Showing papers in "Earth and Space Science in 2019"

The GEDI simulator: A large-footprint waveform lidar simulator for calibration and validation of spaceborne missions

Abstract: NASA's Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar mission which will produce near global (51.6°S to 51.6°N) maps of forest structure and above‐ground biomass density during its 2‐year mission. GEDI uses a waveform simulator for calibration of algorithms and assessing mission accuracy. This paper implements a waveform simulator, using the method proposed in Blair and Hofton (1999; https://doi.org/10.1029/1999GL010484), and builds upon that work by adding instrument noise and by validating simulated waveforms across a range of forest types, airborne laser scanning (ALS) instruments, and survey configurations. The simulator was validated by comparing waveform metrics derived from simulated waveforms against those derived from observed large‐footprint, full‐waveform lidar data from NASA's airborne Land, Vegetation, and Ice Sensor (LVIS). The simulator was found to produce waveform metrics with a mean bias of less than 0.22 m and a root‐mean‐square error of less than 5.7 m, as long as the ALS data had sufficient pulse density. The minimum pulse density required depended upon the instrument. Measurement errors due to instrument noise predicted by the simulator were within 1.5 m of those from observed waveforms and 70–85% of variance in measurement error was explained. Changing the ALS survey configuration had no significant impact on simulated metrics, suggesting that the ALS pulse density is a sufficient metric of simulator accuracy across the range of conditions and instruments tested. These results give confidence in the use of the simulator for the pre‐launch calibration and performance assessment of the GEDI mission.

Ocean‐Scale Interactions From Space

Abstract: Satellite observations of the last two decades have led to a major breakthrough emphasizing the existence of a strongly energetic mesoscale turbulent eddy field in all the oceans. This ocean mesoscale turbulence is characterized by cyclonic and anticyclonic eddies (with a 100- to 300-km size and depth scales of similar to 500-1,000 m) that capture approximatively 80% of the total kinetic energy and is now known to significantly impact the large-scale ocean circulation, the ocean's carbon storage, the air-sea interactions, and therefore the Earth climate as a whole. However, ocean mesoscale turbulence revealed by satellite observations has properties that differ from those related to classical geostrophic turbulence theories. In the last decade, a large number of theoretical and numerical studies has pointed to submesoscale surface fronts (1-50 km), not resolved by satellite altimeters, as the key suspect explaining these discrepancies. Submesoscale surface fronts have been shown to impact mesoscale eddies and the large-scale ocean circulation in counterintuitive ways, leading in particular to up-gradient fluxes. The ocean engine is now known to involve energetic scale interactions, over a much broader range of scales than expected one decade ago, from 1 to 5,000 km. New space observations with higher spatial resolution are however needed to validate and improve these recent theoretical and numerical results.

PIRATA: A Sustained Observing System for Tropical Atlantic Climate Research and Forecasting

Abstract: Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) is a multinational program initiated in 1997 in the tropical Atlantic to improve our understanding and ability to predict ocean‐atmosphere variability. PIRATA consists of a network of moored buoys providing meteorological and oceanographic data transmitted in real time to address fundamental scientific questions as well as societal needs. The network is maintained through dedicated yearly cruises, which allow for extensive complementary shipboard measurements and provide platforms for deployment of other components of the Tropical Atlantic Observing System. This paper describes network enhancements, scientific accomplishments and successes obtained from the last 10 years of observations, and additional results enabled by cooperation with other national and international programs. Capacity building activities and the role of PIRATA in a future Tropical Atlantic Observing System that is presently being optimized are also described.

A Simple Method for Extracting Water Depth From Multispectral Satellite Imagery in Regions of Variable Bottom Type

Abstract: Satellite imagery offers an efficient and cost-effective means of estimating water depth in shallow environments. However, traditional empirical algorithms for calculating water depth often are unable to account for varying bottom reflectance, and therefore yield biased estimates for certain benthic environments. We present a simple method that is grounded in the physics of radiative transfer in seawater, but made more robust through the calibration of individual color-to-depth relationships for separate spectral classes. Our cluster-based regression (CBR) algorithm, applied to a portion of the Great Bahama Bank, drastically reduces the geographic structure in the residual and has a mean absolute error of 0.19 m with quantified uncertainties. Our CBR bathymetry is 3-5x more accurate than existing models and outperforms machine learning protocols at extrapolating beyond the calibration data. Finally, we demonstrate how comparison of CBR with traditional models sensitive to bottom type reveals the characteristic length scales of biosedimentary facies belts. Keypoints: • We use satellite imagery to estimate water depth on the Great Bahama Bank with 0.2 m accuracy • Our algorithm is more robust to variable bottom types than the widelyused linear and ratio methods • Our physics-based method outperforms SVM in cases of limited calibration data coverage c ©2019 American Geophysical Union. All Rights Reserved.

Lunar Science for Landed Missions Workshop Findings Report

Abstract: The Lunar Science for Landed Missions workshop was convened at the National Aeronautics and Space Administration Ames Research Center on 10–12 January, 2018. Interest in the workshop was broad, with 110 people participating in person and 70 people joining online. In addition, the workshop website (https://lunar‐landing.arc.nasa.gov) includes video recordings of many of the presentations. This workshop defined a set of targets that near‐term landed missions could visit for scientific exploration. The scope of such missions was aimed primarily, but not exclusively, at commercial exploration companies with interests in pursuing ventures on the surface of theMoon. Contributed and invited talks were presented that detailed many high priority landing site options across the surface of the Moon that would meet scientific goals in a wide variety of areas, including impact cratering processes and dating, volatiles, volcanism,magnetism, geophysics, and astrophysics. Representatives from the Japan Aerospace Exploration Agency and the European Space Agency also presented about international plans for lunar exploration and science. This report summarizes the set of landing sites and/or investigations that were presented at the workshop that would address high priority science and exploration questions. In addition to landing site discussions, technology developments were also specified that were considered as enhancing to the types of investigations presented. It is evident that the Moon is rich in scientific exploration targets that will inform us on the origin and evolution of the Earth‐Moon system and the history of the inner Solar System, and also has enormous potential for enabling human exploration and for the development of a vibrant lunar commercial sector. Plain Language Summary Where should we explore next on the Moon? This report summarizes potential future landing sites on the surface of the Moon, as presented at the Lunar Science for Landed Missions Workshop in January 2018 at NASA Ames.

Power Law Size Distributions in Geoscience Revisited

Abstract: The size or energy of diverse structures or phenomena in geoscience appears to follow power-law distributions. A rigorous statistical analysis of such observations is tricky, though. Observables can span several orders of magnitude, but the range for which the power law may be valid is typically truncated, usually because the smallest events are too tiny to be detected and the largest ones are limited by the system size. We revisit several examples of proposed power-law distributions dealing with potentially damaging natural phenomena. Adequate fits of the distributions of sizes are especially important in these cases, given that they may be used to assess long-term hazard. After reviewing the theoretical background for power-law distributions, we improve an objective statistical fitting method and apply it to diverse data sets. The method is described in full detail and it is easy to implement. Our analysis elucidates the range of validity of the power-law fit and the corresponding exponent, and whether a power-law tail is improved by a truncated log-normal. We confirm that impact fireballs and Californian earthquakes show untruncated power-law behavior, whereas global earthquakes follow a double power law. Rain precipitation over space and time and tropical cyclones show a truncated power-law regime. Karst sinkholes and wildfires, in contrast, are better described by truncated log-normals, although wildfires also may show power-law regimes. Our conclusions only apply to the analyzed data sets, but show the potential of applying this robust statistical technique in the future.

Global Seismic Nowcasting With Shannon Information Entropy.

Abstract: Seismic nowcasting uses counts of small earthquakes as proxy data to estimate the current dynamical state of an earthquake fault system. The result is an earthquake potential score that characterizes the current state of progress of a defined geographic region through its nominal earthquake "cycle." The count of small earthquakes since the last large earthquake is the natural time that has elapsed since the last large earthquake (Varotsos et al., 2006, https://doi.org/10.1103/PhysRevE.74.021123). In addition to natural time, earthquake sequences can also be analyzed using Shannon information entropy ("information"), an idea that was pioneered by Shannon (1948, https://doi.org/10.1002/j.1538-7305.1948.tb01338.x). As a first step to add seismic information entropy into the nowcasting method, we incorporate magnitude information into the natural time counts by using event self-information. We find in this first application of seismic information entropy that the earthquake potential score values are similar to the values using only natural time. However, other characteristics of earthquake sequences, including the interevent time intervals, or the departure of higher magnitude events from the magnitude-frequency scaling line, may contain additional information.

Helicity Dynamics, Inverse, and Bidirectional Cascades in Fluid and Magnetohydrodynamic Turbulence: A Brief Review

Abstract: We briefly review helicity dynamics, inverse and bidirectional cascades in fluid and magnetohydrodynamic (MHD) turbulence, with an emphasis on the latter. The energy of a turbulent system, an invariant in the nondissipative case, is transferred to small scales through nonlinear mode coupling. Fifty years ago, it was realized that, for a two-dimensional fluid, energy cascades instead to larger scales and so does magnetic excitation in MHD. However, evidence obtained recently indicates that, in fact, for a range of governing parameters, there are systems for which their ideal invariants can be transferred, with constant fluxes, to both the large scales and the small scales, as for MHD or rotating stratified flows, in the latter case including quasi-geostrophic forcing. Such bidirectional, split, cascades directly affect the rate at which mixing and dissipation occur in these flows in which nonlinear eddies interact with fast waves with anisotropic dispersion laws, due, for example, to imposed rotation, stratification, or uniform magnetic fields. The directions of cascades can be obtained in some cases through the use of phenomenological arguments, one of which we derive here following classical lines in the case of the inverse magnetic helicity cascade in electron MHD. With more highly resolved data sets stemming from large laboratory experiments, high-performance computing, and in situ satellite observations, machine learning tools are bringing novel perspectives to turbulence research. Such algorithms help devise new explicit subgrid-scale parameterizations, which in turn may lead to enhanced physical insight, including in the future in the case of these new bidirectional cascades. Plain Language Summary Turbulent flows are prevalent in Geophysics and Space Physics. They are complex and involve interactions between fluctuations at widely separated scales, with the energy expected in the general case to flow only to small scales where it is dissipated. It was found recently that, contrary to such expectations, energy can go in substantial amounts to both the small and large scales, in the presence of magnetic fields, as applicable to space plasmas, and for rotating stratified flows as encountered in the atmosphere and the oceans. This result implies that the amount of energy available for dissipation may differ from flow to flow, and simple scaling arguments allow for predictions that are backed up by results stemming from direct numerical simulations. One should incorporate this bidirectional cascade phenomenon in the turbulence models used for global computations of geophysical and astrophysical media. Furthermore, machine learning tools may prove useful in deriving such enhanced models in their capacity to interrogate the large data bases that already exist for such complex flows.

Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia

Abstract: Surface wind is significant for ocean state climate, ocean mixing, and viability of wind energy techniques. However, surface wind simulated from the regional climate model generally features substantial bias from observation. For the first time, this study compares the performance of five bias correction techniques, (1) linear scaling, (2) variance scaling, (3) quantile mapping based on empirical distribution, (4) quantile mapping based on Weibull distribution, and (5) cumulative distribution functions transformation, in reducing the statistical bias of a regional climate model wind output, which was downscaled from a global climate model CNRM-CM5 during 1991-2000. The surface wind of JRA55 reanalysis data is used as reference. Results show that all bias correction methods are consistent in reducing the climatological mean bias in spatial patterns and intensities. The linear scaling method always performs the worst among all methods in correcting higher-order statistical biases such as skewness, kurtosis, and wind power density. The other four bias correction methods are generally similar in reducing the statistical biases of different measures based on spatial distribution maps. However, when it comes to spatial averaged mean of statistical measures over CORDEX-East Asia in January and July, the quantile mapping based on Weibull distribution generally shows the best skills among all methods in bias reduction. Plain Language Summary In the current stage, global climate model or regional climate model simulations generally feature substantial bias relative to observations, leading to an inaccurate assessment of climate change or inaccurate inputs for impact models. For the first time, we have compared five bias correction methods using various statistical measures to find out the most robust method for correcting statistical properties of simulated winds from regional climate model. Results show that the linear scaling method always performs the worst among all methods in correcting higher-order statistical biases of simulated winds. On average, the quantile mapping based on Weibull distribution shows the best skills among all methods in bias reduction in January and July. This study is of importance for climate change assessment of wind as well as deriving accurate wind forcing for driving ocean model.

Predictability of Weather and Climate.

Abstract: The past developments in the predictability of weather and climate are discussed from the point of view of nonlinear dynamical systems. The problems ahead for long-range predictability extending into the climate time scale are also presented. The sensitive dependence of chaos on initial conditions and the imperfections in the models limit reliable predictability of the instantaneous state of the weather to less than 10 days in present-day operational forecasts. The existence of slowly varying components such as the sea surface temperature, soil moisture, snow cover, and sea ice may provide basis for predicting certain aspects of climate at long range. The regularly varying nonlinear oscillations, such as the Madden-Julian Oscillation, monsoon intraseasonal oscillations, and El Nino-Southern Oscillation, are also possible sources of extended-range predictability at the climate time scale. A prediction model based on phase space reconstruction has demonstrated that monsoon intraseasonal oscillation can be better predicted at long leads.

A Global Survey on the Perceptions and Impacts of Gender Inequality in the Earth and Space Sciences

Abstract: The leaky pipeline phenomenon refers to the disproportionate decline of female scientists at higher academic career levels and is a major problem in the natural sciences. Identifying the underlying causes is challenging, and thus, solving the problem remains difficult. To better understand the reasons for the leaky pipeline, we assess the perceptions and impacts of gender bias and imbalance—two major drivers of the leakage—at different academic career levels with an anonymous survey in geoscience academia (n=1,220). The survey results show that both genders view male geoscientists as substantially more gender biased than female scientists. Moreover, female geoscientists are more than twice as likely to experience negative gender bias at their workplaces and scientific organizations compared to male geoscientists. There are also pronounced gender differences regarding (i) the relevance of role models, (ii) family-friendly working conditions, and (iii) the approval of gender quotas for academic positions. Given the male dominance in senior career levels, our results emphasize that those feeling less impacted by the negative consequences of gender bias and imbalance are the ones in position to tackle the problem. We thus call for actions to better address gender biases and to ensure a balanced gender representation at decision-making levels to ultimately retain more women in geoscience academia.

Role of Ammonia on the Feedback Between AWC and Inorganic Aerosol Formation During Heavy Pollution in the North China Plain

Abstract: Atmospheric NH3 plays a vital role not only in the environmental ecosystem but also in atmosphere chemistry. To further understand the effects of NH3 on the formation of haze pollution in Beijing, ambient NH3 and related species were measured and simulated at high resolutions during the wintertime Air Pollution and Human Health-Beijing (APHH-Beijing) campaign in 2016. We found that the total NHx (gaseous NH3+particle NH4 +) was mostly in excess of the SO4 2−-NO3 −-NH4 +-water equilibrium system during our campaign. This NHx excess made medium aerosol acidity, with the median pH value being 3.6 and 4.5 for polluted and nonpolluted conditions, respectively, and enhanced the formation of particle phase nitrate. Our analysis suggests that NH4NO3 is the most important factor driving the increasing of aerosol water content with NO3 − controlling the prior pollution stage and NH4 + the most polluted stage. Increased formation of NH4NO3 under excess NHx, especially during the nighttime, may trigger the decreasing of aerosol deliquescence relative humidity even down to less than 50% and hence lead to hygroscopic growth even under RH conditions lower than 50% and the wet aerosol particles become better medium for rapid heterogeneous reactions. A further increase of RH promotes the positive feedback “aerosol water content-heterogeneous reactions” and ultimately leads to the formation of severe haze. Modeling results by Nested Air Quality Prediction Monitor System (NAQPMS) show the control of 20% NH3 emission may affect 5–11% of particulate matter PM2.5 formation under current emissions conditions in the North China Plain.

Evaluation of Satellite and Reanalysis Precipitable Water Vapor Data Sets Against Radiosonde Observations in Central Asia

Abstract: Central Asia is facing severe water shortages and conflicts. The spatiotemporal variations of precipitable water vapor (PWV) are important aspects in understanding the water cycle and water resources. However, station observations in central Asia are limited and the performance of satellite and reanalysis products of PWV in central Asia has not been evaluated. Based on radiosonde observations, we show evidence that the two satellite products, namely, Atmospheric Infrared Sounder‐only and Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit, are applicable to investigate the spatiotemporal characteristics of PWV in central Asia. The two satellite products can capture the main climatological features, annual cycle, and monthly variations of PWV in central Asia, with high correlations with radiosonde observations, although slightly underestimate PWV values by −15% to 0%. All the eight current state‐of‐the‐art reanalysis data sets, including European Centre for Medium‐Range Weather Forecasts (ECMWF) interim reanalysis, the fifth generation ECMWF atmospheric reanalysis (ERA5), National Centers for Environmental Prediction (NCEP)1, NCEP2, Climate Forecast System Reanalysis, 55‐year modern Japanese Reanalysis Project, Modern Era Retrospective‐Analysis for Research and Applications (MERRA), and MERRA version 2 (MERRA2), can reasonably reproduce the spatiotemporal variations of PWV, although with an overestimation in spring, autumn, and winter and an underestimation in summer. ERA5 andMERRA2 (NCEP1 and NCEP2) perform better (poorer) compared with other reanalysis data sets. A skill‐weighted ensemble mean of reanalysis data sets is constructed based on the different performance of individual data sets. It is better for understanding the climatological spatial pattern than the equally weighted ensemble mean and individual reanalysis data sets, while ERA5 is suggested to be used for revealing the interannual variations of PWV in central Asia.

Assessment of the Representation of West African Storm Lifecycles in Convection-Permitting Simulations

Abstract: Convection‐permitting models perform better at representing the diurnal cycle and the intermittency of convective rainfall over land than parameterized‐convection models. However, most of the previous model assessments have been from an Eulerian point of view, while key impacts of the rainfall depend on a storm‐relative perspective of the system lifecycle. Here a storm‐tracking algorithm is used to generate storm‐centered Lagrangian lifecycle statistics of precipitation over West Africa from regional climate model simulations and observations. Two versions of the Met Office Unified Model with and without convection parameterization at 4, 12, and 25 km resolution were analyzed. In both of the parameterized‐convection simulations, storm lifetimes are too short compared to observations, and storms have no preferred propagation direction; the diurnal cycle of initiations and dissipations and the spatial distribution of storms are also inaccurate. The storms in the convection‐permitting simulations have more realistic diurnal cycles and lifetimes, but are not as large as the largest observed storms. The convection‐permitting model storms propagate in the correct direction, although not as fast as observed storms, and they have a much improved spatial distribution. The rainfall rate of convection‐permitting storms is likely too intense compared to observations. The improved representation of the statistics of organized convective lifecycles shows that convection‐permitting models provide better simulation of a number of aspects of high‐impact weather which are critical to climate impacts in this important geographic region, providing the high rainfall rates can be taken into account.

Venus Atmospheric Composition In Situ Data: A Compilation

Abstract: The Venus atmosphere is of significant interest yet only rudimentary solid data has been gathered about its composition and chemistry. These measurements are scattered through time and place and are limited by parameters such as resolution and error margins as well as reinterpretations. This paper presents an extensive compilation of published in situ data for the atmospheric composition of Venus. It also includes remotely gathered measurements and some extrapolated and modeled data for the lower atmosphere. The composition tables are divided in four categories: noble gases, reactive gases, noble and non-noble isotopes. These tables were first presented in 2016 within the scientific heritage appendix of the Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission proposal. These tables provide respective measurements, error margins, techniques, altitudes, instruments, mission and references. The objective of this paper is to provide a simple, comprehensive list of available measurements to date; in particular, the in situ data, to serve as a quick overall Venus atmosphere data reference.

Observing Mesospheric Turbulence With Specular Meteor Radars: A Novel Method for Estimating Second-Order Statistics of Wind Velocity

Abstract: J. Vierinen would like to thank the Tromso Science Foundation for supporting this work. This work was partially supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under SPP 1788 (CoSIP)‐CH1482/3‐1, and by the WATILA Project (SAW‐2015‐IAP‐1). The authors gratefully acknowledge the support of the international team by the International Space Science Institute (Bern, Switzerland) and discussions within the ISSI Team 410. Some hardware, software, and analysis work at MIT Haystack Observatory was supported by NSF Major Research Infrastructure Grant AGS‐1626041. We also thank Rudiger Lange (Salzwedel), Fred and Claudia Bauske (Mechelsdorf), Frank Schutz (Gulderup), Dieter Keuer (Breege), and the IAP personnel T. Barth, F. Conte, N. Gudadze, R. Latteck, N. Pfeffer, and J. Trautner for supporting the operations of the MIMO‐CW links, and F. J. Lubken for useful comments during early drafts of this work.

Weak-Turbulent Theory of Wind-Driven Sea

Abstract: Physical oceanography collected a huge amount of experimental data on the wind-driven sea. These data include frequency and angular-frequency spectra of surface elevation as well as spatial spectra measured from planes and satellites. A lot of collected data present fetch and duration dependance of such sea integral characteristics as energy † = and the peak frequency !p. This variety of experimental data can be essentially reduced by the use of Kitaigorodskii similarity conjecture [1], stating that the major features of wind-driven sea can be expressed in terms of dimensionless variables (here U is wind velocity): ” = !pU g ; e = †g 2 U 4 ; ´ = xg U 2 : Experiments show that e;” are powerlike functions on the dimensionless fetch ´: