scholarly journals Evaluation of CESM1 (WACCM) free-running and specified-dynamics atmospheric composition simulations using global multi-species satellite data records

2018 ◽  
Author(s):  
Lucien Froidevaux ◽  
Douglas E. Kinnison ◽  
Ray Wang ◽  
John Anderson ◽  
Ryan A. Fuller
Keyword(s):  
Time Series ◽  
Lower Stratosphere ◽  
Climate Model ◽  
Statistical Significance ◽  
Atmospheric Composition ◽  
Tropical Region ◽  
Model Data ◽  
Data Set ◽  
Rate Of Increase ◽  
Free Running

Abstract. We evaluate the recently delivered Community Earth System Model version 1 (CESM1) Whole Atmosphere Community Climate Model (WACCM) using satellite-derived global composition datasets, focusing on the stratosphere. The simulations include free-running (FR-WACCM) and specified-dynamics (SD-WACCM) versions of the model. Model evaluations are made using global monthly zonal mean time series obtained by the Aura Microwave Limb Sounder (MLS), as well as longer-term global data records compiled by the Global Ozone Chemistry and Related Trace gas Data Records for the Stratosphere (GOZCARDS) project. A recent update (version 2.20) to the original GOZCARDS merged ozone (O3) data set is used. We discuss upper atmospheric climatology and zonal mean variability using O3, hydrogen chloride (HCl), nitrous oxide (N2O), nitric acid (HNO3), and water vapor (H2O) data. There are a few significant model/data mean biases, such as for lower stratospheric O3, for which the models overestimate the mean observed values and seasonal amplitudes. Another clear difference occurs for HNO3 during recurring winter periods of strong HNO3 enhancements at high latitudes; this stems from the known omission of ion chemistry relating to particle precipitation effects, in the global models used here. In the lower stratosphere at high southern latitudes, the variations in polar winter/spring composition observed by MLS are generally well matched by SD-WACCM, the main exception being for the early winter rate of decrease in HCl, which is too slow in the model. In general, the latitude/pressure distributions of annual and semi-annual oscillation amplitudes derived from the MLS data are properly captured by the corresponding model values. Nevertheless, detailed aspects of the interactions between the quasi-biennial, annual, and semi-annual ozone variations in the upper stratosphere are not as well represented by FR-WACCM as by SD-WACCM. One of the evaluation diagnostics we use represents the closeness of fit between the model/data anomaly time series, and we also consider the correlation coefficients. Not surprisingly, SD-WACCM, which is driven by realistic dynamics, generally matches observed deseasonalized anomalies better than FR-WACCM does. Other results indicate that the root mean square variability is sometimes found to be significantly smaller in FR-WACCM than in SD-WACCM and the observations. Most notably, FR-WACCM underestimates the observed interannual variability for H2O by ~ 30 %, typically, and by as much as a factor of two in some regions; this has some implications for the time needed to detect small trends. We have derived trends using a multivariate linear regression (MLR) model, and there is a robust signal in both MLS observations and WACCM of an upper stratospheric O3 increase from 2005 to 2014 by ~ 0.2–0.4 %/yr (±0.2 %/yr, 2σ), depending on which broad latitude bin (tropics or mid-latitudes) is considered. In the lower stratosphere, while some decreases are indicated for 1998–2014 (based on merged GOZCARDS O3), we find near-zero or positive trends when using MLS O3 data alone for 2005–2014, albeit with no robust statistical significance. SD-WACCM results track such positive tendencies (albeit with no statistical significance). For H2O, the most statistically significant trend result for 2005–2014 is an upper stratospheric increase, peaking at slightly more than 0.5 %/yr in the lower mesosphere, in fairly close agreement with SD-WACCM trends, but with smaller values in FR-WACCM. For HCl, while the lower stratospheric vertical gradients of MLS trends are duplicated to some extent by SD-WACCM, the model trends (decreases) are always on the low side of the data trends. There is little model-based indication (in SD-WACCM) of a significantly positive HCl trend derived from the MLS tropical series at 68 hPa; this deserves further study. For N2O, the MLS-derived trends (for 2005–2012) point to negative trends (of up to about −1 %/yr) in the NH mid-latitudes and positive trends (of up to about +3 %/yr) in the SH mid-latitudes, in good agreement with the asymmetry that exists in SD-WACCM trend results. The small observed positive N2O trends of ~ 0.2 %/yr in the 100 to 30 hPa tropical region are also consistent with model results (SD-WACCM in particular), which in turn are very close to the known rate of increase in tropospheric N2O. In the case of HNO3, MLS-derived lower stratospheric trend differences (for 2005–2014) between hemispheres are opposite in sign to those from N2O and in reasonable agreement with both WACCM results, despite large error bars. The data sets and tools discussed here for the evaluation of the models could be expanded to additional comparisons of species not included here, as well as to model intercomparisons using a variety of CCMs, keeping in mind that there are different parameterizations and approaches for both free-running and specified-dynamics simulations.

scholarly journals Interpol-IAGOS: a new method for assessing long-term chemistry–climate simulations in the UTLS based on IAGOS data, and its application to the MOCAGE CCMI REF-C1SD simulation

2021 ◽  
Vol 14 (5) ◽  
pp. 2659-2689
Author(s):  
Yann Cohen ◽  
Virginie Marécal ◽  
Béatrice Josse ◽  
Valérie Thouret
Keyword(s):  
Climate Models ◽  
Lower Stratosphere ◽  
Climate Model ◽  
Weighting Function ◽  
Observation Data ◽  
Model Data ◽  
Data Set ◽  
Upper Troposphere ◽  
Airborne Measurements

Abstract. A wide variety of observation data sets are used to assess long-term simulations provided by chemistry–climate models (CCMs) and chemistry-transport models (CTMs). However, the upper troposphere–lower stratosphere (UTLS) has hardly been assessed in these modelling exercises yet. Observations performed in the framework of IAGOS (In-service Aircraft for a Global Observing System) combine the advantages of in situ airborne measurements in the UTLS with an almost-global-scale sampling, a ∼20-year monitoring period and a high frequency. Even though a few model assessments have been made using the IAGOS database, none of them took advantage of the dense and high-resolution cruise data in their whole ensemble yet. The present study proposes a method to compare this large IAGOS data set to long-term simulations used for chemistry–climate studies. As a first application, the REF-C1SD reference simulation generated by the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) CTM in the framework of Chemistry-Climate Model Initiative (CCMI) phase I has been evaluated during the 1994–2013 period for ozone (O3) and the 2002–2013 period for carbon monoxide (CO). The concept of the new comparison software proposed here (so-called Interpol-IAGOS) is to project all IAGOS data onto the 3-D grid of the model with a monthly resolution, since generally the 3-D outputs provided by chemistry–climate models for multi-model comparisons on multi-decadal timescales are archived as monthly means. This provides a new IAGOS data set (IAGOS-DM) mapped onto the model's grid and time resolution. To get a model data set consistent with IAGOS-DM for the comparison, a subset of the model's outputs is created (MOCAGE-M) by applying a mask that retains only the model data at the available IAGOS-DM grid points. Climatologies are derived from the IAGOS-DM product, and good correlations are reported between with the MOCAGE-M spatial distributions. As an attempt to analyse MOCAGE-M behaviour in the upper troposphere (UT) and the lower stratosphere (LS) separately, UT and LS data in IAGOS-DM were sorted according to potential vorticity. From this, we derived O3 and CO seasonal cycles in eight regions well sampled by IAGOS flights in the northern midlatitudes. They are remarkably well reproduced by the model for lower-stratospheric O3 and also good for upper-tropospheric CO. Along this model evaluation, we also assess the differences caused by the use of a weighting function in the method when projecting the IAGOS data onto the model grid compared to the scores derived in a simplified way. We conclude that the data projection onto the model's grid allows us to filter out biases arising from either spatial or temporal resolution, and the use of a weighting function yields different results, here by enhancing the assessment scores. Beyond the MOCAGE REF-C1SD evaluation presented in this paper, the method could be used by CCMI models for individual assessments in the UTLS and for model intercomparisons with respect to the IAGOS data set.

scholarly journals The Diurnal Variation in Stratospheric Ozone from MACC Reanalysis, ERA-Interim, WACCM, and Earth Observation Data: Characteristics and Intercomparison

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 625
Author(s):  
Ansgar Schanz ◽  
Klemens Hocke ◽  
Niklaus Kämpfer ◽  
Simon Chabrillat ◽  
Antje Inness ◽  
...  
Keyword(s):  
Diurnal Variation ◽  
Climate Model ◽  
Stratospheric Ozone ◽  
Polar Vortex ◽  
Model Systems ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Observation Data ◽  
High Latitudes ◽  
Free Running

In this study, we compare the diurnal variation in stratospheric ozone of the MACC (Monitoring Atmospheric Composition and Climate) reanalysis, ECMWF Reanalysis Interim (ERA-Interim), and the free-running WACCM (Whole Atmosphere Community Climate Model). The diurnal variation of stratospheric ozone results from photochemical and dynamical processes depending on altitude, latitude, and season. MACC reanalysis and WACCM use similar chemistry modules and calculate a similar diurnal cycle in ozone when it is caused by a photochemical variation. The results of the two model systems are confirmed by observations of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) experiment and three selected sites of the Network for Detection of Atmospheric Composition Change (NDACC) at Mauna Loa, Hawaii (tropics), Bern, Switzerland (midlatitudes), and Ny-Ålesund, Svalbard (high latitudes). On the other hand, the ozone product of ERA-Interim shows considerably less diurnal variation due to photochemical variations. The global maxima of diurnal variation occur at high latitudes in summer, e.g., near the Arctic NDACC site at Ny-Ålesund, Svalbard. The local OZORAM radiometer observes this effect in good agreement with MACC reanalysis and WACCM. The sensed diurnal variation at Ny-Ålesund is up to 8% (0.4 ppmv) due to photochemical variations in summer and negligible during the dynamically dominated winter. However, when dynamics play a major role for the diurnal ozone variation as in the lower stratosphere (100–20 hPa), the reanalysis models ERA-Interim and MACC which assimilate data from radiosondes and satellites outperform the free-running WACCM. Such a domain is the Antarctic polar winter where a surprising novel feature of diurnal variation is indicated by MACC reanalysis and ERA-Interim at the edge of the polar vortex. This effect accounts for up to 8% (0.4 ppmv) in both model systems. In summary, MACC reanalysis provides a global description of the diurnal variation of stratospheric ozone caused by dynamics and photochemical variations. This is of high interest for ozone trend analysis and other research which is based on merged satellite data or measurements at different local time.

scholarly journals Chemistry-climate model simulations of the Mt. Pinatubo eruption using CCMI and CMIP6 stratospheric aerosol data

2017 ◽  
Author(s):  
Laura Revell ◽  
Andrea Stenke ◽  
Beiping Luo ◽  
Stefanie Kremser ◽  
Eugene Rozanov ◽  
...  
Keyword(s):  
Lower Stratosphere ◽  
Climate Model ◽  
Stratospheric Aerosol ◽  
Radiative Properties ◽  
Gap Filling ◽  
Data Set ◽  
Model Simulations ◽  
Ozone Loss ◽  
Pinatubo Eruption ◽  
Climate Model Simulations

Abstract. To simulate the impacts of volcanic eruptions on the stratosphere, chemistry-climate models that do not include an online aerosol module require temporally and spatially resolved aerosol size parameters for heterogeneous chemistry and aerosol radiative properties as a function of wavelength. For phase 1 of the Chemistry-Climate Model Initiative (CCMI-1) and, later, for phase 6 of the Coupled Model Intercomparison Project (CMIP6) two such stratospheric aerosol data sets were compiled, whose functional capability and representativeness are compared here. For CCMI-1, the SAGE-4λ data set was compiled, which hinges on the measurements at four wavelengths of the SAGE (Stratospheric Aerosol and Gas Experiment) II satellite instrument and uses ground-based Lidar measurements for gap-filling immediately after the Mt. Pinatubo eruption, when the stratosphere was optically opaque for SAGE II. For CMIP6, the new SAGE-3λ data set was compiled, which excludes the least reliable SAGE II wavelength and uses CLAES (Cryogenic Limb Array Etalon Spectrometer) measurements on UARS, the Upper Atmosphere Research Satellite, for gap-filling following the Mt. Pinatubo eruption instead of ground-based Lidars. Here, we performed SOCOLv3 (Solar Climate Ozone Links version 3) chemistry-climate model simulations of the recent past (1986–2005) to investigate the impact of the Mt. Pinatubo eruption in 1991 on stratospheric temperature and ozone and how this response differs depending on which aerosol data set is applied. The use of SAGE-4λ results in heating and ozone loss being overestimated in the lower stratosphere compared to observations in the post-eruption period by approximately 3 K and 0.2 ppmv, respectively. However, less heating occurs in the model simulations based on SAGE-3λ, because the improved gap-filling procedures after the eruption lead to less aerosol loading in the tropical lower stratosphere. As a result, simulated temperature anomalies in the model simulations based on SAGE-3λ for CMIP6 are in excellent agreement with MERRA and ERA-Interim reanalyses in the post-eruption period. Less heating in the simulations with SAGE-3λ means that the rate of tropical upwelling does not strengthen as much as it does in the simulations with SAGE-4λ, which limits dynamical uplift of ozone and therefore provides more time for ozone to accumulate in tropical mid-stratospheric air. Ozone loss following the Mt. Pinatubo eruption is overestimated by 0.1 ppmv in the model simulations based on SAGE-3λ, which is a better agreement with observations than in the simulations based on SAGE-4λ. Overall, the CMIP6 stratospheric aerosol data set, SAGE-3λ, allows SOCOLv3 to more accurately simulate the post-Pinatubo eruption period.

scholarly journals Construction of merged satellite total O<sub>3</sub> and NO<sub>2</sub> time series in the tropics for trend studies and evaluation by comparison to NDACC SAOZ measurements

2014 ◽  
Vol 7 (10) ◽  
pp. 3337-3354 ◽  
Author(s):  
M. Pastel ◽  
J.-P. Pommereau ◽  
F. Goutail ◽  
A. Richter ◽  
A. Pazmiño ◽  
...  
Keyword(s):  
Time Series ◽  
Lower Stratosphere ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Composition Change ◽  
Long Time ◽  
Uv Visible ◽  
The Tropics ◽  
Lower Noise ◽  
Total Column

Abstract. Long time series of ozone and NO2 total column measurements in the southern tropics are available from two ground-based SAOZ (Système d'Analyse par Observation Zénithale) UV-visible spectrometers operated within the Network for the Detection of Atmospheric Composition Change (NDACC) in Bauru (22° S, 49° W) in S-E Brazil since 1995 and Reunion Island (21° S, 55° E) in the S-W Indian Ocean since 1993. Although the stations are located at the same latitude, significant differences are observed in the columns of both species, attributed to differences in tropospheric content and equivalent latitude in the lower stratosphere. These data are used to identify which satellites operating during the same period, are capturing the same features and are thus best suited for building reliable merged time series for trend studies. For ozone, the satellites series best matching SAOZ observations are EP-TOMS (1995–2004) and OMI-TOMS (2005–2011), whereas for NO2, best results are obtained by combining GOME version GDP5 (1996–2003) and SCIAMACHY – IUP (2003–2011), displaying lower noise and seasonality in reference to SAOZ. Both merged data sets are fully consistent with the larger columns of the two species above South America and the seasonality of the differences between the two stations, reported by SAOZ, providing reliable time series for further trend analyses and identification of sources of interannual variability in the future analysis.

scholarly journals Description and Evaluation of the specified-dynamics experiment in the Chemistry-Climate Model Initiative

2020 ◽  
Vol 20 (6) ◽  
pp. 3809-3840 ◽  
Author(s):  
Clara Orbe ◽  
David A. Plummer ◽  
Darryn W. Waugh ◽  
Huang Yang ◽  
Patrick Jöckel ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
General Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Phase 1 ◽  
General Circulation Models ◽  
Atmospheric Composition ◽  
Cycle Amplitude ◽  
Free Running ◽  
Dynamics Simulations

Abstract. We provide an overview of the REF-C1SD specified-dynamics experiment that was conducted as part of phase 1 of the Chemistry-Climate Model Initiative (CCMI). The REF-C1SD experiment, which consisted of mainly nudged general circulation models (GCMs) constrained with (re)analysis fields, was designed to examine the influence of the large-scale circulation on past trends in atmospheric composition. The REF-C1SD simulations were produced across various model frameworks and are evaluated in terms of how well they represent different measures of the dynamical and transport circulations. In the troposphere there are large (∼40 %) differences in the climatological mean distributions, seasonal cycle amplitude, and trends of the meridional and vertical winds. In the stratosphere there are similarly large (∼50 %) differences in the magnitude, trends and seasonal cycle amplitude of the transformed Eulerian mean circulation and among various chemical and idealized tracers. At the same time, interannual variations in nearly all quantities are very well represented, compared to the underlying reanalyses. We show that the differences in magnitude, trends and seasonal cycle are not related to the use of different reanalysis products; rather, we show they are associated with how the simulations were implemented, by which we refer both to how the large-scale flow was prescribed and to biases in the underlying free-running models. In most cases these differences are shown to be as large or even larger than the differences exhibited by free-running simulations produced using the exact same models, which are also shown to be more dynamically consistent. Overall, our results suggest that care must be taken when using specified-dynamics simulations to examine the influence of large-scale dynamics on composition.

Uncertainty of Climatol adjustment algorithm for daily time series of additive climate variables

2020 ◽  
Author(s):  
Oleg Skrynyk ◽  
Enric Aguilar ◽  
José A. Guijarro ◽  
Sergiy Bubin
Keyword(s):  
Time Series ◽  
Climate Model ◽  
Data Sets ◽  
Climate Variables ◽  
The European Union ◽  
Data Set ◽  
Raw Data ◽  
Climate Signal ◽  
Daily Time Series ◽  
Daily Time

&lt;p&gt;Before using climatological time series in research studies, it is necessary to perform their quality control and homogenization in order to remove possible artefacts (inhomogeneities) usually present in the raw data sets. In the vast majority of cases, the homogenization procedure allows to improve the consistency of the data, which then can be verified by means of the statistical comparison of the raw and homogenized time series. However, a new question then arises: how far are the homogenized data from the true climate signal or, in other words, what errors could still be present in homogenized data?&lt;/p&gt;&lt;p&gt;The main objective of our work is to estimate the uncertainty produced by the adjustment algorithm of the widely used Climatol homogenization software when homogenizing daily time series of the additive climate variables. We focused our efforts on the minimum and maximum air temperature. In order to achieve our goal we used a benchmark data set created by the INDECIS&lt;sup&gt;*&lt;/sup&gt; project. The benchmark contains clean data, extracted from an output of the Royal Netherlands Meteorological Institute Regional Atmospheric Climate Model (version 2) driven by Hadley Global Environment Model 2 - Earth System, and inhomogeneous data, created by introducing realistic breaks and errors.&lt;/p&gt;&lt;p&gt;The statistical evaluation of discrepancies between the homogenized (by means of Climatol with predefined break points) and clean data sets was performed using both a set of standard parameters and a metrics introduced in our work. All metrics used clearly identifies the main features of errors (systematic and random) present in the homogenized time series. We calculated the metrics for every time series (only over adjusted segments) as well as their averaged values as measures of uncertainties in the whole data set.&lt;/p&gt;&lt;p&gt;In order to determine how the two key parameters of the raw data collection, namely the length of time series and station density, influence the calculated measures of the adjustment error we gradually decreased the length of the period and number of stations in the area under study. The total number of cases considered was 56, including 7 time periods (1950-2005, 1954-2005, &amp;#8230;, 1974-2005) and 8 different quantities of stations (100, 90, &amp;#8230;, 30). Additionally, in order to find out how stable are the calculated metrics for each of the 56 cases and determine their confidence intervals we performed 100 random permutations in the introduced inhomogeneity time series and repeated our calculations With that the total number of homogenization exercises performed was 5600 for each of two climate variables.&lt;/p&gt;&lt;p&gt;Lastly, the calculated metrics were compared with the corresponding values, obtained for raw time series. The comparison showed some substantial improvement of the metric values after homogenization in each of the 56 cases considered (for the both variables).&lt;/p&gt;&lt;p&gt;-------------------&lt;/p&gt;&lt;p&gt;&lt;sup&gt;*&lt;/sup&gt;INDECIS is a part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). The work has been partially supported by the Ministry of Education and Science of Kazakhstan (Grant BR05236454) and Nazarbayev University (Grant 090118FD5345).&lt;/p&gt;

A Method for Estimating the Evolution of Brewer-Dobson Circulation Upwelling

2020 ◽  
Author(s):  
Edward Charlesworth ◽  
Felix Ploeger ◽  
Mohamadu Diallo ◽  
Thomas Birner ◽  
Patrick Joeckel
Keyword(s):  
Balance Equation ◽  
Seasonal Cycle ◽  
Inverse Method ◽  
Lower Stratosphere ◽  
Climate Model ◽  
Vertical Mixing ◽  
Model Data ◽  
Absolute Value ◽  
Multiple Datasets

&lt;p&gt;Both theory and climate model results suggest that the Brewer-Dobson circulation should strengthen in the stratosphere with increasing greenhouse gas concentrations. Directly measuring the circulation strength is not possible, so verification of this sensitivity has been limited to indirect inferences from observed tracer fields of long-lived species. These methods, however, are complex and accumulation of the data required for them is difficult. When limiting discussion to the tropical lower stratosphere, ozone concentrations have shown to be consistent with an accelerating circulation. These measurements are particularly useful because of the long timeseries available from multiple datasets, but they have only been used for indirect investigations of the circulation strength, up until now.&lt;/p&gt;&lt;p&gt;In this work, we invert the ozone balance equation to solve for upwelling. By limiting the investigation to 70 hPa in the southern tropics and estimating upwelling anomalies from the long-term mean (and not the absolute value of upwelling) most chemical terms and both horizontal and vertical mixing can be neglected, and calculation of the remaining terms is straight-forward. To verify the validity of the method, a calculation of upwelling is performed using climate model data, from which a comparison of actual upwelling and upwelling from the inverse method can be made. The seasonal cycle of upwelling anomalies is compared to upwelling anomalies from reanalyses and model results, and trends and variability are discussed.&lt;/p&gt;

scholarly journals First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change

2012 ◽  
Vol 5 (1) ◽  
pp. 1355-1379
Author(s):  
F. Forster ◽  
R. Sussmann ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
D. W. T. Griffith ◽  
...  
Keyword(s):  
Time Series ◽  
Near Infrared ◽  
Calibration Factor ◽  
Time Dependent ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Data Set ◽  
The Difference ◽  
Difference Time

Abstract. We present the intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar FTIR measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.). Direct comparison of the retrieved MIR and NIR time series shows a phase shift in XCH4 seasonality, i.e. a significant time-dependent bias leading to a standard deviation (stdv) of the difference time series (NIR-MIR) of 8.4 ppb. After eliminating differences in a prioris by using ACTM-simulated profiles as a common prior, the seasonalities of the (corrected) MIR and NIR time series agree within the noise (stdv = 5.2 ppb for the difference time series). The difference time series (NIR-MIR) do not show a significant trend. Therefore it is possible to use a simple scaling factor for the intercalibration without a time-dependent linear or seasonal component. Using the Garmisch and Wollongong data together, we obtain an overall calibration factor MIR/NIR = 0.9926(18). The individual calibration factors per station are 0.9940(14) for Garmisch and 0.9893(40) for Wollongong. They agree within their error bars with the overall calibration factor which can therefore be used for both stations. Our results suggest that after applying the proposed intercalibration concept to all stations performing both NIR and MIR measurements, it should be possible to obtain one refined overall intercalibration factor for the two networks. This would allow to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

scholarly journals Analysis of global water vapour trends from satellite measurements in the visible spectral range

2007 ◽  
Vol 7 (4) ◽  
pp. 11761-11796 ◽  
Author(s):  
S. Mieruch ◽  
S. Noël ◽  
H. Bovensmann ◽  
J. P. Burrows
Keyword(s):  
Time Series ◽  
Water Vapour ◽  
Statistical Significance ◽  
Visible Spectral Range ◽  
Optical Absorption Spectroscopy ◽  
Data Set ◽  
Factors Affecting ◽  
Scanning Imaging ◽  
Global Water

Abstract. Global water vapour total column amounts have been retrieved from spectral data provided by the Global Ozone Monitoring Experiment (GOME) flying on ERS-2, which was launched in April 1995, and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard ENVISAT launched in March 2002. For this purpose the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) approach has been used. The combination of the data from both instruments provides us with a long-term global data set spanning more than 11 years with the potential of extension up to 2020 by GOME-2 data, on Metop. Using linear and non-linear methods from time series analysis and standard statistics the trends of H2O contents and their errors have been calculated. In this study, factors affecting the trend such as the length of the time series, the magnitude of the variability of the noise, and the autocorrelation of the noise are investigated. Special emphasis has been placed on the calculation of the statistical significance of the observed trends, which reveal significant local changes of water vapour columns distributed over the whole globe.

scholarly journals Evaluation of CLaMS, KASIMA and ECHAM5/MESSy1 simulations in the lower stratosphere using observations of Odin/SMR and ILAS/ILAS-II

2009 ◽  
Vol 9 (1) ◽  
pp. 1977-2020
Author(s):  
F. Khosrawi ◽  
R. Müller ◽  
M. H. Proffitt ◽  
R. Ruhnke ◽  
O. Kirner ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
General Circulation ◽  
Lower Stratosphere ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Circulation Model ◽  
Lagrangian Model ◽  
Data Sets ◽  
Data Set ◽  
The Impact

Abstract. 1-year data sets of monthly averaged nitrous oxide (N2O) and ozone (O3) derived from satellite measurements were used as a tool for the evaluation of atmospheric photochemical models. Two 1-year data sets, one derived from the Improved Limb Atmospheric Spectrometer (ILAS and ILAS-II) and one from the Odin Sub-Millimetre Radiometer (Odin/SMR) were employed. Here, these data sets are used for the evaluation of two Chemical Transport Models (CTMs), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA) and the Chemical Lagrangian Model of the Stratosphere (CLaMS) as well as for one Chemistry-Climate Model (CCM), the atmospheric chemistry general circulation model ECHAM5/MESSy1 (E5M1) in the lower stratosphere with focus on the Northern Hemisphere. Since the Odin/SMR measurements cover the entire hemisphere, the evaluation is performed for the entire hemisphere as well as for the low latitudes, midlatitudes and high latitudes using the Odin/SMR 1-year data set as reference. To assess the impact of using different data sets for such an evaluation study we repeat the evaluation for the polar lower stratosphere using the ILAS/ILAS-II data set. Only small differences were found using ILAS/ILAS-II instead of Odin/SMR as a reference, thus, showing that the results are not influenced by the particular satellite data set used for the evaluation. The evaluation of CLaMS, KASIMA and E5M1 shows that all models are in good agreement with Odin/SMR and ILAS/ILAS-II. Differences are generally in the range of ±20%. Larger differences (up to −40%) are found in all models at 500±25 K for N2O mixing ratios greater than 200 ppb. Generally, the largest differences were found for the tropics and the lowest for the polar regions. However, an underestimation of polar winter ozone loss was found both in KASIMA and E5M1 both in the Northern and Southern Hemisphere.

Sign in / Sign up

Export Citation Format

Share Document