Short-period solar cycle signals in the ionosphere observed by FORMOSAT-3/COSMIC

We analyze 2 years of the FORMOSAT-3/COSMIC GPS radio occultation data to study the response of the Earth's ionosphere to the solar rotation (27-day) induced solar flux variations. Here we report electron density variations in the ionosphere (∼100–500 km) associated with the 27-day solar cycle. The peak-to-peak variation in electron density at low latitudes in the F2 region is about ∼10^4–10^5 electrons cm^(−3) or 20–40%, and can be as high as 60% depending on altitude, latitude, and season. The half and double periods of the 27-day are also observed at an amplitude comparable to that of the 27-day. The results place useful constraints for modeling chemical and dynamical processes in the ionosphere

Coupling Processes Between Atmospheric Chemistry and Climate

This is the first semi-annual report for NAS5-97039 summarizing work performed for January 1997 through June 1997. Work in this project is related to NAS1-20666, also funded by NASA ACMAP. The work funded in this project also benefits from work at AER associated with the AER three-dimensional isentropic transport model funded by NASA AEAP and the AER two-dimensional climate-chemistry model (co-funded by Department of Energy). The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry

Simulation of upper tropospheric CO₂ from chemistry and transport models

The California Institute of Technology/Jet Propulsion Laboratory two-dimensional (2-D), three-dimensional (3-D) GEOS-Chem, and 3-D MOZART-2 chemistry and transport models (CTMs), driven respectively by NCEP2, GEOS-4, and NCEP1 reanalysis data, have been used to simulate upper tropospheric CO2 from 2000 to 2004. Model results of CO2 mixing ratios agree well with monthly mean aircraft observations at altitudes between 8 and 13 km (Matsueda et al., 2002) in the tropics. The upper tropospheric CO2 seasonal cycle phases are well captured by the CTMs. Model results have smaller seasonal cycle amplitudes in the Southern Hemisphere compared with those in the Northern Hemisphere, which are consistent with the aircraft data. Some discrepancies are evident between the model and aircraft data in the midlatitudes, where models tend to underestimate the amplitude of CO2 seasonal cycle. Comparison of the simulated vertical profiles of CO2 between the different models reveals that the convection in the 3-D models is likely too weak in boreal winter and spring. Model sensitivity studies suggest that convection mass flux is important for the correct simulation of upper tropospheric CO2

Accounting for aerosol scattering in the CLARS retrieval of column averaged CO_2 mixing ratios

The California Laboratory for Atmospheric Remote Sensing Fourier transform spectrometer (CLARS‐FTS) deployed at Mount Wilson, California, has been measuring column abundances of greenhouse gases in the Los Angeles (LA) basin in the near‐infrared spectral region since August 2011. CLARS‐FTS measures reflected sunlight and has high sensitivity to absorption and scattering in the boundary layer. In this study, we estimate the retrieval biases caused by aerosol scattering and present a fast and accurate approach to correct for the bias in the CLARS column averaged CO2 mixing ratio product, X_(CO2). The high spectral resolution of 0.06 cm^(−1) is exploited to reveal the physical mechanism for the bias. We employ a numerical radiative transfer model to simulate the impact of neglecting aerosol scattering on the CO_2 and O_2 slant column densities operationally retrieved from CLARS‐FTS measurements. These simulations show that the CLARS‐FTS operational retrieval algorithm likely underestimates CO_2 and O_2 abundances over the LA basin in scenes with moderate aerosol loading. The bias in the CO_2 and O_2 abundances due to neglecting aerosol scattering cannot be canceled by ratioing each other in the derivation of the operational product of X_(CO2). We propose a new method for approximately correcting the aerosol‐induced bias. Results for CLARS X_(CO2) are compared to direct‐Sun X_(CO2) retrievals from a nearby Total Carbon Column Observing Network (TCCON) station. The bias‐correction approach significantly improves the correlation between the X_(CO2) retrieved from CLARS and TCCON, demonstrating that this approach can increase the yield of useful data from CLARS‐FTS in the presence of moderate aerosol loading

Information-rich spectral channels for simulated retrievals of partial column-averaged methane

Space‐based remote sensing of the column‐averaged methane dry air mole fraction (XCH_4) has greatly increased our understanding of the spatiotemporal patterns in the global methane cycle. The potential to retrieve multiple pieces of vertical profile information would further improve the quantification of CH_4 across space‐time scales. We conduct information analysis for channel selection and evaluate the prospects of retrieving multiple pieces of information as well as total column CH_4 from both ground‐based and space‐based near‐infrared remote sensing spectra. We analyze the degrees of freedom of signal (DOF) in the CH_4 absorption bands near 2.3 μm and 1.6 μm and select ∼1% of the channels that contain >95% of the information about the CH_4 profile. The DOF is around 4 for fine ground‐based spectra (resolution = 0.01 cm^(−1)) and 3 for coarse space‐based spectra (resolution = 0.20 cm^(−1)) based on channel selection and a signal‐to‐noise ratio (SNR) of 300. The DOF varies from 2.2 to 3.2 when SNR is between 100 and 300, and spectral resolution is 0.20 cm^(−1). Simulated retrieval tests in clear‐sky conditions using the selected channels reveal that the retrieved partial column‐averaged CH_4 values are not sensitive to the a priori profiles and can reflect local enhancements of CH_4 in different partial air columns. Both the total and partial column‐averaged retrieval errors in all tests are within 1% of the true state. These simulated tests highlight the possibility to retrieve up to three to four pieces of information about the vertical distribution of CH_4 in reality

Seasonal cycle of N_2O: Analysis of data

We carried out a systematic study of the seasonal cycle and its latitudinal variation in the nitrous oxide (N_2O) data collected by National Oceanic and Atmospheric Administration–Global Monitoring Division (NOAA-GMD) and the Advanced Global Atmospheric Gases Experiment (AGAGE). In order to confirm the weak seasonal signal in the observations, we applied the multitaper method for the spectrum analysis and studied the stations with significant seasonal cycle. In addition, the measurement errors must be small compared with the seasonal cycle. The N_2O seasonal cycles from seven stations satisfied these criteria and were analyzed in detail. The stations are Alert (82°N, 62°W), Barrow (71°N, 157°W), Mace Head (53°N, 10°W), Cape Kumukahi (19°N, 155°W), Cape Matatula (14°S, 171°W), Cape Grim (41°S, 145°E) and South Pole (90°S, 102°W). The amplitude (peak to peak) of the seasonal cycle of N_2O varies from 0.29 ppb (parts-per-billion by mole fraction in dry air) at the South Pole to 1.15 ppb at Alert. The month at which the seasonal cycle is at a minimum varies monotonically from April (South Pole) to September (Alert). The seasonal cycle in the Northern Hemisphere shows the influence of the stratosphere; the seasonal cycle of N_2O in the Southern Hemisphere suggests greater influence from surface sources. Preliminary estimates are obtained for the magnitude of the seasonally varying sources needed to account for the observations

Fundamental modes of atmospheric CFC-11 from empirical mode decomposition

Following an initial growth, the concentrations of chlorofluorocarbon-11 (CFC-11) in the atmosphere started to decline in the 1990's due to world-wide legislative control on emissions. The amplitude of the annual cycle of CFC-11 was much larger in the earlier period compared with that in the later period. We apply here the Ensemble Empirical Mode Decomposition (EEMD) analysis to the CFC-11 data obtained by the U.S. National Oceanic and Atmospheric Administration. The sum of the second and third intrinsic mode functions (IMFs) represents the annual cycle, which shows that the annual cycle of CFC-11 has varied by a factor of 2–3 from the mid-1970's to the present over polar regions. The results provide an illustration of the power of the EEMD method in extracting a variable annual cycle from data dominated by increasing and decreasing trends. Finally, we compare the annual cycle obtained by the EEMD analysis to that obtained using conventional methods such as Fourier transforms and running averages

A non-monotonic eddy diffusivity profile of Titan's atmosphere revealed by Cassini observations

Recent measurements from the limb-view soundings of Cassini/CIRS and the stellar occultations from Cassini/UVIS revealed the complete vertical profiles of minor species (e.g., C_2H_2 and C_2H_4) from 100 to 1000 km in the atmosphere of Titan. In this study, we developed an inversion technique to retrieve the eddy diffusion profile using C_2H_2 as a tracer species. The retrieved eddy profile features a low eddy diffusion zone near the altitude of the detached haze layer (~550 km), which could be a consequence of stabilization through aerosol heating. Photochemical modeling results using the retrieved eddy profile are in better agreement with the Cassini measurements than previous models. The underestimation of C_2H_4 in the stratosphere has been a long-standing problem in planetary photochemical modeling, and the new eddy diffusion profile does not solve this problem. In order to match the observations, we suggest a new expression for the rate coefficient of the key reaction, H + C_2H_4 + M⟶C_2H_5 + M. The new reaction rate coefficient is estimated to be ~10 times lower than that used by Moses et al. (2005)'s model, and should be validated in the laboratory and tested against the hydrocarbon chemistry of giant planets

Spectropolarimetric Measurements of Scattered Sunlight in the Huggins Bands

No abstract availabl

Accounting for aerosol scattering in the CLARS retrieval of column averaged CO 2 mixing ratios

Abstract The California Laboratory for Atmospheric Remote Sensing Fourier transform spectrometer (CLARS-FTS) deployed at Mount Wilson, California, has been measuring column abundances of greenhouse gases in the Los Angeles (LA) basin in the near-infrared spectral region since August 2011. CLARS-FTS measures reflected sunlight and has high sensitivity to absorption and scattering in the boundary layer. In this study, we estimate the retrieval biases caused by aerosol scattering and present a fast and accurate approach to correct for the bias in the CLARS column averaged CO 2 mixing ratio product, X CO2 . The high spectral resolution of 0.06 cm À1 is exploited to reveal the physical mechanism for the bias. We employ a numerical radiative transfer model to simulate the impact of neglecting aerosol scattering on the CO 2 and O 2 slant column densities operationally retrieved from CLARS-FTS measurements. These simulations show that the CLARS-FTS operational retrieval algorithm likely underestimates CO 2 and O 2 abundances over the LA basin in scenes with moderate aerosol loading. The bias in the CO 2 and O 2 abundances due to neglecting aerosol scattering cannot be canceled by ratioing each other in the derivation of the operational product of X CO2 . We propose a new method for approximately correcting the aerosol-induced bias. Results for CLARS X CO2 are compared to direct-Sun X CO2 retrievals from a nearby Total Carbon Column Observing Network (TCCON) station. The bias-correction approach significantly improves the correlation between the X CO2 retrieved from CLARS and TCCON, demonstrating that this approach can increase the yield of useful data from CLARS-FTS in the presence of moderate aerosol loading