Laboratory for Atmospheres 2008 Technical Highlights

The 2008 Technical Highlights describes the efforts of all members of the Laboratory for Atmospheres. Their dedication to advancing Earth Science through conducting research, developing and running models, designing instruments, managing projects, running field campaigns, and numerous other activities, is highlighted in this report. The Laboratory for Atmospheres (Code 613) is part of the Earth Sciences Division (Code 610), formerly the Earth Sun Exploration Division, under the Sciences and Exploration Directorate (Code 600) based at NASA s Goddard Space Flight Center in Greenbelt, Maryland. In line with NASA s Exploration Initiative, the Laboratory executes a comprehensive research and technology development program dedicated to advancing knowledge and understanding of the atmospheres of Earth and other planets. The research program is aimed at understanding the influence of solar variability on the Earth s climate; predicting the weather and climate of Earth; understanding the structure, dynamics, and radiative properties of precipitation, clouds, and aerosols; understanding atmospheric chemistry, especially the role of natural and anthropogenic trace species on the ozone balance in the stratosphere and the troposphere; and advancing our understanding of physical properties of Earth s atmosphere. The research program identifies problems and requirements for atmospheric observations via satellite missions. Laboratory scientists conceive, design, develop, and implement ultraviolet, infrared, optical, radar, laser, and lidar technology for remote sensing of the atmosphere. Laboratory members conduct field measurements for satellite data calibration and validation, and carry out numerous modeling activities. These modeling activities include climate model simulations, modeling the chemistry and transport of trace species on regional-to-global scales, cloud-resolving models, and development of next-generation Earth system models. Interdisciplinary research is carried out in collaboration with other laboratories and research groups within the Earth Sciences Division, across the Sciences and Exploration Directorate, and with partners in universities and other Government agencies. The Laboratory for Atmospheres is a vital participant in NASA s research agenda. Our Laboratory often has relatively large programs, sizable satellite missions, and observational campaigns that require the cooperative and collaborative efforts of many scientists. We ensure an appropriate balance between our scientists responsibility for these large collaborative projects and their need for an active individual research agenda. This balance allows members of the Laboratory to continuously improve their scientific credentials. Members of the Laboratory interact with the general public to support a wide range of interests in the atmospheric sciences. Among other activities, the Laboratory raises the public s awareness of atmospheric science by presenting public lectures and demonstrations, by making scientific data available to wide audiences, by teaching, and by mentoring students and teachers. The Laboratory makes substantial efforts to attract new scientists to the various areas of atmospheric research. We strongly encourage the establishment of partnerships with Federal and state agencies that have operational responsibilities to promote the societal application of our science products. This report describes our role in NASA s mission, gives a broad description of our research, and summarizes our scientists major accomplishments during calendar year 2008. The report also contains useful information on human resources, scientific interactions, and outreach activities

Concept design, analysis, and Integration of the new U.P.C. multispectral lidar system

The increasing need for range-resolved aerosol and water-vapour atmospheric observation networks worldwide has given rise to multi-spectral LIDARs (Light Detection and Ranging, a synonym of laser radar) as advanced remote sensing sensors. This Ph.D. presents the design, integration and analysis of the new 6-channel multispectral elastic/Raman LIDAR for aerosol and water-vapour content monitoring developed at the Remote Sensing Lab. (RSLAB) of the Universitat Polit ecnica de Catalunya (UPC). It is well known that the combination of at least three elastic and two Raman nitrogen channels are su cient to enable retrieval of the optical and microphysical properties of aerosols with a key impact on climate change variables. The UPC lidar is part of the EARLINET (European Aerosol Research Lidar Network) -GALION (Global Atmospheric Watch Atmospheric Lidar Observation Network), a ground-based continental network including more than 28 stations. Currently, only 8 of the 28 EARLINET stations are of such advanced type. This Ph.D. speci cally focuses on: (1) Concept link-budget instrument design and overlap factor assessment. The former includes opto-atmospheric parameter modelling and assessment of backscattered power and SNR levels, and maximum system range for the di erent reception channels (3 elastic, and 2 aerosol and 1 water-vapour Raman channels, ultraviolet to near-infrared bands). The latter studies the laser-telescope crossover function (or overlap function) by means of a novel raytracing Gaussian model. The problem of overlap function computation and its near-range sensitivity for medium size aperture (f=10, f=11) bi-axial tropospheric lidar systems using both detector and ber-optics coupling alternatives at the telescope focal-plane is analysed using this new ray-tracing approach, which provides a much simpler solution than analyticalbased methods. Sensitivity to laser divergence, eld-lens and detector/ ber positions, and ber's numerical aperture is considered. (2) Design and opto-mechanical implementation of the 6-channel polychromator (i.e., the spectrally selective unit in reception). Design trade-o s concerning light collimation, end-to-end transmissivity, net channel responsivity, and homogeneous spatial light distribution onto the detectors' active area discussed. (3) System integration and validation. This third part is two fold: On one hand, fi rst-order backscatter-coe cient error bounds (a level-1 data product) for the two-component elastic lidar inversion algorithm are estimated for both random (observation noise) and systematic error sources (user's uncertainty in the backscatter-coe cient calibration, and user's uncertainty in the aerosol extinction-to-backscatter lidar ratio). On the other hand, the multispectral lidar so far integrated is described at both hardware and control software level. Statistical validation results for the new UPC lidar (today in routine operation) in the framework of SPALI-2010 intercomparison campaign are presented as part of EARLINET quality assurance / optimisation of instruments' program. The methodology developed in the rst part of this Ph.D. has successfully been applied to the speci cation case study of the IFAE/UAB lidar system, which will be installed and operated at the Cherenkov Telescope Array (CTA) observatory. Finally, specs for automated unmanned unattended lidar operation with service times close to 365/24 are presented at the end of this Ph.D. in response to the increasing demand for larger observation times and availability periods of lidar stations

Lidar and S-band radar profiling of the atmosphere : adaptive processing for boundary-layer monitoring, optical-parameter error estimation, and application cases

This Ph.D. thesis addresses remote sensing of the atmosphere by means of lidar and S-band clear-air weather radar, and related data signal processing. Active remote sensing by means of these instruments offers unprecedented capabilities of spatial and temporal resolutions for vertical atmospheric profiling and the retrieval of key optical and physical atmospheric products in an increasing environmental regulatory framework. The first goal is this Ph.D. concerns the estimation of error bounds in the inversion of the profile of the atmospheric backscatter coefficient from elastic lidar signals (i.e., without wavelength shift in reception when interacting with atmospheric scatterers) by means of the two-component inversion algorithm (the so-called Klett-Fernald-Sasano¿s algorithm). This objective departs from previous works at the Remote Sensing Lab. (RSLab) of the Universitat Politècnica de Catalunya (UPC) and derives first-order error-propagated bounds (approximate) and total-increment bounds (exact). As distinctive feature in the state of the art, the error bounds merge into a single body both systematic (i.e., user-calibration inputs) and random error sources (finite signal-to-noise ratio, SNR) yielding an explicit mathematical form. The second goal, central to this Ph.D., tackles retrieval of the Atmospheric Boundary Layer Height (ABLH) from elastic lidar and S-band Frequency-Modulated Continuous-Wave (FMCW) radar observations by using adaptive techniques based on the Extended Kalman Filter (EKF). The filter is based on morphological modelling of the Mixing-Layer-to-Free-Troposphere transition and continuous estimation of the noise covariance information. In the lidar-EKF realization the proposed technique is shown to outperform classic ABLH estimators such as those based on derivative techniques, thresholded decision, or the variance centroid method. The EKF formulation is applied to both ceilometer and UPC lidar records in high- and low-SNR scenes. The lidar-EKF approach is re-formulated and successfully extended to S-band radar scenes (Bragg¿s scattering) in presence of interferent noise sources (Rayleigh scattering from e.g., insects and birds). In this context, the FMCW feature enables the range-resolved capability. EKF-lidar and EKF-radar ABLH estimates are cross-examined from field campaign results. Finally, the third goal deals with exploitation of the existing UPC lidar station: In a first introductory part, a modified algorithm for enhancing the dynamic range of elastic lidar channels by ¿gluing¿ analog and photon-counting data records is formulated. In a second part, two case examples (including application of the gluing algorithm) are presented to illustrate the capabilities of the UPC lidar in networked atmospheric observation of two recent volcano eruption events as part of the EARLINET (European Aerosol Research Lidar Network). The latter is part of GALION (Global Atmospheric Watch Atmospheric Lidar Observation Network)-GEOSS (Global Earth Observation System of Systems) framework.La tesis doctoral aborda la teledetecció atmosfèrica amb tècniques lidar i radar (banda S) i llur tractament del senyal. La teledetecció activa amb aquests instruments ofereix resolucions espacials i temporals sense precedents en la perfilometria vertical de l'atmosfera i recuperació de productes de dades òptics i físics atmosfèrics en un marc de creixent regulació mediambiental. El primer objectiu d'aquesta tesi concerneix l'estimació de cotes d'error en la inversió del perfil del coeficient de retrodispersió atmosfèrica a partir de senyals lidar de tipus elàstic (és a dir, sense desplaçament de la longitud d'ona en recepció al interactuar amb els dispersors atmosfèrics) mitjançant l'algorisme d'inversió de dues components de Klett-Fernald-Sasano. Aquest objectiu parteix de treballs previs en el Remote Sensing Lab. (RSLab) de la Universitat Politècnica de Catalunya (UPC) i permet obtenir cotes de primer ordre (aproximades) basades en propagació d'errors i cotes (exactes) basades en el increment total de l'error. Característica diferencial en front l'estat de l'art és l'assimilació d'errors sistemàtics (per exemple, entrades de cal.libració d'usuari) i aleatoris (relació senyal-soroll, SNR, finita) en forma matemàtica explícita. El segon objectiu, central de la tesis, aborda l'estimació de l'altura de la capa límit atmosfèrica (ABLH) a partir de senyal lidar elàstics i d'observacions radar en banda S (ona continua amb modulació en freqüència, FMCW) utilitzant tècniques adaptatives basades en filtrat estès de Kalman (EKF). El filtre es basa en modelat morfològic de la transició atmosfèrica entre la capa de mescla i la troposfera lliure i en l'estimació continua de la informació de covariança del soroll. En el prototipus lidar-EKF la tècnica proposada millora clarament les tècniques clàssiques d'estimació de la ABLH como són les basades en mètodes derivatius, decisió de llindar, o el mètode de la variança-centroide. La formulació EKF s'aplica tant a mesures procedents de ceilòmetres lidar como de la pròpia estació lidar UPC en escenes d'alta i baixa SNR. Addicionalment, l'enfoc lidar-EKF es reformula i s'estén amb èxit a escenes radar en banda S (dispersió Bragg) en presència de fonts de soroll interferent (dispersió Rayleigh de, per exemple, insectes i ocells). En aquest context, la característica FMCW permet la capacitat de resolució en distància. L'estimació de la ABLH amb els prototipus lidar-EKF i radar-EKF s'intercompara en campanyes de mesura. Finalment, el tercer objectiu atén a l'explotació de l'estació lidar UPC existent: En una primera part introductòria, es formula un algorisme modificat de "gluing" per a la millora del marge dinàmic de canals lidar elàstics mitjançant combinació (o "enganxat") de senyals lidar adquirits analògicament i amb foto-comptatge. En una segona part, es presenten dos exemples (incloent l'aplicació de l'algorisme de "gluing") que il.lustren les capacitats del lidar de la UPC en l'observació atmosfèrica de dos recents erupcions volcàniques des de la xarxa d'observació EARLINET (European Aerosol Research Lidar Network). Aquesta última és part de GALION (Global Atmospheric Watch Atmospheric Lidar Observation Network)-GEOSS (Global Earth Observation System of Systems)

Laboratory for Atmospheres 2009 Technical Highlights

The 2009 Technical Highlights describes the efforts of all members of the Laboratory for Atmospheres. Their dedication to advancing Earth Science through conducting research, developing and running models, designing instruments, managing projects, running field campaigns, and numerous other activities, is highlighted in this report

Développement et mise en oeuvre de LiDAR embarqués sur bouées dérivantes pour l'étude des propriétés des aérosols et des nuages en Arctique et des forçages radiatifs induits

To improve our knowledge of the processes and interactions which occur in Arctic between atmosphere, sea ice and ocean, an EQUIPEX funding was granted to the IAOOS project. This improvement will be reached by deploying a network of multi-instrumented buoys. For the atmospheric analyses an innovative backscattering LiDAR meeting with constraints of the project and arctic environment has been developed. An analytical model of signal to noise ratio in clear sky led to the instrumental key parameters, and numerical simulations helped in improving the system performances. An evolutive prototype has been realized within the tight planning of this EQUIPEX. The first whole equiped buoy was deployed close to the north pole in April 2014 and worked until the beginning of December 2014. A second deployment of two buoys, including a polarized version, was then realized within the N-ICE campaign from January to June 2015. These first campaigns gave first statistics of aerosols and clouds distribution in the central arctic region with an autonomous LiDAR. First results show frequent aerosols layers in mid-troposphere during spring, as well as a high occurence of very low clouds. LiDAR measurements were also used to estimate downwelling longwave and shortwave at surface. Results obtained from these first deployments and comparisons with analysis and outputs from the WRF model show a first overview of what can be expected from this network of multi-instrumented buoys in the central arctic region.Afin de mieux comprendre les processus et les interactions entre l'atmosphère, la glace de mer et l'océan en arctique, un financement EQUIPEX a permis de développer et déployer le projet IAOOS (Ice-Atmosphere-Ocean-Observing-System) de réseau de bouées multi-instrumentées. Pour la partie atmosphère un LiDAR rétrodiffusion innovant a été développé pour répondre aux contraintes du projet et de l'environnement arctique. Un modèle analytique du rapport signal sur bruit en air clair a permis de préciser les paramètres clés de la conception. Des simulations numériques ont ensuite permis d'affiner les performances du système. Un prototype évolutif a été réalisé dans le planning serré de cet EQUIPEX, avant la mise en œuvre d'une première bouée complète au Pôle Nord en avril 2014, qui a fonctionné jusqu'en décembre 2014. Un second déploiement de deux bouées a ensuite été réalisé à l'occasion de la campagne N-ICE de janvier à juin 2015, dont l'une était équipée d'une version polarisée du LiDAR. Les deux campagnes ont permis d'obtenir des premières statistiques de la distribution des aérosols et des nuages en arctique central avec un système LiDAR autonome. Les premiers résultats montrent la présence de couches d'aérosols assez fréquentes au printemps dans la moyenne troposphère et des nuages bas très fréquents. Les mesures LiDAR ont été utilisées pour effectuer une estimation des flux infrarouge et visible descendants. Les résultats des deux premiers déploiements et les comparaisons avec des analyses et des sorties du modèle WRF fournissent des premiers éléments sur l'apport que pourra présenter ce réseau de bouées multi-instrumentées en région centrale arctique

State of the Climate in 2010

Several large-scale climate patterns influenced climate conditions and weather patterns across the globe during 2010. The transition from a warm El Niño phase at the beginning of the year to a cool La Niña phase by July contributed to many notable events, ranging from record wetness across much of Australia to historically low Eastern Pacific basin and near-record high North Atlantic basin hurricane activity. The remaining five main hurricane basins experienced below- to well-below-normal tropical cyclone activity. The negative phase of the Arctic Oscillation was a major driver of Northern Hemisphere temperature patterns during 2009/10 winter and again in late 2010. It contributed to record snowfall and unusually low temperatures over much of northern Eurasia and parts of the United States, while bringing above-normal temperatures to the high northern latitudes. The February Arctic Oscillation Index value was the most negative since records began in 1950. The 2010 average global land and ocean surface temperature was among the two warmest years on record. The Arctic continued to warm at about twice the rate of lower latitudes. The eastern and tropical Pacific Ocean cooled about 1°C from 2009 to 2010, reflecting the transition from the 2009/10 El Niño to the 2010/11 La Niña. Ocean heat fluxes contributed to warm sea surface temperature anomalies in the North Atlantic and the tropical Indian and western Pacific Oceans. Global integrals of upper ocean heat content for the past several years have reached values consistently higher than for all prior times in the record, demonstrating the dominant role of the ocean in the Earth’s energy budget. Deep and abyssal waters of Antarctic origin have also trended warmer on average since the early 1990s. Lower tropospheric temperatures typically lag ENSO surface fluctuations by two to four months, thus the 2010 temperature was dominated by the warm phase El Niño conditions that occurred during the latter half of 2009 and early 2010 and was second warmest on record. The stratosphere continued to be anomalously cool. Annual global precipitation over land areas was about five percent above normal. Precipitation over the ocean was drier than normal after a wet year in 2009. Overall, saltier (higher evaporation) regions of the ocean surface continue to be anomalously salty, and fresher (higher precipitation) regions continue to be anomalously fresh. This salinity pattern, which has held since at least 2004, suggests an increase in the hydrological cycle. Sea ice conditions in the Arctic were significantly different than those in the Antarctic during the year. The annual minimum ice extent in the Arctic—reached in September—was the third lowest on record since 1979. In the Antarctic, zonally averaged sea ice extent reached an all-time record maximum from mid-June through late August and again from mid-November through early December. Corresponding record positive Southern Hemisphere Annular Mode Indices influenced the Antarctic sea ice extents. Greenland glaciers lost more mass than any other year in the decade-long record. The Greenland Ice Sheet lost a record amount of mass, as the melt rate was the highest since at least 1958, and the area and duration of the melting was greater than any year since at least 1978. High summer air temperatures and a longer melt season also caused a continued increase in the rate of ice mass loss from small glaciers and ice caps in the Canadian Arctic. Coastal sites in Alaska show continuous permafrost warming and sites in Alaska, Canada, and Russia indicate more significant warming in relatively cold permafrost than in warm permafrost in the same geographical area. With regional differences, permafrost temperatures are now up to 2°C warmer than they were 20 to 30 years ago. Preliminary data indicate there is a high probability that 2010 will be the 20th consecutive year that alpine glaciers have lost mass. Atmospheric greenhouse gas concentrations continued to rise and ozone depleting substances continued to decrease. Carbon dioxide increased by 2.60 ppm in 2010, a rate above both the 2009 and the 1980–2010 average rates. The global ocean carbon dioxide uptake for the 2009 transition period from La Niña to El Niño conditions, the most recent period for which analyzed data are available, is estimated to be similar to the long-term average. The 2010 Antarctic ozone hole was among the lowest 20% compared with other years since 1990, a result of warmer-than-average temperatures in the Antarctic stratosphere during austral winter between mid-July and early September. List of authors and affiliations... .3 Abstract 16 1. Introduction 17 2. Global Climate 27 a. Overview .. 27 b. Temperature 36; 1. Surface temperature .. 36; 2. Lower tropospheric temperatures 37; 3. Lower stratospheric temperatures .. 38; 4. Lake temperature 39 c. Hydrologic cycle .. 40; I. Surface humidity .. 40; 2. Total column water vapor .41; 3. Precipitation . 42; 4. Northern Hemisphere continental snow cover extent ... 44; 5. Global cloudiness 45; 6. River discharge . 46; 7. Permafrost thermal state . 48; 8. Groundwater and terrestrial water storage .. 49; 9. Soil moisture ..52; 10. Lake levels 53 d. Atmospheric circulation 55; 1. Mean sea level pressure . 55; 2. Ocean surface wind speed 56 e. Earth radiation budget at top-of-atmosphere ... 58 f. Atmosphere composition ...59; 1. Atmosphere chemical composition ...59; 2. Aerosols 65; 3. Stratospheric ozone 67 g. Land surface properties . 68; 1. Alpine glaciers and ice sheets .. 68; 2. Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) ... 72; 3. Biomass burning ... 72; 4. Forest biomass and biomass change .74 3. Global Oceans 77 a. Overview .. 77 b. Sea surface temperatures .. 78 c. Ocean heat content .81 d. Global ocean heat fluxes ... 84 e. Sea surface salinity .. 86 f. Subsurface salinity ... 88 g. Surface currents ... 92; 1. Pacific Ocean 93; 2. Indian Ocean 94; 3. Atlantic Ocean . 95 h. Meridional overturning circulation observations in the subtropical North Atlantic . 95 i. Sea level variations ... 98 j. The global ocean carbon cycle 100; 1. Air-sea carbon dioxide fluxes 100; 2. Subsurface carbon inventory . 102; 3. Global ocean phytoplankton . 105 4. Tropics ... 109 a. Overview 109 b. ENSO and the tropical Pacific 109; 1. Oceanic conditions ... 109; 2. Atmospheric circulation: Tropics .110; 3. Atmospheric circulation: Extratropics ...112; 4. ENSO temperature and precipitation impacts .113 c. Tropical intraseasonal activity .113 d. Tropical cyclones 114; 1. Overview .114; 2. Atlantic basin ...115; 3. Eastern North Pacific basin .121; 4. Western North Pacific basin .. 123; 5. Indian Ocean basins .. 127; 6. Southwest Pacific basin 129; 7. Australian region basin 130 e. Tropical cyclone heat potential .. 132 f. Intertropical Convergence Zones . 134; 1. Pacific ... 134; 2. Atlantic 136 g. Atlantic multidecadal oscillation 137 h. Indian Ocean Dipole . 138 5. The arctic ... 143 a. Overview 143 b. Atmosphere 143 c. Ocean .. 145; 1. Wind-driven circulation . 145; 2. Ocean temperature and salinity 145; 3. Biology and geochemistry .. 146; 4. Sea level .. 148 d. Sea ice cover ... 148; 1. Sea ice extent . 148; 2. Sea ice age ... 149; 3. Sea ice thickness 150 e. Land .. 150; 1. Vegetation ... 150; 2. Permafrost ... 152; 3. River discharge ... 153; 4. Terrestrial snow 154; 5. Glaciers outside Greenland 155 f. Greenland ... 156; 1. Coastal surface air temperature . 156; 2. Upper air temperatures . 158; 3. Atmospheric circulation . 158; 4. Surface melt extent and duration and albedo . 159; 5. Surface mass balance along the K-Transect .. 159; 6. Total Greenland mass loss from GRACE . 160; 7. Marine-terminating glacier area changes .. 160 6. ANTARCTICA ..161 a. Overview .161 b. Circulation ...161 c. Surface manned and automatic weather station observations 163 d. Net precipitation ... 164 e. 2009/10 Seasonal melt extent and duration . 167 f. Sea ice extent and concentration .. 167 g. Ozone depletion 170 7. Regional climates ... 173 a. Overview 173 b. North America ... 173; 1. Canada 173; 2. United States .. 175; 3. México . 179 c. Central America and the Caribbean .. 182; 1. Central America 182; 2. The Caribbean ... 183 d. South America .. 186; 1. Northern South America and the Tropical Andes . 186; 2. Tropical South America east of the Andes .. 187; 3. Southern South America 190 e. Africa 192; 1. Northern Africa 192; 2. Western Africa .. 193; 3. Eastern Africa . 194; 4. Southern Africa .. 196; 5. Western Indian Ocean countries 198 f. Europe . 199; 1. Overview 199; 2. Central and Western Europe 202; 3. The Nordic and Baltic countries . 203; 4. Iberia 205; 5. Mediterranean, Italian, and Balkan Peninsulas .206; 6. Eastern Europe .. 207; 7. Middle East ..208 g. Asia ... 210; 1. Russia ... 210; 2. East Asia ..215; 3. South Asia 217; 4. Southwest Asia ...219 h. Oceania ...222; 1. Southwest Pacific ..222; 2. Northwest Pacific, Micronesia .. 224; 3. Australia .. 227; 4. New Zealand .. 229 8. SEASONAL SUMMARIES ... 233 Acknowledgments 237 Appendix: Acronyms and Abbreviations 238 References . 24

Remote Sensing of Plant Biodiversity

This Open Access volume aims to methodologically improve our understanding of biodiversity by linking disciplines that incorporate remote sensing, and uniting data and perspectives in the fields of biology, landscape ecology, and geography. The book provides a framework for how biodiversity can be detected and evaluated—focusing particularly on plants—using proximal and remotely sensed hyperspectral data and other tools such as LiDAR. The volume, whose chapters bring together a large cross-section of the biodiversity community engaged in these methods, attempts to establish a common language across disciplines for understanding and implementing remote sensing of biodiversity across scales. The first part of the book offers a potential basis for remote detection of biodiversity. An overview of the nature of biodiversity is described, along with ways for determining traits of plant biodiversity through spectral analyses across spatial scales and linking spectral data to the tree of life. The second part details what can be detected spectrally and remotely. Specific instrumentation and technologies are described, as well as the technical challenges of detection and data synthesis, collection and processing. The third part discusses spatial resolution and integration across scales and ends with a vision for developing a global biodiversity monitoring system. Topics include spectral and functional variation across habitats and biomes, biodiversity variables for global scale assessment, and the prospects and pitfalls in remote sensing of biodiversity at the global scale

Remote Sensing of Plant Biodiversity

At last, here it is. For some time now, the world has needed a text providing both a new theoretical foundation and practical guidance on how to approach the challenge of biodiversity decline in the Anthropocene. This is a global challenge demanding global approaches to understand its scope and implications. Until recently, we have simply lacked the tools to do so. We are now entering an era in which we can realistically begin to understand and monitor the multidimensional phenomenon of biodiversity at a planetary scale. This era builds upon three centuries of scientific research on biodiversity at site to landscape levels, augmented over the past two decades by airborne research platforms carrying spectrometers, lidars, and radars for larger-scale observations. Emerging international networks of fine-grain in-situ biodiversity observations complemented by space-based sensors offering coarser-grain imagery—but global coverage—of ecosystem composition, function, and structure together provide the information necessary to monitor and track change in biodiversity globally. This book is a road map on how to observe and interpret terrestrial biodiversity across scales through plants—primary producers and the foundation of the trophic pyramid. It honors the fact that biodiversity exists across different dimensions, including both phylogenetic and functional. Then, it relates these aspects of biodiversity to another dimension, the spectral diversity captured by remote sensing instruments operating at scales from leaf to canopy to biome. The biodiversity community has needed a Rosetta Stone to translate between the language of satellite remote sensing and its resulting spectral diversity and the languages of those exploring the phylogenetic diversity and functional trait diversity of life on Earth. By assembling the vital translation, this volume has globalized our ability to track biodiversity state and change. Thus, a global problem meets a key component of the global solution. The editors have cleverly built the book in three parts. Part 1 addresses the theory behind the remote sensing of terrestrial plant biodiversity: why spectral diversity relates to plant functional traits and phylogenetic diversity. Starting with first principles, it connects plant biochemistry, physiology, and macroecology to remotely sensed spectra and explores the processes behind the patterns we observe. Examples from the field demonstrate the rising synthesis of multiple disciplines to create a new cross-spatial and spectral science of biodiversity. Part 2 discusses how to implement this evolving science. It focuses on the plethora of novel in-situ, airborne, and spaceborne Earth observation tools currently and soon to be available while also incorporating the ways of actually making biodiversity measurements with these tools. It includes instructions for organizing and conducting a field campaign. Throughout, there is a focus on the burgeoning field of imaging spectroscopy, which is revolutionizing our ability to characterize life remotely. Part 3 takes on an overarching issue for any effort to globalize biodiversity observations, the issue of scale. It addresses scale from two perspectives. The first is that of combining observations across varying spatial, temporal, and spectral resolutions for better understanding—that is, what scales and how. This is an area of ongoing research driven by a confluence of innovations in observation systems and rising computational capacity. The second is the organizational side of the scaling challenge. It explores existing frameworks for integrating multi-scale observations within global networks. The focus here is on what practical steps can be taken to organize multi-scale data and what is already happening in this regard. These frameworks include essential biodiversity variables and the Group on Earth Observations Biodiversity Observation Network (GEO BON). This book constitutes an end-to-end guide uniting the latest in research and techniques to cover the theory and practice of the remote sensing of plant biodiversity. In putting it together, the editors and their coauthors, all preeminent in their fields, have done a great service for those seeking to understand and conserve life on Earth—just when we need it most. For if the world is ever to construct a coordinated response to the planetwide crisis of biodiversity loss, it must first assemble adequate—and global—measures of what we are losing