Forecast Bias Correction: A Second Order Method

The difference between a model forecast and actual observations is called forecast bias. This bias is due to either incomplete model assumptions and/or poorly known parameter values and initial/boundary conditions. In this paper we discuss a method for estimating corrections to parameters and initial conditions that would account for the forecast bias. A set of simple experiments with the logistic ordinary differential equation is performed using an iterative version of a first order version of our method to compare with the second order version of the method.Comment: 27 Pages, 3 figures, 8 table

Estimation of Near Surface Tornadic Wind Speeds

Modeling studies consistently demonstrate that the most violent winds in a tornadic vortex occur in the lowest tens of meters above the surface. These velocities are unobservable by radar platforms due to line of sight considerations. In this work, a methodology is developed which utilizes parametric tangential velocity models derived from Doppler radar measurements, together with a tangential momentum and mass continuity constraint, to estimate the radial and vertical velocities in a steady axisymmetric frame. This technique is tested with a set of model output utilized as "truth". The methodology yields good estimates when the tangential vortex model is a good approximation to the actual tangential wind field, in the regions that are retrievable from the information aloft. Interestingly, there are regions of the unobservable portion of the domain that do not communicate with the region above through the dynamics we have selected. These regions are explored, and different variational procedures for estimating solutions on these regions are discussed. A probabilistic method is utilized to quantify how uncertainty in the vortex model parameters translates into the retrieved radial and vertical velocities, and the resulting improvement in estimations using ensemble statistics is discussed

On the ability of space-based passive and active remote sensing observations of CO2 to detect flux perturbations to the carbon cycle

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Atmospheres 123 (2018): 1460–1477, doi:10.1002/2017JD027836.Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT and OCO-2, however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint.NASA Grant Numbers: NNX15AJ27G, NNX15AH13G2018-07-2

Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS): Final Report of the ASCENDS Ad Hoc Science Definition Team

Improved remote sensing observations of atmospheric carbon dioxide (CO2) are critically needed to quantify, monitor, and understand the Earth's carbon cycle and its evolution in a changing climate. The processes governing ocean and terrestrial carbon uptake remain poorly understood,especially in dynamic regions with large carbon stocks and strong vulnerability to climate change,for example, the tropical land biosphere, the northern hemisphere high latitudes, and the Southern Ocean. Because the passive spectrometers used by GOSAT (Greenhouse gases Observing SATellite) and OCO-2 (Orbiting Carbon Observatory-2) require sunlit and cloud-free conditions,current observations over these regions remain infrequent and are subject to biases. These short comings limit our ability to understand and predict the processes controlling the carbon cycle on regional to global scales.In contrast, active CO2 remote-sensing techniques allow accurate measurements to be taken day and night, over ocean and land surfaces, in the presence of thin or scattered clouds, and at all times of year. Because of these benefits, the National Research Council recommended the National Aeronautics and Space Administration (NASA) Active Sensing of CO2 Emissions over Nights,Days, and Seasons (ASCENDS) mission in the 2007 report Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. The ability of ASCENDS to collect low-bias observations in these key regions is expected to address important gaps in our knowledge of the contemporary carbon cycle.The ASCENDS ad hoc Science Definition Team (SDT), comprised of carbon cycle modeling and active remote sensing instrument teams throughout the United States (US), worked to develop the mission's requirements and advance its readiness from 2008 through 2018. Numerous scientific investigations were carried out to identify the benefit and feasibility of active CO2 remote sensing measurements for improving our understanding of CO2 sources and sinks. This report summarizes their findings and recommendations based on mission modeling studies, analysis of ancillary meteorological data products, development and demonstration of candidate technologies, anddesign studies of the ASCENDS mission concept

Near-infrared Spectral Characterization of Solar-type Stars in the Northern Hemisphere

Although solar-analog stars have been studied extensively over the past few decades, most of these studies have focused on visible wavelengths, especially those identifying solar-analog stars to be used as calibration tools for observations. As a result, there is a dearth of well-characterized solar analogs for observations in the near-infrared, a wavelength range important for studying solar system objects. We present 184 stars selected based on solar-like spectral type and V-J and V-K colors whose spectra we have observed in the 0.8-4.2 micron range for calibrating our asteroid observations. Each star has been classified into one of three ranks based on spectral resemblance to vetted solar analogs. Of our set of 184 stars, we report 145 as reliable solar-analog stars, 21 as solar analogs usable after spectral corrections with low-order polynomial fitting, and 18 as unsuitable for use as calibration standards owing to spectral shape, variability, or features at low to medium resolution. We conclude that all but 5 of our candidates are reliable solar analogs in the longer wavelength range from 2.5 to 4.2 microns. The average colors of the stars classified as reliable or usable solar analogs are V-J=1.148, V-H=1.418, and V-K=1.491, with the entire set being distributed fairly uniformly in R.A. across the sky between -27 and +67 degrees in decl.Comment: 19 pages, 8 figures, 2 table

An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake?

On October 19, 2020, the Mw7.6 Sand Point earthquake struck south of the Shumagin Islands in Alaska. Moment tensors indicate the earthquake was primarily strike-slip, yet the event produced an enigmatic tsunami that was larger and more widespread than expected for an earthquake of that magnitude and mechanism. Using a suite of hydrodynamic, seismic, and geodetic modeling techniques, we explore plausible causes of the tsunami. We find that strike-slip models consistent with the moment tensor orientation cannot produce the observed tsunami. Hydrodynamic inversion of sea surface deformation from deep ocean and tide gauge data suggest seafloor deformation more closely matches a megathrust, rather than a strike-slip, source. Static slip inversions, using sea level and Global Navigation Satellite System data, allow for a portion of co-seismic megathrust slip that can explain tsunamigenesis. Combining all available geophysical datasets to model the kinematic rupture, we show that considerable, relatively slow, megathrust slip is allowable in the Shumagin segment, concurrent with strike-slip faulting. We hypothesize that the slow megathrust rupture does not contribute much seismic radiation allowing it to previously go unnoticed with traditional seismic monitoring

The Potential of the Geostationary Carbon Cycle Observatory (GeoCarb) to Provide Multi-scale Constraints on the Carbon Cycle in the Americas

The second NASA Earth Venture Mission, Geostationary Carbon Cycle Observatory (GeoCarb), will provide measurements of atmospheric carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and solar-induced fluorescence (SIF) from Geostationary Orbit (GEO). The GeoCarb mission will deliver daily maps of column concentrations of CO2, CH4, and CO over the observed landmasses in the Americas at a spatial resolution of roughly 10 × 10 km. Persistent measurements of CO2, CH4, CO, and SIF will contribute significantly to resolving carbon emissions and illuminating biotic processes at urban to continental scales, which will allow the improvement of modeled biogeochemical processes in Earth System Models as well as monitor the response of the biosphere to disturbance. This is essential to improve understanding of the Carbon-Climate connection. In this paper, we introduce the instrument and the GeoCarb Mission, and we demonstrate the potential scientific contribution of the mission through a series of CO2 and CH4 simulation experiments. We find that GeoCarb will be able to constrain emissions at urban to continental spatial scales on weekly to annual time scales. The GeoCarb mission particularly builds upon the Orbiting Carbon Obserevatory-2 (OCO-2), which is flying in Low Earth Orbit

National CO\u3csub\u3e2\u3c/sub\u3e budgets (2015-2020) inferred from atmospheric CO\u3csub\u3e2\u3c/sub\u3e observations in support of the global stocktake

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries\u27 carbon budgets. These estimates are based on top-down NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-Averaged dry-Air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with bottom-up estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015-2020) as both a global 1gg×g1g gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites\u27 (CEOS) website: 10.48588/npf6-sw92 . Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29-4.58gPgCO2yr-1 (0.90-1.25gPgCyr-1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems