scholarly journals An aerosol vertical data assimilation system (NAQPMS-PDAF v1.0): development and application

2022 ◽  
Author(s):  
Haibo Wang ◽  
Ting Yang ◽  
Zifa Wang ◽  
Jianjun Li ◽  
Wenxuan Chai ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Global Climate ◽  
Correlation Coefficients ◽  
Orthogonal Polarization ◽  
Vertical Profiles ◽  
Online Data ◽  
Ground Based Lidar ◽  
The Impact

Abstract. Aerosol vertical stratification information is important for global climate and planetary boundary layer (PBL) stability, and no single method can obtain spatiotemporally continuous vertical profiles. This paper develops an online data assimilation (DA) framework for the Eulerian atmospheric chemistry-transport model (CTM) Nested Air Quality Prediction Model System (NAQPMS) with the Parallel Data Assimilation Framework (PDAF) as the NAQPMS-PDAF for the first time. Online coupling occurs via a memory-based approach with two-level parallelization, and the arrangement of state vectors during the filter is specifically designed. Scaling tests provide evidence that the NAQPMS-PDAF can make efficient use of parallel computational resources for up to 2.5 k processors with weak scaling efficiency up to 0.7. One-month-long aerosol extinction coefficient profiles measured by the ground-based lidar and the concurrent hourly surface PM2.5 are solely and simultaneously assimilated to investigate the performance and application of the DA system. The hourly analysis and subsequent one-hour simulation are validated through lidar and surface PM2.5 measurements assimilated and not assimilated. The results show that lidar DA can significantly improve the underestimation of aerosol loading, especially at a height of approximately 400 m in the free-running (FR) experiment, with the BIAS changing from −0.20 (−0.14) 1/km to −0.02 (−0.01) 1/km and correlation coefficients increasing from 0.33 (0.28) to 0.91 (0.53) averaged over sites with measurements assimilated (not assimilated). Compared with the FR experiment, simultaneously assimilating PM2.5 and lidar can have a more consistent pattern of aerosol vertical profiles with a combination of surface PM2.5 and lidar, independent extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and aerosol optical depth (AOD) from the Aerosol Robotic Network (AERONET). Lidar DA has a larger temporal impact than that in PM2.5 DA but has deficiencies in subsequent quantification on the surface PM2.5. The proposed NAQPMS-PDAF has great potential for further research on the impact of aerosol vertical distribution.

scholarly journals Impact of uncertainties in inorganic chemical rate constants on tropospheric composition and ozone radiative forcing

2017 ◽  
Author(s):  
Ben Newsome ◽  
Mat Evans
Keyword(s):  
Rate Constant ◽  
Atmospheric Chemistry ◽  
Rate Constants ◽  
Tropospheric Ozone ◽  
Radiative Forcing ◽  
Transport Model ◽  
Surface Ozone ◽  
Photolysis Rates ◽  
The Impact ◽  
Chemical Rate

Abstract. Chemical rate constants determine the composition of the atmosphere and how this composition has changed over time. They are central to our understanding of climate change and air quality degradation. Atmospheric chemistry models, whether online or offline, box, regional or global use these rate constants. Expert panels synthesise laboratory measurements, making recommendations for the rate constants that should be used. This results in very similar or identical rate constants being used by all models. The inherent uncertainties in these recommendations are, in general, therefore ignored. We explore the impact of these uncertainties on the composition of the troposphere using the GEOS-Chem chemistry transport model. Based on the JPL and IUPAC evaluations we assess 50 mainly inorganic rate constants and 10 photolysis rates, through simulations where we increase the rate of the reactions to the 1σ upper value recommended by the expert panels. We assess the impact on 4 standard metrics: annual mean tropospheric ozone burden, surface ozone and tropospheric OH concentrations, and tropospheric methane lifetime. Uncertainty in the rate constants for NO2 + OH    M →  HNO3, OH + CH4 → CH3O2 + H2O and O3 + NO → NO2 + O2 are the three largest source of uncertainty in these metrics. We investigate two methods of assessing these uncertainties, addition in quadrature and a Monte Carlo approach, and conclude they give similar outcomes. Combining the uncertainties across the 60 reactions, gives overall uncertainties on the annual mean tropospheric ozone burden, surface ozone and tropospheric OH concentrations, and tropospheric methane lifetime of 11, 12, 17 and 17 % respectively. These are larger than the spread between models in recent model inter-comparisons. Remote regions such as the tropics, poles, and upper troposphere are most uncertain. This chemical uncertainty is sufficiently large to suggest that rate constant uncertainty should be considered when model results disagree with measurement. Calculations for the pre-industrial allow a tropospheric ozone radiative forcing to be calculated of 0.412 ± 0.062 Wm−2. This uncertainty (15 %) is comparable to the inter-model spread in ozone radiative forcing found in previous model-model inter-comparison studies where the rate constants used in the models are all identical or very similar. Thus the uncertainty of tropospheric ozone radiative forcing should expanded to include this additional source of uncertainty. These rate constant uncertainties are significant and suggest that refinement of supposedly well known chemical rate constants should be considered alongside other improvements to enhance our understanding of atmospheric processes.

scholarly journals Model – TCCON comparisons of column-averaged methane with a focus on the stratosphere

2016 ◽  
Author(s):  
Andreas Ostler ◽  
Ralf Sussmann ◽  
Prabir K. Patra ◽  
Sander Houweling ◽  
Marko De Bruine ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Meteorological Data ◽  
Michelson Interferometer ◽  
Total Carbon ◽  
Data Sets ◽  
Transport Models ◽  
Improved Model ◽  
The Impact ◽  
Chemistry Experiment

Abstract. The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model-TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. In comparison to simulated model fields we find an improved model-TCCON XCH4 agreement for all models with MIPAS-based stratospheric CH4 fields. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 ppb to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 ppb to 4.3 ppb), and LMDz (Laboratoire de Météorologie Dynamique model with Zooming capability; from 6.8 ppb to 4.3 ppb), respectively. MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduce the average XCH4 bias for ACTM (3.3 ppb), but increase the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that the range of satellite-based stratospheric CH4 is insufficient to resolve a possible stratospheric contribution to differences in total column CH4 between TCCON and TM5 or LMDz. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. This implies that there is a need to better understand the impact of individual model transport components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) on modeled stratospheric CH4.

Investigation of the impact of thermodynamic profiles of ground based lidar systems on short-range forecast skill by means of ETKF-hybrid 3DVAR data assimilation

2021 ◽  
Author(s):  
Rohith Thundathil ◽  
Thomas Schwitalla ◽  
Andreas Behrendt ◽  
Diego Lange ◽  
Florian Späth ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Wrf Model ◽  
Absolute Humidity ◽  
Raman Lidar ◽  
High Definition ◽  
Background Error ◽  
Ground Based Lidar ◽  
Ensemble Transform Kalman Filter ◽  
Definition Of ◽  
The Impact

<p>Ground based active remote-sensing instruments have proved its potential through its high quality observations of thermodynamic profiles. In this study, thermodynamic profiles obtained from the temperature Raman lidar (TRL) and the water-vapour differential absorption lidar (DIAL) of the University of Hohenheim (UHOH) are assimilated into the Weather Research and Forecasting model data assimilation (WRFDA) system through a new forward operator for absolute humidity and mixing ratio developed in-house.<br>Thermodynamic DA was performed either with the deterministic 3-dimensional variational (3DVAR) DA system or with the hybrid 3DVAR-Ensemble Transform Kalman Filter (ETKF) approach. We used data of the High Definition of Clouds and Precipitation for advancing Climate Prediction (HD(CP)2 project Observation Prototype Experiment (HOPE). The WRF model was configured for a central European domain at a convection permitting resolution of 2.5 km spatial grid increment and 100 levels in the vertical with fine resolution in the planetary boundary layer (PBL). The assimilation experiments were conducted in a rapid update cycle (RUC) mode with an hourly update frequency. The hybrid 3DVAR-ETKF DA system was incorporated with an adaptive inflation scheme using a set of 10 ensemble members each with the same configuration as the previous experiments for the 3DVAR.  We will present the results of three DA experiments. In the first experiment (CONV_DA), or the control run, only assimilation of the conventional observations was carried out with 3DVAR DA. The second experiment (QT_DA) was a 3DVAR DA assimilating WVMR and temperature together in addition to the conventional dataset. The third experiment (QT_HYB_DA) assimilated WVMR and temperature together in addition to the conventional dataset with Hybrid DA.<br>The WVMR RMSE with respect to the WVDIAL reduced by 41 % in 3DVAR and still reduced to 51 % in QT_HYB_DA compared to CONV_DA. Although temperature RMSE with respect to TRL increased by 5 % in QT_DA, RMSE significantly reduced to 47 % in QT_HYB_DA compared to CONV_DA. The correlation between the temperature and WVMR variables in the background error covariance matrix of the 3DVAR, which is static and not flow-dependent, limited the improvement in temperature. Flow-dependency in Hybrid DA improved the error correlations.<br>We also present results of a collaborative effort with the Raman lidar for meteorological observation (RALMO) from the MeteoSwiss and the Atmospheric Raman Temperature and Humidity Sounder (ARTHUS) using even finer model resolution. The initial results of the new study will also be presented here.</p>

scholarly journals The impact of Climate Change on the Western Pacific Subtropical High and the related ozone pollution in Shanghai, China

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Luyu Chang ◽  
Jianming Xu ◽  
Xuexi Tie ◽  
Wei Gao
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Transport Model ◽  
Global Climate ◽  
Photochemical Reactions ◽  
Ozone Pollution ◽  
High Positive Correlation ◽  
Near Surface ◽  
High Solar Radiation ◽  
The Impact

AbstractSevere ozone (O3) episodes occur frequently in Shanghai during late-summers. We define geopotential height averaged over the key area region (122.5°E-135°E, 27.5°N -35°N) at 500 hPa as a WPSH_SHO3 index which has high positive correlation with surface O3 concentration in Shanghai. In addition, the index has a significant long-term increasing trend during the recent 60 years. Analysis shows the meteorological conditions under the strong WPSH_SHO3 climate background (compared to the weak background) have several important anomalies: (1) A strong WPSH center occurs over the key area region. (2) The cloud cover is less, resulting in high solar radiation and low humidity, enhancing the photochemical reactions of O3. (3) The near-surface southwesterly winds are more frequent, enhancing the transport of upwind pollutants and O3 precursors from polluted regions to Shanghai and producing higher O3 chemical productions. This study suggests that the global climate change could lead to a stronger WPSH in the key region, enhancing ozone pollution in Shanghai. A global chemical/transport model (MOZART-4) is applied to show that the O3 concentrations can be 30 ppbv higher under a strong WPSH_SHO3 condition than a weak condition, indicating the important effect of the global climate change on local air pollution in Shanghai.

scholarly journals The constraint of CO<sub>2</sub> measurements made onboard passenger aircraft on surface-atmosphere fluxes: the impact of transport model errors in vertical mixing

2016 ◽  
Author(s):  
Shreeya Verma ◽  
Julia Marshall ◽  
Christoph Gerbig ◽  
Christian Roedenbeck ◽  
Kai Uwe Totsche
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Synthetic Data ◽  
Vertical Profiles ◽  
Model Errors ◽  
Transport Models ◽  
Boundary Layer Height ◽  
Temporal Sampling ◽  
The Impact

Abstract. Inaccurate representation of atmospheric processes by transport models is a dominant source of uncertainty in inverse analyses and can lead to large discrepancies in the retrieved flux estimates. We investigate the impact of uncertainties in vertical transport as simulated by atmospheric transport models on fluxes retrieved using vertical profiles from aircraft as an observational constraint. Our numerical experiments are based on synthetic data with realistic spatial and temporal sampling of aircraft measurements. The impact of such uncertainties on the flux retrieved using the ground-based network with those retrieved using the aircraft profiles are compared. We find that the posterior flux retrieved using aircraft profiles is less susceptible to errors in boundary layer height as compared to the ground- based network. This highlights the benefit of utilizing atmospheric observations made onboard aircraft over surface measurements for flux estimation using inverse methods. We further use synthetic vertical profiles of CO2 in an inversion to estimate the potential of these measurements, which will be made available through the IAGOS (In-Service Aircraft for a Global Observing System) project in future, in constraining the regional carbon budget. Our results show that the regions tropical Africa and temperate Eurasia, that are under constrained by the existing surface based network, will benefit the most from these measurements, the reduction of posterior flux uncertainty being about 7 to 10 %.

scholarly journals Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

2013 ◽  
Vol 13 (19) ◽  
pp. 9917-9937 ◽  
Author(s):  
R. Locatelli ◽  
P. Bousquet ◽  
F. Chevallier ◽  
A. Fortems-Cheney ◽  
S. Szopa ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Initial Conditions ◽  
Spatial Scales ◽  
Global Scale ◽  
Methane Emissions ◽  
Inverse Modelling ◽  
Model Errors ◽  
Inverse Systems ◽  
The Impact

Abstract. A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System) inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure) is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr−1 at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr−1 in North America to 7 Tg yr−1 in Boreal Eurasia (from 23 to 48%, respectively). At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly question the consistency of transport model errors in current inverse systems. Future inversions should include more accurately prescribed observation covariances matrices in order to limit the impact of transport model errors on estimated methane fluxes.

scholarly journals Global stratospheric fluorine inventory for 2004–2009 from Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) measurements and SLIMCAT model simulations

2014 ◽  
Vol 14 (1) ◽  
pp. 267-282 ◽  
Author(s):  
A. T. Brown ◽  
M. P. Chipperfield ◽  
N. A. D. Richards ◽  
C. Boone ◽  
P. F. Bernath
Keyword(s):  
Atmospheric Chemistry ◽  
Radiative Forcing ◽  
Transport Model ◽  
Similar Rate ◽  
Montreal Protocol ◽  
Negative Slope ◽  
Mixing Ratios ◽  
Inorganic Species ◽  
The Tropics ◽  
The Impact

Abstract. Fluorine-containing species can be extremely effective atmospheric greenhouse gases. We present fluorine budgets using organic and inorganic species retrieved by the ACE-FTS satellite instrument supplemented with output from the SLIMCAT 3-D chemical transport model. The budgets are calculated between 2004 and 2009 for a number of latitude bands: 70–30° N, 30–00° N, 00° N–30° S, and 30–70° S. At lower altitudes total fluorine profiles are dominated by the contribution from CFC-12, up to an altitude of 20 km in the extra-tropics and 29 km in the tropics; above these altitudes the profiles are dominated by hydrogen fluoride (HF). Our data show that total fluorine profiles at all locations have a negative slope with altitude, providing evidence that overall fluorine emissions (measured by their F content) have been increasing with time. Total stratospheric fluorine is increasing at a similar rate in the tropics: 32.5 ± 4.9 ppt yr−1 (1.31 ± 0.20% per year) in the Northern Hemisphere (NH) and 29.8 ± 5.3 ppt yr−1 (1.21 ± 0.22% per year) in the Southern Hemisphere (SH). Extra-tropical total stratospheric fluorine is also increasing at a similar rate in both the NH and SH: 28.3 ± 2.7 ppt per year (1.12 ± 0.11% per year) in the NH and 24.3 ± 3.1 ppt per year (0.96 ± 0.12% per year) in the SH. The calculation of radiative efficiency-weighted total fluorine allows the changes in radiative forcing between 2004 and 2009 to be calculated. These results show an increase in radiative forcing of between 0.23 ± 0.11% per year and 0.45 ± 0.11% per year, due to the increase in fluorine-containing species during this time. The decreasing trends in the mixing ratios of halons and chlorofluorocarbons (CFCs), due to their prohibition under the Montreal Protocol, have suppressed an increase in total fluorine caused by increasing mixing ratios of hydrofluorocarbons (HFCs). This has reduced the impact of fluorine-containing species on global warming.

scholarly journals Assimilation of lidar signals: application to aerosol forecasting in the Mediterranean Basin

2014 ◽  
Vol 14 (9) ◽  
pp. 13059-13107 ◽  
Author(s):  
Y. Wang ◽  
K. N. Sartelet ◽  
M. Bocquet ◽  
P. Chazette ◽  
M. Sicard ◽  
...  
Keyword(s):  
Transport Model ◽  
Interpolation Method ◽  
Period Length ◽  
Research Network ◽  
Optimal Interpolation ◽  
Aerodynamic Diameter ◽  
Background Error ◽  
The Mediterranean ◽  
Ground Based Lidar ◽  
The Impact

Abstract. This paper presents a new application of assimilating lidar signals to aerosol forecasting. It aims at investigating the impact of a ground-based lidar network on analysis and short-term forecasts of aerosols through a case study in the Mediterranean. To do so, we employ a data assimilation (DA) algorithm based on the optimal interpolation method developed in the chemistry transport model (CTM) {Polair3D of the air quality modelling platform POLYPHEMUS. We assimilate hourly-averaged normalised range corrected lidar signals (PR2) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EARLINET) integrated into the Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS) and an additional system in Corsica deployed in the framework of the pre-ChArMEx (Chemistry-Aerosol Mediterranean Experiment)/TRAQA (TRAnsport à longue distance et Qualité de l'Air) campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research network like EARLINET and the potential usefulness of assimilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 μm (PM2.5) and those with an aerodynamic diameter higher than 2.5 μm but lower than 10 μm (PM2.5–10) are analysed separately using the lidar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on algorithmic parameters, e.g. the horizontal correlation length (Lh) used in the background error covariance matrix (50 km, 100 km or 200 km), the altitudes at which DA is performed (0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l.) and the assimilation period length (12 h or 24 h). We find that DA with Lh = 100 km and assimilation from 1.0 to 3.5 km a.g.l. during a 12 h assimilation period length leads to the best scores for PM10 and PM2.5 during the forecast period with reference to available measurements from surface networks. Secondly, the aerosol simulation results without and with lidar DA using the optimal parameters (Lh

scholarly journals Stratospheric lifetime ratio of CFC-11 and CFC-12 from satellite and model climatologies

2014 ◽  
Vol 14 (11) ◽  
pp. 16865-16906 ◽  
Author(s):  
L. Hoffmann ◽  
C. M. Hoppe ◽  
R. Müller ◽  
G. S. Dutton ◽  
J. C. Gille ◽  
...  
Keyword(s):  
Global Warming ◽  
Atmospheric Chemistry ◽  
Climate Model ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Michelson Interferometer ◽  
Coupled Model ◽  
Model System ◽  
Satellite Observations ◽  
The Impact

Abstract. Chlorofluorocarbons (CFCs) play a key role in stratospheric ozone loss and are strong infrared absorbers that contribute to global warming. The stratospheric lifetimes of CFCs are a measure of their global loss rates that are needed to determine global warming and ozone depletion potentials. We applied the tracer-tracer correlation approach to zonal mean climatologies from satellite measurements and model data to assess the lifetimes of CFCl3 (CFC-11) and CF2Cl2 (CFC-12). We present estimates of the CFC-11/CFC-12 lifetime ratio and the absolute lifetime of CFC-12, based on a reference lifetime of 52 yr for CFC-11. We analyzed climatologies from three satellite missions, the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS), the HIgh Resolution Dynamics Limb Sounder (HIRDLS), and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). We found a CFC-11/CFC-12 lifetime ratio of 0.47±0.08 and a CFC-12 lifetime of 111(96–132) yr for ACE-FTS, a ratio of 0.46±0.07 and a lifetime of 112(97–133) yr for HIRDLS, and a ratio of 0.46±0.08 and a lifetime of 112(96–135) yr for MIPAS. The error-weighted, combined CFC-11/CFC-12 lifetime ratio is 0.47±0.04 and the CFC-12 lifetime estimate is 112(102–123) yr. These results agree with the recent Stratosphere-troposphere Processes And their Role in Climate (SPARC) reassessment, which recommends lifetimes of 52(43–67) yr and 102(88–122) yr, respectively. Having smaller uncertainties than the results from other recent studies, our estimates can help to better constrain CFC-11 and CFC-12 lifetime recommendations in future scientific studies and assessments. Furthermore, the satellite observations were used to validate first simulation results from a new coupled model system, which integrates a Lagrangian chemistry transport model into a climate model. For the coupled model we found a CFC-11/CFC-12 lifetime ratio of 0.48±0.07 and a CFC-12 lifetime of 110(95–129) yr, based on a ten-year perpetual run. Closely reproducing the satellite observations, the new model system will likely become a useful tool to assess the impact of advective transport, mixing, and photochemistry as well as climatological variability on the stratospheric lifetimes of long-lived tracers.

scholarly journals Evaluating nighttime CALIOP 0.532 μm aerosol optical depth and extinction coefficient retrievals

2012 ◽  
Vol 5 (2) ◽  
pp. 2747-2794 ◽  
Author(s):  
J. R. Campbell ◽  
J. L. Tackett ◽  
J. S. Reid ◽  
J. Zhang ◽  
C. A. Curtis ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Extinction Coefficient ◽  
A Priori ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Vertical Profiles ◽  
Diurnal Variability ◽  
Data Points ◽  
Ground Based Lidar

Abstract. NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 μm aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1° × 1° resolution versus corresponding/co-incident 0.550 μm AOD derived using the US Navy Aerosol Analysis and Prediction System (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. Daytime datasets are investigated similarly for context. Regional-mean CALIOP vertical profiles of night/day 0.532 μm extinction coefficient are compared with 0.523/0.532 μm ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalized 1° × 1° bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalized bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach ±20%. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalized bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a-priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day.

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