∼  90 km drop to very low values. The data can be accessed at doi:10.1594/PANGAEA.861730.

scholarly journals Strato-mesospheric carbon monoxide profiles above Kiruna since 2008

2016 ◽  
Author(s):  
Niall J. Ryan ◽  
Mathias Palm ◽  
Uwe Raffalski ◽  
Richard Larsson ◽  
Gloria Manney ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Atmospheric Temperature ◽  
Weather Forecasts ◽  
Us Air Force ◽  
Microwave Imager ◽  
High Level ◽  
Co Concentrations

Abstract. This paper presents the retrieval and validation of a self-consistent timeseries of carbon monoxide (CO) above Kiruna using measurements from the Kiruna Microwave Radiometer (KIMRA). The spectra are inverted using an optimal estimation method to retrieve altitude profiles of CO concentrations in the atmosphere within approximately 48–84 km altitude. Atmospheric temperature data from the Special Sensor Microwave Imager/Sounder aboard the US Air Force meteorological satellite, DMSP-F18, are used in the inversion of KIMRA spectra between January 2011 and May 2014. This dataset is compared with CO data from Microwave Limb Sounder aboard the Aura satellite and shows a high level of agreement at all altitudes: There is a maximum bias for KIMRA of ~ 0.65 ppm at 68 km (corresponding to 14.7 % of the mean CO value at 68 km), and correlations between the instruments are within 0.87 and 0.94. To expand the CO dataset outside of the lifetime of DMSP-F18, another inversion setup was used that incorporates modelled temperatures from the European Centre for Medium-Range Weather Forecasts. The effect on the retrieved CO profiles when using a different temperature dataset in the inversion was assessed. A comparison of the two overlapping KIMRA CO datasets shows a bias of  0.98 at all altitudes below 82.5 km. The extended dataset shows a higher variation (≤ 6 %) in CO concentrations that is not explained by random error estimates. The extended KIMRA CO timeseries currently spans 2008 to 2015, with gaps corresponding to non-operation and summer periods when CO concentrations below ~ 90 km drop to very low values. The data can be accessed at: https://doi.pangaea.de/10.1594/PANGAEA.861730.

scholarly journals Quality assessment of ground-based microwave measurements of chlorine monoxide, ozone, and nitrogen dioxide from the NDSC radiometer at the Plateau de Bure

2004 ◽  
Vol 22 (6) ◽  
pp. 1903-1915 ◽  
Author(s):  
P. Ricaud ◽  
P. Baron ◽  
J. de La Noë
Keyword(s):  
Microwave Radiometer ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Temporal Variations ◽  
Data Sets ◽  
Site Location ◽  
Data Set ◽  
Chlorine Monoxide ◽  
Slow Drift ◽  
Retrieval Scheme

Abstract. A ground-based microwave radiometer dedicated to chlorine monoxide (ClO) measurements around 278GHz has been in operation from December 1993-June 1996 at the Plateau de Bure, France (45° N, 5.9° E, 2500m altitude). It belongs to the international Network for the Detection of Stratospheric Change. A detailed study of both measurements and retrieval schemes has been undertaken. Although dedicated to the measurements of ClO, simultaneous profiles of O3, ClO and NO2, together with information about the instrumental baseline, have been retrieved using the optimal estimation method. The vertical profiles have been compared with other ground-based microwave data, satellite-borne data and model results. Data quality shows: 1) the weak sensitivity of the instrument that obliges to make time averages over several hours; 2) the site location where measurements of good opacities are possible for only a few days per year; 3) the baseline undulation affecting all the spectra, an issue common to all the microwave instruments; 4) the slow drift of some components affecting frequencies by 3-4MHz within a couple of months. Nevertheless, when temporally averaging data over a few days, ClO temporal variations (diurnal and over several weeks in winter 1995) from 35-50km are consistent with model results and satellite data, particularly at the peak altitude around 40km, although temporal coincidences are infrequent in winter 1995. In addition to ClO, it is possible to obtain O3 information from 30-60km whilst the instrument is not optimized at all for this molecule. Retrievals of O3 are reasonable when compared with model and another ground-based data set, although the lowermost layers are affected by the contamination of baseline remnants. Monthly-averaged diurnal variations of NO2 are detected at 40km and appear in agreement with photochemical model results and satellite zonally-averaged data, although the amplitude is weaker than the other data sets. This NO2 result highlights the great potential of the retrieval scheme used.

scholarly journals Five years of CO, HCN, C<sub>2</sub>H<sub>6</sub>, C<sub>2</sub>H<sub>2</sub>, CH<sub>3</sub>OH, HCOOH and H<sub>2</sub>CO total columns measured in the Canadian high Arctic

2014 ◽  
Vol 7 (6) ◽  
pp. 1547-1570 ◽  
Author(s):  
C. Viatte ◽  
K. Strong ◽  
K. A. Walker ◽  
J. R. Drummond
Keyword(s):  
Time Series ◽  
Fourier Transform ◽  
Biomass Burning ◽  
Atmospheric Chemistry ◽  
A Priori ◽  
Estimation Method ◽  
Optimal Estimation ◽  
High Arctic ◽  
Retrieval Algorithm ◽  
Data Set

Abstract. We present a five-year time series of seven tropospheric species measured using a ground-based Fourier transform infrared (FTIR) spectrometer at the Polar Environment Atmospheric Research Laboratory (PEARL; Eureka, Nunavut, Canada; 80°05' N, 86°42' W) from 2007 to 2011. Total columns and temporal variabilities of carbon monoxide (CO), hydrogen cyanide (HCN) and ethane (C2H6) as well as the first derived total columns at Eureka of acetylene (C2H2), methanol (CH3OH), formic acid (HCOOH) and formaldehyde (H2CO) are investigated, providing a new data set in the sparsely sampled high latitudes. Total columns are obtained using the SFIT2 retrieval algorithm based on the optimal estimation method. The microwindows as well as the a priori profiles and variabilities are selected to optimize the information content of the retrievals, and error analyses are performed for all seven species. Our retrievals show good sensitivities in the troposphere. The seasonal amplitudes of the time series, ranging from 34 to 104%, are captured while using a single a priori profile for each species. The time series of the CO, C2H6 and C2H2 total columns at PEARL exhibit strong seasonal cycles with maxima in winter and minima in summer, in opposite phase to the HCN, CH3OH, HCOOH and H2CO time series. These cycles result from the relative contributions of the photochemistry, oxidation and transport as well as biogenic and biomass burning emissions. Comparisons of the FTIR partial columns with coincident satellite measurements by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) show good agreement. The correlation coefficients and the slopes range from 0.56 to 0.97 and 0.50 to 3.35, respectively, for the seven target species. Our new data set is compared to previous measurements found in the literature to assess atmospheric budgets of these tropospheric species in the high Arctic. The CO and C2H6concentrations are consistent with negative trends observed over the Northern Hemisphere, attributed to fossil fuel emission decrease. The importance of poleward transport for the atmospheric budgets of HCN and C2H2 is highlighted. Columns and variabilities of CH3OH and HCOOH at PEARL are comparable to previous measurements performed at other remote sites. However, the small columns of H2CO in early May might reflect its large atmospheric variability and/or the effect of the updated spectroscopic parameters used in our retrievals. Overall, emissions from biomass burning contribute to the day-to-day variabilities of the seven tropospheric species observed at Eureka.

scholarly journals Mesospheric CO above Troll station, Antarctica observed by a ground based microwave radiometer

2013 ◽  
Vol 6 (1) ◽  
pp. 1-26 ◽  
Author(s):  
C. Straub ◽  
P. J. Espy ◽  
R. E. Hibbins ◽  
D. A. Newnham
Keyword(s):  
Carbon Monoxide ◽  
Pressure Range ◽  
Microwave Radiometer ◽  
Correlation Coefficients ◽  
Data Set ◽  
British Antarctic Survey ◽  
Order Of Magnitude ◽  
High Bias ◽  
Co Concentrations

Abstract. This paper presents mesospheric carbon monoxide (CO) data acquired by the ground-based microwave radiometer of the British Antarctic Survey (BAS radiometer) stationed at Troll station in Antarctica (72° S, 2.5° E, 1270 a.m.s.l.). The data set covers the period from February 2008 to January 2010, however, due to very low CO concentrations below approximately 80 km altitude in summer, profiles can only be retrieved during Antarctic winter. CO is measured for approximately 2 h each day and profiles are retrieved approximately every half hour. The retrieved profiles, covering the pressure range from 1 to 0.01 hPa (approximately 48 to 80 km), are compared to measurements from Aura/MLS and SD-WACCM. This intercomparison reveals a low bias of 0.5 to 1 ppmv at 0.1 hPa (approximately 64 km) and 2.5 to 3.5 ppmv at 0.01 hPa (approximately 80 km) of the BAS microwave radiometer compared to both reference datasets. One explanation for this low bias could be the known high bias of MLS which is in the same order of magnitude. The ground based radiometer shows high and significant correlation (coefficients higher than 0.9/0.65 compared to MLS/SD-WACCM) at all altitudes compared with both reference datasets. doi:10.5285/DE3E2092-406D-47A9-9205-3971A8DFB4A9

scholarly journals Validation of merged MSU4 and AMSU9 temperature climate records with a new 2002–2012 vertically resolved temperature record

2015 ◽  
Vol 8 (1) ◽  
pp. 235-267 ◽  
Author(s):  
A. A. Penckwitt ◽  
G. E. Bodeker ◽  
P. Stoll ◽  
J. Lewis ◽  
T. von Clarmann ◽  
...  
Keyword(s):  
Time Series ◽  
Radio Occultation ◽  
Temperature Data ◽  
Data Sets ◽  
Data Set ◽  
Upper Troposphere ◽  
Microwave Sounding Unit ◽  
Source Data ◽  
Microwave Sounding ◽  
Temperature Time

Abstract. A new database of monthly mean zonal mean (5° zones) temperature time series spanning 17 pressure levels from 300 to 7 hPa and extending from 2002 to 2012 was created by merging monthly mean time series from two satellite-based mid-infrared spectrometers (ACE-FTS and MIPAS), a microwave sounder (SMR), and from three satellite-based radio occultation experiments (GRACE, CHAMP, and TSX). The primary intended use of this new temperature data set is to validate the merging of the Microwave Sounding Unit channel 4 (MSU4), and Advanced Microwave Sounding Unit channel 9 (AMSU9) temperature time series conducted in previous studies. The six source data sets were merged by removing offsets and trends between the different measurement series. Weighted means were calculated of the six source data sets where the weights were a function of the uncertainty on the original monthly mean data. This new temperature data set of the upper troposphere and stratosphere has been validated by comparing it to RATPAC-A, COSMIC radio occultation data as well as the NCEPCFSR reanalyses. Differences in all three cases were typically < 2 K in the upper troposphere and lower stratosphere, but could reach up to 5 K in the mid-stratosphere. The data across the 17 pressure levels have then been vertically integrated, using the MSU4/AMSU9 weighting function, to provide a deep vertical layer temperature proxy of the merged MSU4+AMSU9 series. Differences between this vertically integrated data set and two different versions of the MSU4+AMSU9 data set – one from Remote Sensing Systems and one from the University of Alabama at Huntsville – were examined for discontinuities. No statistically significant discontinuities were found in either of those two data sets suggesting that the transition from the MSU4+AMSU9 data to AMSU9 data only does not introduce any discontinuities in the MSU4+AMSU9 climate data records that might compromise their use in temperature trend analyses.

scholarly journals An edge-cloud collaboration architecture for pattern anomaly detection of time series in wireless sensor networks

2021 ◽  
Author(s):  
Cong Gao ◽  
Ping Yang ◽  
Yanping Chen ◽  
Zhongmin Wang ◽  
Yue Wang
Keyword(s):  
Time Series ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
Estimation Method ◽  
Feature Representation ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Data Sets ◽  
Edge Node

AbstractWith large deployment of wireless sensor networks, anomaly detection for sensor data is becoming increasingly important in various fields. As a vital data form of sensor data, time series has three main types of anomaly: point anomaly, pattern anomaly, and sequence anomaly. In production environments, the analysis of pattern anomaly is the most rewarding one. However, the traditional processing model cloud computing is crippled in front of large amount of widely distributed data. This paper presents an edge-cloud collaboration architecture for pattern anomaly detection of time series. A task migration algorithm is developed to alleviate the problem of backlogged detection tasks at edge node. Besides, the detection tasks related to long-term correlation and short-term correlation in time series are allocated to cloud and edge node, respectively. A multi-dimensional feature representation scheme is devised to conduct efficient dimension reduction. Two key components of the feature representation trend identification and feature point extraction are elaborated. Based on the result of feature representation, pattern anomaly detection is performed with an improved kernel density estimation method. Finally, extensive experiments are conducted with synthetic data sets and real-world data sets.

scholarly journals Loi and Gong Low-Degree Rotational Splittings

1998 ◽  
Vol 185 ◽  
pp. 167-168
Author(s):  
T. Appourchaux ◽  
M.C. Rabello-Soares ◽  
L. Gizon
Keyword(s):  
Time Series ◽  
The Other ◽  
Data Sets ◽  
Data Set ◽  
Low Degree ◽  
Fourier Spectra

Two different data sets have been used to derive low-degree rotational splittings. One data set comes from the Luminosity Oscillations Imager of VIRGO on board SOHO; the observation starts on 27 March 96 and ends on 26 March 97, and are made of intensity time series of 12 pixels (Appourchaux et al, 1997, Sol. Phys., 170, 27). The other data set was kindly made available by the GONG project; the observation starts on 26 August 1995 and ends on 21 August 1996, and are made of complex Fourier spectra of velocity time series for l = 0 − 9. For the GONG data, the contamination of l = 1 from the spatial aliases of l = 6 and l = 9 required some cleaning. To achieve this, we applied the inverse of the leakage matrix of l = 1, 6 and 9 to the original Fourier spectra of the same degrees; cleaning of all 3 degrees was achieved simultaneously (Appourchaux and Gizon, 1997, these proceedings).

scholarly journals An assessment of Bayesian bias estimator for numerical weather prediction

2008 ◽  
Vol 15 (6) ◽  
pp. 1013-1022 ◽  
Author(s):  
J. Son ◽  
D. Hou ◽  
Z. Toth
Keyword(s):  
Time Series ◽  
Numerical Weather Prediction ◽  
Sampling Error ◽  
Weather Prediction ◽  
Training Data ◽  
Statistical Characteristics ◽  
Forecast Errors ◽  
Data Sets ◽  
Data Set ◽  
Numerical Weather

Abstract. Various statistical methods are used to process operational Numerical Weather Prediction (NWP) products with the aim of reducing forecast errors and they often require sufficiently large training data sets. Generating such a hindcast data set for this purpose can be costly and a well designed algorithm should be able to reduce the required size of these data sets. This issue is investigated with the relatively simple case of bias correction, by comparing a Bayesian algorithm of bias estimation with the conventionally used empirical method. As available forecast data sets are not large enough for a comprehensive test, synthetically generated time series representing the analysis (truth) and forecast are used to increase the sample size. Since these synthetic time series retained the statistical characteristics of the observations and operational NWP model output, the results of this study can be extended to real observation and forecasts and this is confirmed by a preliminary test with real data. By using the climatological mean and standard deviation of the meteorological variable in consideration and the statistical relationship between the forecast and the analysis, the Bayesian bias estimator outperforms the empirical approach in terms of the accuracy of the estimated bias, and it can reduce the required size of the training sample by a factor of 3. This advantage of the Bayesian approach is due to the fact that it is less liable to the sampling error in consecutive sampling. These results suggest that a carefully designed statistical procedure may reduce the need for the costly generation of large hindcast datasets.

scholarly journals Results from the validation campaign of the ozone radiometer GROMOS-C at the NDACC station of La Réunion Island

2016 ◽  
Author(s):  
Susana Fernandez ◽  
Rolf Rüfenacht ◽  
Niklaus Kämpfer ◽  
Thierry Portafaix ◽  
Françoise Posny ◽  
...  
Keyword(s):  
Middle Atmosphere ◽  
Microwave Radiometer ◽  
Estimation Method ◽  
Emission Spectra ◽  
Optimal Estimation ◽  
Reunion Island ◽  
La Réunion ◽  
North East ◽  
Réunion Island ◽  
La Réunion Island

Abstract. Abstract. Ozone is a species of primary interest as it performs a key role in the middle atmosphere and its monitoring is thus necessary. At the Institute of Applied Physics of the University of Bern, Switzerland, we built a new ground based microwave radiometer, GROMOS-C (GRound based Ozone MOnitoring System for Campaigns). It has a compact design and can be operated at remote places with very little maintenance requirements, being therefore suitable for remote deployments. It has been conceived to measure the vertical distribution of ozone in the middle atmosphere, by observing pressure broadened emission spectra at a frequency of 110.836 GHz. In addition, meridional and zonal wind profiles can be retrieved, based on the Doppler shift of the ozone line measured in the 4 directions of observation (North-East-South-West). In June 2014 the radiometer was installed in the Maïdo observatory, on La Réunion Island (21.2° S, 55.5° E). High resolution ozone spectra were continuously recorded during 7 months. Vertical profiles of ozone have been retrieved through an optimal estimation inversion process, using the Atmospheric Radiative Transfer Simulator ARTS2 as the forward model. The best estimate of the vertical profile is done by means of the optimal estimation method. The validation is performed against ozone profiles from the Microwave Limb Sounder (MLS) on the Aura satellite, the ozone lidar located in the observatory and with ozone profiles from weekly radiosondes. Zonal and meridional winds retrieved from GROMOS-C data are validated against another wind radiometer located in situ, WIRA. In addition, we compare both ozone and winds with ECMWF model data. Results show that GROMOS-C provides reliable ozone profiles between 30 to 0.02 hPa. The comparison with lidar shows a very good agreement at all levels. The accordance with MLS is within less than 10 % for pressure levels between 25 and 0.2 hPa.

scholarly journals Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

2018 ◽  
Vol 18 (3) ◽  
pp. 1573-1592 ◽  
Author(s):  
Gerrit de Leeuw ◽  
Larisa Sogacheva ◽  
Edith Rodriguez ◽  
Konstantinos Kourtidis ◽  
Aristeidis K. Georgoulias ◽  
...  
Keyword(s):  
Time Series ◽  
European Space Agency ◽  
Mainland China ◽  
Satellite Observations ◽  
Data Sets ◽  
Data Set ◽  
Modis Aod ◽  
The Difference ◽  
Along Track ◽  
Aerosol Properties

Abstract. The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth – AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995–2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the Envisat period in 2012, showing decreasing AOD.

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