scholarly journals Relative drifts and stability of satellite and ground-based stratospheric ozone profiles at NDACC lidar stations

2012 ◽  
Vol 5 (1) ◽  
pp. 471-516
Author(s):  
P. J. Nair ◽  
S. Godin-Beekmann ◽  
L. Froidevaux ◽  
L. E. Flynn ◽  
J. M. Zawodny ◽  
...  
Keyword(s):  
Stratospheric Ozone ◽  
Measurement Techniques ◽  
Data Sets ◽  
Data Set ◽  
Meteorological Observatory ◽  
The Stability ◽  
Combined Time Series ◽  
Relative Differences ◽  
Term Data

Abstract. The long-term evolution of stratospheric ozone at different stations in the low and mid-latitudes is investigated. The analysis is performed by comparing the collocated profiles of ozone lidars, at the northern mid-latitudes (Meteorological Observatory Hohenpeißenberg, Haute-Provence Observatory, Tsukuba and Table Mountain Facility), tropics (Mauna Loa Observatory) and southern mid-latitudes (Lauder), with ozonesondes and space-borne sensors (SBUV(/2), SAGE II, HALOE, UARS MLS and Aura MLS), extracted around the stations. Relative differences are calculated to find biases and temporal drifts in the measurements. All measurement techniques show their best agreement with respect to the lidar at 20–40 km, where the differences are within ±3% and drifts are less than ±0.3% yr−1 at all stations. In addition, the stability of the long-term ozone observations (lidar, SBUV(/2), SAGE II and HALOE) is evaluated by the cross-comparison of each data set. In general, all lidars and SBUV(/2) exhibit near zero drifts and the comparison between SAGE II and HALOE shows larger, but insignificant drifts. The RMS of the drifts of lidar and SBUV(/2) is 0.22 and 0.27% yr−1, respectively. The average drifts of the long-term data sets, derived from various comparisons, are less than ±0.3% yr−1 in 20–40 km at all stations. A combined time series of the relative differences between SAGE II, HALOE and Aura MLS with respect to lidar data at six sites is constructed, to obtain long-term data sets lasting up to 27 yr. The relative drifts derived from these combined data are very small, within ±0.2% yr−1.

scholarly journals Relative drifts and stability of satellite and ground-based stratospheric ozone profiles at NDACC lidar stations

2012 ◽  
Vol 5 (6) ◽  
pp. 1301-1318 ◽  
Author(s):  
P. J. Nair ◽  
S. Godin-Beekmann ◽  
L. Froidevaux ◽  
L. E. Flynn ◽  
J. M. Zawodny ◽  
...  
Keyword(s):  
Stratospheric Ozone ◽  
Measurement Techniques ◽  
Data Sets ◽  
Data Set ◽  
Meteorological Observatory ◽  
The Stability ◽  
Combined Time Series ◽  
Relative Differences ◽  
Term Data

Abstract. The long-term evolution of stratospheric ozone at different stations in the low and mid-latitudes is investigated. The analysis is performed by comparing the collocated profiles of ozone lidars, at the northern mid-latitudes (Meteorological Observatory Hohenpeißenberg, Haute-Provence Observatory, Tsukuba and Table Mountain Facility), tropics (Mauna Loa Observatory) and southern mid-latitudes (Lauder), with ozonesondes and space-borne sensors (SBUV(/2), SAGE II, HALOE, UARS MLS and Aura MLS), extracted around the stations. Relative differences are calculated to find biases and temporal drifts in the measurements. All measurement techniques show their best agreement with respect to the lidar at 20–40 km, where the differences and drifts are generally within ±5% and ±0.5% yr−1, respectively, at most stations. In addition, the stability of the long-term ozone observations (lidar, SBUV(/2), SAGE II and HALOE) is evaluated by the cross-comparison of each data set. In general, all lidars and SBUV(/2) exhibit near-zero drifts and the comparison between SAGE II and HALOE shows larger, but insignificant drifts. The RMS of the drifts of lidar and SBUV(/2) is 0.22 and 0.27% yr−1, respectively at 20–40 km. The average drifts of the long-term data sets, derived from various comparisons, are less than ±0.3% yr−1 in the 20–40 km altitude at all stations. A combined time series of the relative differences between SAGE II, HALOE and Aura MLS with respect to lidar data at six sites is constructed, to obtain long-term data sets lasting up to 27 years. The relative drifts derived from these combined data are very small, within ±0.2% yr−1.

scholarly journals Past changes in the vertical distribution of ozone – Part 1: Measurement techniques, uncertainties and availability

2014 ◽  
Vol 7 (5) ◽  
pp. 1395-1427 ◽  
Author(s):  
B. Hassler ◽  
I. Petropavlovskikh ◽  
J. Staehelin ◽  
T. August ◽  
P. K. Bhartia ◽  
...  
Keyword(s):  
Stratospheric Ozone ◽  
Measurement Techniques ◽  
United Nations Environment Programme ◽  
Critical Examination ◽  
Profile Measurement ◽  
Data Sets ◽  
Data Set ◽  
Ozone Profile ◽  
Measurement Uncertainties

Abstract. Peak stratospheric chlorofluorocarbon (CFC) and other ozone depleting substance (ODS) concentrations were reached in the mid- to late 1990s. Detection and attribution of the expected recovery of the stratospheric ozone layer in an atmosphere with reduced ODSs as well as efforts to understand the evolution of stratospheric ozone in the presence of increasing greenhouse gases are key current research topics. These require a critical examination of the ozone changes with an accurate knowledge of the spatial (geographical and vertical) and temporal ozone response. For such an examination, it is vital that the quality of the measurements used be as high as possible and measurement uncertainties well quantified. In preparation for the 2014 United Nations Environment Programme (UNEP)/World Meteorological Organization (WMO) Scientific Assessment of Ozone Depletion, the SPARC/IO3C/IGACO-O3/NDACC (SI2N) Initiative was designed to study and document changes in the global ozone profile distribution. This requires assessing long-term ozone profile data sets in regards to measurement stability and uncertainty characteristics. The ultimate goal is to establish suitability for estimating long-term ozone trends to contribute to ozone recovery studies. Some of the data sets have been improved as part of this initiative with updated versions now available. This summary presents an overview of stratospheric ozone profile measurement data sets (ground and satellite based) available for ozone recovery studies. Here we document measurement techniques, spatial and temporal coverage, vertical resolution, native units and measurement uncertainties. In addition, the latest data versions are briefly described (including data version updates as well as detailing multiple retrievals when available for a given satellite instrument). Archive location information for each data set is also given.

scholarly journals SI<sup>2</sup>N overview paper: ozone profile measurements: techniques, uncertainties and availability

2013 ◽  
Vol 6 (6) ◽  
pp. 9857-9938 ◽  
Author(s):  
B. Hassler ◽  
I. Petropavlovskikh ◽  
J. Staehelin ◽  
T. August ◽  
P. K. Bhartia ◽  
...  
Keyword(s):  
Stratospheric Ozone ◽  
Measurement Techniques ◽  
United Nations Environment Programme ◽  
Critical Examination ◽  
Profile Measurement ◽  
Data Sets ◽  
Data Set ◽  
Ozone Profile ◽  
Measurement Uncertainties

Abstract. Peak stratospheric chlorofluorocarbon (CFC) and other ozone depleting substance (ODS) concentrations were reached in the mid to late 1990s. Detection and attribution of the expected recovery of the stratospheric ozone layer in an atmosphere with reduced ODSs as well as efforts to understand the evolution of stratospheric ozone in the presence of increasing greenhouse gases are key current research topics. These require a critical examination of the ozone changes with an accurate knowledge of the spatial (geographical and vertical) and temporal ozone response. For such an examination, it is vital that the quality of the measurements used be as high as possible and measurement uncertainties well quantified. In preparation for the 2014 United Nations Environment Programme (UNEP)/World Meteorological Organization (WMO) Scientific Assessment of Ozone Depletion, the SPARC/IO3C/IGACO-O3/NDACC (SI2N) initiative was designed to study and document changes in the global ozone profile distribution. This requires assessing long-term ozone profile data sets in regards to measurement stability and uncertainty characteristics. The ultimate goal is to establish suitability for estimating long-term ozone trends to contribute to ozone recovery studies. Some of the data sets have been improved as part of this initiative with updated versions now available. This summary presents an overview of stratospheric ozone profile measurement data sets (ground- and satellite-based) available for ozone recovery studies. Here we document measurement techniques, spatial and temporal coverage, vertical resolution, native units and measurement uncertainties. In addition, the latest data versions are briefly described (including data version updates as well as detailing multiple retrievals when available for a given satellite instrument). Archive location information is for each data set is also given.

Trophic Level Relationships in Pelagic Food Webs: Comparisons Derived from Long-Term Data Sets for Oneida Lake, New York (USA), and Lake St. George, Ontario (Canada)

1992 ◽  
Vol 49 (8) ◽  
pp. 1588-1596 ◽  
Author(s):  
Donald J. McQueen ◽  
Edward L. Mills ◽  
John L. Forney ◽  
Mark R. S. Johannes ◽  
John R. Post
Keyword(s):  
New York ◽  
Total Phosphorus ◽  
Trophic Level ◽  
Data Sets ◽  
Phytoplankton Abundance ◽  
Data Set ◽  
Oneida Lake ◽  
Pelagic Food Webs ◽  
Term Data

We used standardized methods to analyze a 14-yr data set from Oneida Lake and a 10-yr data set from Lake St. George. We estimated mean summer concentrations of several trophic level indicators including piscivores, planktivores, zooplankton, phytoplankton, and total phosphorus, and we then investigated the relationships between these variables. Both data sets yielded similar long-term and short-term trends. The long-term mean annual trends were that (1) the relationships between concentrations of planktivores and zooplankton (including daphnids) were always negative, (2) the relationships between concentrations of zooplankton and various measures of phytoplankton abundance were unpredictable and never statistically significant, and (3) the relationships between total phosphorus and various measures of phytoplankton abundance were always positive. Over short periods, the data from both lakes showed periodic, strong top-down relationships between concentrations of zooplankton (especially large Daphnia) and chlorophyll a, but these events were unpredictable and were seldom related to piscivore abundance.

scholarly journals ML-TOMCAT: machine-learning-based satellite-corrected global stratospheric ozone profile data set from a chemical transport model

2021 ◽  
Vol 13 (12) ◽  
pp. 5711-5729
Author(s):  
Sandip S. Dhomse ◽  
Carlo Arosio ◽  
Wuhu Feng ◽  
Alexei Rozanov ◽  
Mark Weber ◽  
...  
Keyword(s):  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Profile Data ◽  
Data Set ◽  
Ozone Profile ◽  
Satellite Instruments

Abstract. High-quality stratospheric ozone profile data sets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments provide stratospheric ozone profile measurements over typical mission durations of 5–15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create long-term observation-based ozone profile data sets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different data sets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a random-forest (RF) ensemble learning method to create a merged 42-year (1979–2020) stratospheric ozone profile data set (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gases, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991–1998) and Aura (2005–2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based data sets which use pressure as a vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the data sets which are altitude-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties of the observational data sets. The ML-TOMCAT (V1.0) data set is ideally suited for the evaluation of chemical model ozone profiles from the tropopause to 0.1 hPa and is freely available via https://doi.org/10.5281/zenodo.5651194 (Dhomse et al., 2021).

scholarly journals How long do satellites need to overlap? Evaluation of climate data stability from overlapping satellite records

2017 ◽  
Vol 17 (24) ◽  
pp. 15069-15093 ◽  
Author(s):  
Elizabeth C. Weatherhead ◽  
Jerald Harder ◽  
Eduardo A. Araujo-Pradere ◽  
Greg Bodeker ◽  
Jason M. English ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Spectral Irradiance ◽  
Data Sets ◽  
Climate Data ◽  
Data Set ◽  
Long Term Stability ◽  
Earth Observations ◽  
Earth’S Climate ◽  
The Stability

Abstract. Sensors on satellites provide unprecedented understanding of the Earth's climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, long-term, stable records of the parameters they measure. Ground-based intercomparisons offer some insight, while reference observations and internal calibrations give further assistance for understanding long-term stability. A valuable tool for evaluating and developing long-term records from satellites is the examination of data from overlapping satellite missions. This paper addresses how the length of overlap affects the ability to identify an offset or a drift in the overlap of data between two sensors. Ozone and temperature data sets are used as examples showing that overlap data can differ by latitude and can change over time. New results are presented for the general case of sensor overlap by using Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) solar irradiance data as an example. To achieve a 1 % uncertainty in estimating the offset for these two instruments' measurement of the Mg II core (280 nm) requires approximately 5 months of overlap. For relative drift to be identified within 0.1 % yr−1 uncertainty (0.00008 W m−2 nm−1 yr−1), the overlap for these two satellites would need to be 2.5 years. Additional overlap of satellite measurements is needed if, as is the case for solar monitoring, unexpected jumps occur adding uncertainty to both offsets and drifts; the additional length of time needed to account for a single jump in the overlap data may be as large as 50 % of the original overlap period in order to achieve the same desired confidence in the stability of the merged data set. Results presented here are directly applicable to satellite Earth observations. Approaches for Earth observations offer additional challenges due to the complexity of the observations, but Earth observations may also benefit from ancillary observations taken from ground-based and in situ sources. Difficult choices need to be made when monitoring approaches are considered; we outline some attempts at optimizing networks based on economic principles. The careful evaluation of monitoring overlap is important to the appropriate application of observational resources and to the usefulness of current and future observations.

scholarly journals Assessment of Odin-OSIRIS ozone measurements from 2001 to the present using MLS, GOMOS, and ozone sondes

2013 ◽  
Vol 6 (2) ◽  
pp. 3819-3857 ◽  
Author(s):  
C. Adams ◽  
A. E. Bourassa ◽  
V. Sofieva ◽  
L. Froidevaux ◽  
C. A. McLinden ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Imaging System ◽  
Data Sets ◽  
Validation Data ◽  
Data Set ◽  
Long Term Stability ◽  
Ozone Data ◽  
High Bias ◽  
The Stability

Abstract. The Optical Spectrograph and InfraRed Imaging System (OSIRIS) was launched aboard the Odin satellite in 2001 and is continuing to take limb-scattered sunlight measurements of the atmosphere. This work aims to characterize and assess the stability of the OSIRIS 11 yr v5.0x ozone data set. Three validation data sets were used: the v2.2 Microwave Limb Sounder (MLS) and v6 Global Ozone Monitoring of Occultation on Stars (GOMOS) satellite data records, and ozone sonde measurements. Global mean percent differences between coincident OSIRIS and validation measurements are within 5% of zero at all altitude layers above 18.5 km for MLS, above 21.5 km for GOMOS, and above 17.5 km for ozone sondes. Below 17.5 km, OSIRIS measurements agree with ozone sondes within 5% and are well-correlated (R > 0.75) with them. For low OSIRIS optics temperatures (< 16 °C), OSIRIS ozone measurements are biased low by up 6% compared with the validation data sets for 25.5–40.5 km. Biases between OSIRIS ascending and descending node measurements were investigated and were found to be related to aerosol retrievals below 27.5 km. Above 30 km, agreement between OSIRIS and the validation data sets was related to the OSIRIS retrieved albedo, which measures apparent upwelling, with a high bias for in OSIRIS data with large albedos. In order to assess the long-term stability of OSIRIS measurements, global average drifts relative to the validation data sets were calculated and were found to be < 3% per decade for comparisons against MLS for 19.5–36.5 km, GOMOS for 18.5–54.5 km, and ozone sondes for 12.5–22.5 km, and within error of 3% per decade at most altitudes. Above 36.5 km, the relative drift for OSIRIS versus MLS ranged from ~ 0–6%, depending on the data set used to convert MLS data to the OSIRIS altitude versus number density grid. Overall, this work demonstrates that the OSIRIS 11 yr ozone data set from 2001 to the present is suitable for trend studies.

scholarly journals Interlaboratory comparison of <i>δ</i><sup>13</sup>C and <i>δ</i>D measurements of atmospheric CH<sub>4</sub> for combined use of data sets from different laboratories

2018 ◽  
Vol 11 (2) ◽  
pp. 1207-1231 ◽  
Author(s):  
Taku Umezawa ◽  
Carl A. M. Brenninkmeijer ◽  
Thomas Röckmann ◽  
Carina van der Veen ◽  
Stanley C. Tyler ◽  
...  
Keyword(s):  
Interlaboratory Comparison ◽  
Data Sets ◽  
Data Set ◽  
Use Of Data ◽  
Combined Use ◽  
Modelling Studies ◽  
Hydrogen Isotope Ratios ◽  
Term Data ◽  
Carbon And Hydrogen Isotope

Abstract. We report results from a worldwide interlaboratory comparison of samples among laboratories that measure (or measured) stable carbon and hydrogen isotope ratios of atmospheric CH4 (δ13C-CH4 and δD-CH4). The offsets among the laboratories are larger than the measurement reproducibility of individual laboratories. To disentangle plausible measurement offsets, we evaluated and critically assessed a large number of intercomparison results, some of which have been documented previously in the literature. The results indicate significant offsets of δ13C-CH4 and δD-CH4 measurements among data sets reported from different laboratories; the differences among laboratories at modern atmospheric CH4 level spread over ranges of 0.5 ‰ for δ13C-CH4 and 13 ‰ for δD-CH4. The intercomparison results summarized in this study may be of help in future attempts to harmonize δ13C-CH4 and δD-CH4 data sets from different laboratories in order to jointly incorporate them into modelling studies. However, establishing a merged data set, which includes δ13C-CH4 and δD-CH4 data from multiple laboratories with desirable compatibility, is still challenging due to differences among laboratories in instrument settings, correction methods, traceability to reference materials and long-term data management. Further efforts are needed to identify causes of the interlaboratory measurement offsets and to decrease those to move towards the best use of available δ13C-CH4 and δD-CH4 data sets.

scholarly journals Construction of intensity-duration-frequency (IDF) curves for precipitation with annual maxima data in Rwanda, Central Africa

2013 ◽  
Vol 35 ◽  
pp. 1-5 ◽  
Author(s):  
G. R. Demarée ◽  
H. Van de Vyver
Keyword(s):  
Central Africa ◽  
Fixed Time ◽  
Data Sets ◽  
Time Intervals ◽  
Data Set ◽  
Probabilistic Information ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Term Data

Abstract. Detailed probabilistic information on the intensity of precipitation in Central Africa is highly needed in order to cope with the risk analysis of natural hazards. In the mountainous areas of Rwanda land slides frequently occur and might cause a heavy toll in human lives. The establishment of Intensity-Duration-Frequency curves for precipitation in Central Africa remains a difficult task as adequate long-term data sets for short aggregation times are usually not available. In 1962 recording raingauges were installed at several stations in Rwanda. According to the climatological procedures in use at that time in Congo, Rwanda and Burundi, maximum monthly and annual precipitation depths for fixed-time durations of 15, 30, 45, 60 and 120 min were determined from the rainfall charts. The data set is completed by the monthly and annual daily precipitation extremes from the non-recording raingauge at the stations. The authors used the dataset to establish the IDF-curves for precipitation at 3 stations in Rwanda having more than 20 yr of operation. The fixed-hour intervals of multiple 15 min require the use of a technique converting data from fixed-time intervals into data of arbitrary starting intervals. Therefore, the van Montfort technique was used.

scholarly journals Assessment of Odin-OSIRIS ozone measurements from 2001 to the present using MLS, GOMOS, and ozonesondes

2014 ◽  
Vol 7 (1) ◽  
pp. 49-64 ◽  
Author(s):  
C. Adams ◽  
A. E. Bourassa ◽  
V. Sofieva ◽  
L. Froidevaux ◽  
C. A. McLinden ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Imaging System ◽  
Data Sets ◽  
Validation Data ◽  
Data Set ◽  
Long Term Stability ◽  
Ozone Data ◽  
The Stability ◽  
Global Mean

Abstract. The Optical Spectrograph and InfraRed Imaging System (OSIRIS) was launched aboard the Odin satellite in 2001 and is continuing to take limb-scattered sunlight measurements of the atmosphere. This work aims to characterize and assess the stability of the OSIRIS 11 yr v5.0x ozone data set. Three validation data sets were used: the v2.2 Microwave Limb Sounder (MLS) and v6 Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite data records, and ozonesonde measurements. Global mean percent differences between coincident OSIRIS and validation measurements are within 5% at all altitudes above 18.5 km for MLS, above 21.5 km for GOMOS, and above 17.5 km for ozonesondes. Below 17.5 km, OSIRIS measurements agree with ozonesondes within 5% and are well-correlated (R > 0.75) with them. For low OSIRIS optics temperatures (< 16 °C), OSIRIS ozone measurements have a negative bias of 1–6% compared with the validation data sets for 25.5–40.5 km. Biases between OSIRIS ascending and descending node measurements were investigated and found to be related to aerosol retrievals below 27.5 km. Above 30 km, agreement between OSIRIS and the validation data sets was related to the OSIRIS retrieved albedo, which measures apparent upwelling, with a positive bias in OSIRIS data with large albedos. In order to assess the long-term stability of OSIRIS measurements, global average drifts relative to the validation data sets were calculated and were found to be < 3% per decade for comparisons with MLS for 19.5–36.5 km, GOMOS for 18.5–54.5 km, and ozonesondes for 12.5–22.5 km. Above 36.5 km, the relative drift for OSIRIS versus MLS ranged from ~ 0 to 6% per decade, depending on the data set used to convert MLS data to the OSIRIS altitude versus number density grid. Overall, this work demonstrates that the OSIRIS 11 yr ozone data set from 2001 to the present is suitable for trend studies.

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