We have previously demonstrated a pulsed direct detection IPDA lidar to measure range and the column concentration of atmospheric CO₂. The lidar measures the atmospheric backscatter profiles and samples the shape of the 1,572.33 nm CO₂ absorption line. We participated in the ASCENDS science flights on the NASA DC-8 aircraft during August 2011 and report here lidar measurements made on four flights over a variety of surface and cloud conditions near the US. These included over a stratus cloud deck over the Pacific Ocean, to a dry lake bed surrounded by mountains in Nevada, to a desert area with a coal-fired power plant, and from the Rocky Mountains to Iowa, with segments with both cumulus and cirrus clouds. Most flights were to altitudes >12 km and had 5–6 altitude steps. Analyses show the retrievals of lidar range, CO₂ column absorption, and CO₂ mixing ratio worked well when measuring over topography with rapidly changing height and reflectivity, through thin clouds, between cumulus clouds, and to stratus cloud tops. The retrievals shows the decrease in column CO₂ due to growing vegetation when flying over Iowa cropland as well as a sudden increase in CO₂ concentration near a coal-fired power plant. For regions where the CO₂ concentration was relatively constant, the measured CO₂ absorption lineshape (averaged for 50 s) matched the predicted shapes to better than 1% RMS error. For 10 s averaging, the scatter in the retrievals was typically 2–3 ppm and was limited by the received signal photon count. Retrievals were made using atmospheric parameters from both an atmospheric model and from in situ temperature and pressure from the aircraft. The retrievals had no free parameters and did not use empirical adjustments, and >70% of the measurements passed screening and were used in analysis. The differences between the lidar-measured retrievals and in situ measured average CO2 column concentrations were 6 km.

Here we report on measurements made with an improved CO₂ Sounder lidar during the ASCENDS 2014 and 2016 airborne campaigns. The changes made to the 2011 version of the lidar included incorporating a rapidly wavelength-tunable, step-locked seed laser in the transmitter, using a much more sensitive HgCdTe APD detector and using an analog digitizer with faster readout time in the receiver. We also improved the lidar's calibration approach and the XCO₂ retrieval algorithm. The 2014 and 2016 flights were made over several types of topographic surfaces from 3 to 12 km aircraft altitudes in the continental US. The results are compared to the XCO₂ values computed from an airborne in situ sensor during spiral-down maneuvers. The 2014 results show significantly better performance and include measurement of horizontal gradients in XCO₂ made over the Midwestern US that agree with chemistry transport models. The results from the 2016 airborne lidar retrievals show precisions of ∼ 0.7 parts per million (ppm) with 1 s averaging over desert surfaces, which is an improvement of about 8 times compared to similar measurements made in 2011. Measurements in 2016 were also made over fresh snow surfaces that have lower surface reflectance at the laser wavelengths. The results from both campaigns showed that the mean values of XCO₂ retrieved from the lidar consistently agreed with those based on the in situ sensor to within 1 ppm. The improved precision and accuracy demonstrated in the 2014 and 2016 flights should benefit future airborne science campaigns and advance the technique's readiness for a space-based instrument.

We have measured the column-averaged atmospheric CO₂ mixing ratio to a variety of cloud tops by using an airborne pulsed multi-wavelength integrated-path differential absorption (IPDA) lidar. Airborne measurements were made at altitudes up to 13 km during the 2011, 2013 and 2014 NASA Active Sensing of CO₂ Emissions over Nights, Days, and Seasons (ASCENDS) science campaigns flown in the United States West and Midwest and were compared to those from an in situ sensor. Analysis of the lidar backscatter profiles shows the average cloud top reflectance was ∼ 5 % for the CO₂ measurement at 1572.335 nm except to cirrus clouds, which had lower reflectance. The energies for 1 µs wide laser pulses reflected from cloud tops were sufficient to allow clear identification of CO₂ absorption line shape and then to allow retrievals of atmospheric column CO₂ from the aircraft to cloud tops more than 90 % of the time. Retrievals from the CO₂ measurements to cloud tops had minimal bias but larger standard deviations when compared to those made to the ground, depending on cloud top roughness and reflectance. The measurements show this new capability helps resolve CO₂ horizontal and vertical gradients in the atmosphere. When used with nearby full-column measurements to ground, the CO₂ measurements to cloud tops can be used to estimate the partial-column CO₂ concentration below clouds, which should lead to better estimates of surface carbon sources and sinks. This additional capability of the range-resolved CO₂ IPDA lidar technique provides a new benefit for studying the carbon cycle in future airborne and space-based CO₂ missions.

Measured upwelling radiances from Nimbus-7 SBUV (Solar Backscatter Ultraviolet) and seven NOAA SBUV/2 instruments have been used to calculate the 340 nm Lambertian equivalent reflectivity (LER) of the Earth from 1979 to 2011 after applying a common calibration. The 340 nm LER is highly correlated with cloud and aerosol cover because of the low surface reflectivity of the land and oceans (typically 2 to 6 RU, reflectivity units, where 1 RU = 0.01 = 1.0%) relative to the much higher reflectivity of clouds plus nonabsorbing aerosols (typically 10 to 90 RU). Because of the nearly constant seasonal and long-term 340 nm surface reflectivity in areas without snow and ice, the 340 nm LER can be used to estimate changes in cloud plus aerosol amount associated with seasonal and interannual variability and decadal climate change. The annual motion of the Intertropical Convergence Zone (ITCZ), episodic El Niño Southern Oscillation (ENSO), and latitude-dependent seasonal cycles are apparent in the LER time series. LER trend estimates from 5° zonal average and from 2° × 5° , latitude × longitude, time series show that there has been a global net decrease in 340 nm cloud plus aerosol reflectivity. The decrease in cos²(latitude) weighted average LER from 60° S to 60° N is 0.79 ± 0.03 RU over 33 yr, corresponding to a 3.6 ± 0.2% decrease in LER. Applying a 3.6% cloud reflectivity perturbation to the shortwave energy balance partitioning given by Trenberth et al. (2009) corresponds to an increase of 2.7 W m⁻² of solar energy reaching the Earth's surface and an increase of 1.4% or 2.3 W m⁻² absorbed by the surface, which is partially offset by increased longwave cooling to space. Most of the decreases in LER occur over land, with the largest decreases occurring over the US (−0.97 RU decade⁻¹), Brazil (−0.9 RU decade⁻¹), and central Europe (−1.35 RU decade⁻¹). There are reflectivity increases near the west coast of Peru and Chile (0.8 ± 0.1 RU decade⁻¹), over parts of India, China, and Indochina, and almost no change over Australia. The largest Pacific Ocean change is −2 ± 0.1 RU decade⁻¹ over the central equatorial region associated with ENSO. There has been little observed change in LER over central Greenland, but there has been a significant decrease over a portion of the west coast of Greenland. Similar significant decreases in LER are observed over a portion of the coast of Antarctica for longitudes −160° to −60° and 80° to 150°.

We review the singular value decomposition (SVD) framework and use it for quantifying and discerning vertical information in greenhouse gas retrievals from column integrated absorption measurements. While the commonly used traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We review the SVD method, explicitly recognize the use of an uninformative prior and show it to incur no bias from the choice of the prior. We also make the connection between the SVD method and the pseudo-inverse, which makes it more intuitive and easy to understand. We illustrate the use of the SVD method on an integrated path differential absorption CO₂ lidar measurement model and verify our derivations and bias-free properties versus optimal estimation using numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. Hence, the SVD method is particularly useful for situations in which knowledge of the prior mean and prior covariance of the true state (e.g., greenhouse gas profiles) is inadequate.

We present observing system simulation experiments (OSSEs) to evaluate the impact of a proposed network of ground-based miniaturized laser heterodyne radiometer (mini-LHR) instruments that measure atmospheric column-averaged carbon dioxide (XCO₂) with a 1 ppm precision. A particular strength of this passive measurement approach is its insensitivity to clouds and aerosols due to its direct sun pointing and narrow field of view (0.2^∘). Developed at the NASA Goddard Space Flight Center (GSFC), these portable, low-cost mini-LHR instruments were designed to operate in tandem with the sun photometers used by the AErosol RObotic NETwork (AERONET). This partnership allows us to leverage the existing framework of AERONET's global ground network of more than 500 sites as well as providing simultaneous measurements of aerosols that are known to be a major source of error in retrievals of XCO₂ from passive nadir-viewing satellite observations. We show, using the global 3-D GEOS-Chem chemistry transport model, that a deployment of 50 mini-LHRs at strategic (but not optimized) AERONET sites significantly improves our knowledge of global and regional land-based CO₂ fluxes. This improvement varies seasonally and ranges 58 %–81 % over southern lands, 47 %–76 % over tropical lands, 71 %–92 % over northern lands, and 64 %–91 % globally. We also show significant added value from combining mini-LHR instruments with the existing ground-based NOAA flask network. Collectively, these data result in improved a posteriori CO₂ flux estimates on spatial scales of ∼10 km², especially over North America and Europe, where the ground-based networks are densest. Our studies suggest that the mini-LHR network could also play a substantive role in reducing carbon flux uncertainty in Arctic and tropical systems by filling in geographical gaps in measurements left by ground-based networks and space-based observations. A realized network would also provide necessary data for the quinquennial global stocktakes that form part of the Paris Agreement.