A Multi-Functional Fiber Laser Lidar for Earth Science &amp; Exploration

Dobbs, Michael E.; Krabill, William B.; Cisewski, Michael S.; Harriso, F. Wallace; Shum, C. K.; McGregor, Dong; Neal, Mark; Stokes, Sheldon S.

doi:10.1364/cleo.2009.cfj5

Cited by 6 publications

(5 citation statements)

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“…The MFLL, developed by Harris Corp., with support and evaluation by NASA's LaRC (Dobbs et al, ; ), was designed specifically to address the goals set by the Active Sensing of CO 2 over Nights, Days, and Seasons (ASCENDS) mission and is the first intensity‐modulated continuous‐wave (IM‐CW) laser absorption spectrometer (LAS). This section provides only a brief overview of the MFLL and its operation during ACT‐America; further details of the MFLL instrument for ACT‐America can be found in Campbell et al ().…”

Section: Instruments and Data Setsmentioning

confidence: 99%

Evaluation of OCO‐2 X Variability at Local and Synoptic Scales using Lidar and In Situ Observations from the ACT‐America Campaigns

et al. 2020

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With nearly 1 million observations of column-mean carbon dioxide concentration (X CO 2 ) per day, the Orbiting Carbon Observatory 2 (OCO-2) presents exciting possibilities for monitoring the global carbon cycle, including the detection of subcontinental column CO 2 variations. While the OCO-2 data set has been shown to achieve target precision and accuracy on a single-sounding level, the validation of X CO 2 spatial gradients on subcontinental scales remains challenging. In this work, we investigate the use of an integrated path differential absorption (IPDA) lidar for evaluation of OCO-2 observations via NASA's Atmospheric Carbon and Transport (ACT)-America project. The project has completed eight clear-sky underflights of OCO-2 with the Multifunctional Fiber Laser Lidar (MFLL)-along with a suite of in situ instruments-giving a precisely colocated, high-resolution validation data set spanning nearly 3,800 km across four seasons. We explore the challenges and opportunities involved in comparing the MFLL and OCO-2 X CO 2 data sets and evaluate their agreement on synoptic and local scales. We find that OCO-2 synoptic-scale gradients generally agree with those derived from the lidar, typically to ±0.1 ppm per degree latitude for gradients ranging in strength from 0 to 1 ppm per degree latitude. CO 2 reanalysis products also typically agree to ±0.25 ppm per degree when compared with an in situ-informed CO 2 "curtain." Real X CO 2 features at local scales, however, remain challenging to observe and validate from space, with correlation coefficients typically below 0.35 between OCO-2 and the MFLL. Even so, ACT-America data have helped investigate interesting local X CO 2 patterns and identify systematic spurious cloud-related features in the OCO-2 data set.

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Section: Instruments and Data Setsmentioning

confidence: 99%

Evaluation of OCO‐2 X Variability at Local and Synoptic Scales using Lidar and In Situ Observations from the ACT‐America Campaigns

et al. 2020

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“…The MFLL lidar (Dobbs et al, 2008;Dobler et al, 2013) was one of several flight instruments developed as a test bed for the CO 2 lidar to be used aboard NASA's proposed AS-CENDS satellite (Jucks et al, 2015;Kawa et al, 2018). We examine MFLL data from six OCO-2 underflights here, four taken over the Great Plains and two over the Mid-Atlantic (Table 1).…”

Section: Mfll Measurements and Their Pairing With Oco-2 Overflight Datamentioning

confidence: 99%

“…Several of these lidars were instrument test beds developed as part of NASA's Active Sensing of CO 2 Emissions over Nights, Days, and Seasons (ASCENDS) satellite project (Jucks et al, 2015;Kawa et al, 2018). One of these, the Multi-functional Fiber Laser Lidar (MFLL) (Dobbs et al, 2008;Dobler et al, 2013), has been flown (Campbell et al, 2020) as part of NASA's Atmospheric Carbon and Transport (ACT) -America project, an effort to detail CO 2 variability as a function of weather and front location across the eastern half of North America (Davis et al, 2021). Several of these MFLL flights were designed to pass underneath OCO-2 along its ground track as it passed by, allowing CO 2 from the better part of the full column to be compared between the two.…”

Section: Introductionmentioning

confidence: 99%

A new exponentially decaying error correlation model for assimilating OCO-2 column-average CO<sub>2</sub> data using a length scale computed from airborne lidar measurements

et al. 2022

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Abstract. To check the accuracy of column-average dry air CO2 mole fractions (XCO2) retrieved from Orbiting Carbon Observatory (OCO-2) data, a similar quantity has been measured from the Multi-functional Fiber Laser Lidar (MFLL) aboard aircraft flying underneath OCO-2 as part of the Atmospheric Carbon and Transport (ACT) – America flight campaigns. Here we do a lagged correlation analysis of these MFLL–OCO-2 column CO2 differences and find that their correlation spectrum falls off rapidly at along-track separation distances under 10 km, with a correlation length scale of about 10 km, and less rapidly at longer separation distances, with a correlation length scale of about 20 km. The OCO-2 satellite takes many CO2 measurements with small (∼3 km2) fields of view (FOVs) in a thin (<10 km wide) swath running parallel to its orbit: up to 24 separate FOVs may be obtained per second (across a ∼6.75 km distance on the ground), though clouds, aerosols, and other factors cause considerable data dropout. Errors in the CO2 retrieval method have long been thought to be correlated at these fine scales, and methods to account for these when assimilating these data into top-down atmospheric CO2 flux inversions have been developed. A common approach has been to average the data at coarser scales (e.g., in 10 s long bins) along-track, then assign an uncertainty to the averaged value that accounts for the error correlations. Here we outline the methods used up to now for computing these 10 s averages and their uncertainties, including the constant-correlation-with-distance error model that was used to summarize the OCO-2 version 9 XCO2 retrievals as part of the OCO-2 flux inversion model intercomparison project. We then derive a new one-dimensional error model using correlations that decay exponentially with separation distance, apply this model to the OCO-2 data using the correlation length scales derived from the MFLL–OCO-2 differences, and compare the results (for both the average and its uncertainty) to those given by the current constant correlation error model. To implement this new model, the data are averaged first across 2 s spans to collapse the cross-track distribution of the real data onto the 1-D path assumed by the new model. Considering correlated errors can cause the average value to fall outside the range of the values averaged; two strategies for preventing this are presented. The correlation lengths over the ocean, which the land-based MFLL data do not clarify, are assumed to be twice those over the land. The new correlation model gives 10 s XCO2 averages that are only a few tenths of 1 ppm different from the constant correlation model. Over land, the uncertainties in the mean are also similar, suggesting that the +0.3 constant correlation coefficient currently used in the model there is accurate. Over the oceans, the twice-the-land correlation lengths that we assume here result in a significantly lower uncertainty on the mean than the +0.6 constant correlation currently gives – measurements similar to the MFLL ones are needed over the oceans to do better. Finally, we show how our 1-D exponential error correlation model may be used to account for correlations in inversion methods that choose to assimilate each XCO2 retrieval individually and also to account for correlations between separate 10 s averages when these are assimilated instead.

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“…To enable maximum efficiency and reliability of these wind power generating systems, it is necessary to integrate complex real-time sensing systems to monitor the magnitude and direction of the kinetic energy to be harnessed [2,3,4] . LIDAR measurement techniques have shown significant potential and the design of sensing systems is rapidly evolving [4,5,6] .…”

Section: Introductionmentioning

confidence: 99%

Development of a high-speed wideband wavelength tunable infra-red laser source for real time wind turbine array sensing applications

Mitchell

Janssen

Poor

2011

Integrated Photonics: Materials, Devices, and Applications

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This paper reports the development of an infra-red circa 193THz (~1.5µm) frequency tunable laser source selected and evaluated for photonic environment sensing systems. LIDAR (LIght Detection And Ranging) offers a method of remote wind speed measurement. Widespread deployment of the technique has been limited by the expense and complexity of LIDAR systems. However development of systems based on optical fiber and photonic components from the telecommunications industry promises improvements in cost, compactness, and reliability, so that it becomes viable to consider deployment of such systems on large wind turbines for the advance detection of fluctuations of wind speed. A monolithic multi-section laser, originally designed as a tunable source for telecommunications applications, has been modified and re-evaluated as a source for sensing applications, based on the technique of coherent laser radar (CLR), and coherent doppler LIDAR (CDL). A tunable frequency optical source should fulfil specific technical criteria to fulfil the applications requirements; speed of frequency selection, absolute accuracy of emitted frequency, spectral purity, and stability. Custom electronics and firmware were developed to realise an improvement in frequency switching speed by a factor of 10 relative to equivalent commercially available telecoms (DBR) sources, satisfying the target application requirements. An overview of the sensing architecture is presented, a detailed description of the fast tuning process described, including the custom hardware and firmware, and specifically the laser energising sequence. The results of the laser module are then presented with detailed consideration of the target application.

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A Multi-Functional Fiber Laser Lidar for Earth Science & Exploration

Cited by 6 publications

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Evaluation of OCO‐2 X Variability at Local and Synoptic Scales using Lidar and In Situ Observations from the ACT‐America Campaigns

Evaluation of OCO‐2 X Variability at Local and Synoptic Scales using Lidar and In Situ Observations from the ACT‐America Campaigns

A new exponentially decaying error correlation model for assimilating OCO-2 column-average CO<sub>2</sub> data using a length scale computed from airborne lidar measurements

Development of a high-speed wideband wavelength tunable infra-red laser source for real time wind turbine array sensing applications

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A Multi-Functional Fiber Laser Lidar for Earth Science & Exploration

Cited by 6 publications

References 0 publications

Evaluation of OCO‐2 X Variability at Local and Synoptic Scales using Lidar and In Situ Observations from the ACT‐America Campaigns

Evaluation of OCO‐2 X Variability at Local and Synoptic Scales using Lidar and In Situ Observations from the ACT‐America Campaigns

A new exponentially decaying error correlation model for assimilating OCO-2 column-average CO&lt;sub&gt;2&lt;/sub&gt; data using a length scale computed from airborne lidar measurements

Development of a high-speed wideband wavelength tunable infra-red laser source for real time wind turbine array sensing applications

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A new exponentially decaying error correlation model for assimilating OCO-2 column-average CO<sub>2</sub> data using a length scale computed from airborne lidar measurements