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At least 109 records · Page 6

The Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: A Case Study over the Continental U.S. using the GISS-ModelE2 and WRF Models

Dynamical downscaling is being increasingly used for climate change studies, wherein the climates simulated by a coupled atmosphere-ocean general circulation model (AOGCM) for a historical and a future (projected) decade are used to drive a regional climate model (RCM) over a specific area. While previous studies have demonstrated that RCMs can add value to AOGCM-simulated climatologies over different world regions, it is unclear as to whether or not this translates to a better reproduction of the observed climate change therein. We address this issue over the continental U.S. using the GISS-ModelE2 and WRF models, a state-of-the-science AOGCM and RCM, respectively. As configured here, the RCM does not effect holistic improvement in the seasonally and regionally averaged surface air temperature or precipitation for the individual historical decades. Insofar as the climate change between the two decades is concerned, the RCM does improve upon the AOGCM when nudged in the domain proper, but only modestly so. Further, the analysis indicates that there is not a strong relationship between skill in capturing climatological means and skill in capturing climate change. Though additional research would be needed to demonstrate the robustness of this finding in AOGCM/RCM models generally, the evidence indicates that, for climate change studies, the most important factor is the skill of the driving global model itself, suggesting that highest priority should be given to improving the long-range climate skill of AOGCMs.

Racherla, P. N.↗

Increasing large wildfires over the western United States linked to diminishing sea ice in the Arctic

Abstract The compound nature of large wildfires in combination with complex physical and biophysical processes affecting variations in hydroclimate and fuel conditions makes it difficult to directly connect wildfire changes over fire-prone regions like the western United States (U.S.) with anthropogenic climate change. Here we show that increasing large wildfires during autumn over the western U.S. are fueled by more fire-favorable weather associated with declines in Arctic sea ice during preceding months on both interannual and interdecadal time scales. Our analysis (based on observations, climate model sensitivity experiments, and a multi-model ensemble of climate simulations) demonstrates and explains the Arctic-driven teleconnection through regional circulation changes with the poleward-shifted polar jet stream and enhanced fire-favorable surface weather conditions. The fire weather changes driven by declining Arctic sea ice during the past four decades are of similar magnitude to other leading modes of climate variability such as the El Niño-Southern Oscillation that also influence fire weather in the western U.S.

54 ENVIRONMENTAL SCIENCES↗

Comparison of Radiative Energy Flows in Observational Datasets and Climate Modeling

This study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10Wm(exp -2) each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface. Comparisons of spatial radiative flux distributions at the TOA between observations and climate modeling indicate large deficiencies in the strength and distribution of model-simulated cloud radiative effects. Differences are largest for lower-altitude clouds over low-latitude oceans. Global modeling simulates stronger cloud radiative effects (CRE) by +30Wmexp -2) over trade wind cumulus regions, yet smaller CRE by about -30Wm(exp -2) over (smaller in area) stratocumulus regions. At the surface, climate modeling simulates on average about 15Wm(exp -2) smaller radiative net flux imbalances, as if climate modeling underestimates latent heat release (and precipitation). Relative to observational datasets, simulated surface net fluxes are particularly lower over oceanic trade wind regions (where global modeling tends to overestimate the radiative impact of clouds). Still, with the uncertainty in noncloud ancillary data, observational data do not establish a reliable reference.

Raschke, Ehrhard↗

Demonstration of Imaging Fourier Transform Spectrometer (FTS) Performance for Planetary and Geostationary Earth Observing

The combination of massively parallel spatial sampling and accurate spectral radiometry offered by imaging FTS makes it extremely attractive for earth and planetary remote sensing. We constructed a breadboard instrument to help assess the potential for planetary applications of small imaging FTS instruments in the 1 - 5 micrometer range. The results also support definition of the NASA Geostationary Imaging FTS (GIFTS) instrument that will make key meteorological and climate observations from geostationary earth orbit. The Planetary Imaging FTS (PIFTS) breadboard is based on a custom miniaturized Bomen interferometer that uses corner cube reflectors, a wishbone pivoting voice-coil delay scan mechanism, and a laser diode metrology system. The interferometer optical output is measured by a commercial infrared camera procured from Santa Barbara Focalplane. It uses an InSb 128x128 detector array that covers the entire FOV of the instrument when coupled with a 25 mm focal length commercial camera lens. With appropriate lenses and cold filters the instrument can be used from the visible to 5 micrometers. The delay scan is continuous, but slow, covering the maximum range of +/- 0.4 cm in 37.56 sec at a rate of 500 image frames per second. Image exposures are timed to be centered around predicted zero crossings. The design allows for prediction algorithms that account for the most recent fringe rate so that timing jitter produced by scan speed variations can be minimized. Response to a fixed source is linear with exposure time nearly to the point of saturation. Linearity with respect to input variations was demonstrated to within 0.16% using a 3-point blackbody calibration. Imaging of external complex scenes was carried out at low and high spectral resolution. These require full complex calibration to remove background contributions that vary dramatically over the instrument FOV. Testing is continuing to demonstrate the precise radiometric accuracy and noise characteristics.

Revercomb, Henry E.↗

The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

Whiteman, David N.↗

The sensitivity of a general circulation model to Saharan dust heating

Evidence is accumulating that tropospheric aerosols, such as Saharan dust, can significantly influence weather and climate. The Climate Model of the Goddard Laboratory for Atmospheric Sciences is presently used to assess the possible effects of Saharan dust on the weather and climate of North Africa and the tropical Atlantic Ocean. The three-dimensional model solves the conservation equations for the horizontal wind vector, potential temperature, water vapor mixing ratio, and surface pressure. Parameterizations are included for turbulent exchange at the earth surface, cumulus convection, large scale saturation, diurnally varying solar radiation, and terrestrial radiation. Realistic simulations are thereby produced for many aspects of the observed climate.

Randall, D.↗

Managing Traffic on the Three-Way Street: Steps Toward Closing the Aerosol Forcing Uncertainty Gap

Understanding changes in the radiative forcing of climate is critical for any effort to attribute, mitigate, or predict climate change. Although greenhouse gases (GHGs) contribute most of the radiative forcing, uncertainty in the climate forcing by airborne particles (aerosols) dominates the uncertainty in forcing changes overall. Yet, aerosol forcing has remained virtually undiminished for more than 20 years despite considerable advances in most of the key contributing elements. Satellite and suborbital measurements, as well as modeling, each have essential roles to play in reducing the uncertainty in the aerosol forcing of climate. This presentation will begin by briefly covering the reasons why aerosols are important for climate study, and will then summarize what we are learning about aerosols from current satellite remote-sensing work, and allude to the roles of suborbital measurements and models. Emphasis will be placed on nascent efforts to link satellite data with models, the need to continue as planned current programs supporting advanced, global-scale satellite and surface-based aerosol and precursor gas observations, climate modeling, as well as intensive field campaigns aimed at characterizing the underlying physical and chemical processes involved. The talk will conclude by highlighting new efforts needed to obtain systematic in situ measurements of aerosol microphysical and chemical properties, along with a greater research focus on integrating the unique contributions of measurements and modeling toward reducing the aerosol climate forcing uncertainty gap.

aerosol↗

Capturing Complete Spatial Context in Satellite Observations of Greenhouse Gases

Scientific consensus from a 2015 pre-Decadal Survey workshop highlighted the essential need for a wide-swath (mapping) low earth orbit (LEO) instrument delivering carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) measurements with global coverage. OCO-2 pioneered space-based CO2 remote sensing, but lacks the CH4, CO and mapping capabilities required for an improved understanding of the global carbon cycle. The Carbon Balance Observatory (CARBO) advances key technologies to enable high-performance, cost-effective solutions for a space-based carbon-climate observing system. CARBO is a compact, modular, 15-30° field of view spectrometer that delivers high-precision CO2, CH4, CO and solar induced chlorophyll fluorescence (SIF) data with weekly global coverage from LEO. CARBO employs innovative immersion grating technologies to achieve diffraction-limited performance with OCO-like spatial (2 x 2 sq.km) and spectral (λ/Δλ≈ 20,000) resolution in a package that is >50% smaller, lighter and more cost-effective. CARBO delivers a 25- to 50-fold increase in spatial coverage compared to OCO-2 with no loss of detection sensitivity. Individual CARBO modules weigh < 20 kg, opening diverse new space-based platform opportunities.

Miller, Charles E.↗

Soil organic matter diagenetic state informs boreal forest ecosystem feedbacks to climate change

The fate of soil organic carbon (SOC) in boreal forests is dependent on the integrative ecosystem response to climate change. For example, boreal forest productivity is often nitrogen (N) limited, and climate warming can enhance N cycling and primary productivity. However, the net effect of this feedback on the SOC reservoir and its longevity with climate change remain unclear due to difficulty in detecting small differences between large and variable carbon (C) fluxes needed to determine net changes in soil reservoirs. The diagenetic state of SOC – resulting from the physicochemical and biological transformations that alter the original biomolecular composition of detrital inputs to soil over time – is useful for tracing the net response of SOC at the timescales relevant to climate change not usually discernible from fluxes and stocks alone. Here, we test two hypotheses using a mesic boreal forest climate transect: (1) the SOC diagenetic state is maintained across this climosequence, and (2) the maintenance of the SOC diagenetic state is a consequence of coupled soil C and N cycling, signifying the role of enhanced N cycling supporting SOC inputs that maintain SOC stocks within the warmer-climate forests. Shifts in nonvascular to vascular plant inputs with climate observed in these and other boreal forests highlighted the need to carefully separate biogeochemical indicators of SOC source from those signifying diagenetic alteration. We thus evaluated and applied lignin biomarkers to assess the diagenetic alteration of SOC in these boreal forest organic soils and directly compared the lignin diagenetic state with that of soil organic nitrogen (SON) assessed through amino acid composition. The lignin diagenetic state remained constant across the climate transect, indicating a balance between the input and removal of lignin in these mesic boreal forests. When combined with previous knowledge of these forest ecosystems, including the diagenetic state of SON and direct measures of C fluxes and stocks, the results indicate a coupled increase in C and N cycling with climate warming that supports forest productivity and maintains SOC stocks. This balance could markedly shift as other factors begin to limit forest productivity (e.g., trace nutrients, water) with further climate change or affect forest nutrient allocation (e.g., forest age or compositional change). Further application of the approach presented here could be used to detect the limits of this and other ecosystem–climate feedbacks, by providing a tractable and parameterizable index of the lignin state across large spatial scales, necessary for ecosystem-scale parameterizations.

54 ENVIRONMENTAL SCIENCES↗

The Critical Role of the Routing Scheme in Simulating Peak River Discharge in Global Hydrological Models

Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge which is crucial in flood simulations has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971-2010) within the ISIMIP2a (Inter-Sectoral Impact Model Intercomparison Project phase 2a) project. The runoff simulations were used as input for the global river routing model CaMa-Flood (Catchment-based Macro-scale Floodplain). The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC (Global Runoff Data Centre) stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about two-thirds of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.

peak river discharge↗

Multigenic resistance to Xylella fastidiosa in wild grapes ( Vitis sps.) and its implications within a changing climate

Xylella fastidiosa is a bacterium that infects crops like grapevines, coffee, almonds, citrus and olives. There is little understanding of the genes that contribute to plant resistance, the genomic architecture of resistance, and the potential role of climate in shaping resistance, in part because major crops like grapevines (Vitis vinifera) are not resistant to the bacterium. Here we study a wild grapevine species, V. arizonica, that segregates for resistance. Using genome-wide association, we identify candidate resistance genes. Resistance-associated kmers are shared with a sister species of V. arizonica but not with more distant species, suggesting that resistance evolved more than once. Finally, resistance is climate dependent, because individuals from low (< 10 °C) temperature locations in the wettest quarter were typically susceptible to infection, likely reflecting a lack of pathogen pressure in colder climates. In fact, climate is as effective a predictor of resistance phenotypes as some genetic markers. We extend our climate observations to additional crops, predicting that increased pathogen pressure is more likely for grapevines and almonds than some other susceptible crops.

60 APPLIED LIFE SCIENCES↗

TPSAS-NF1676L-27604-DND

Satellite-based hyperspectral observations provide high information content for the Earth's atmospheric and surface properties; however, in order to analyze hyperspectral data efficiently, fast and accurate radiative transfer model is needed. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate radiative transfer in the cloudy atmosphere from far IR to visible and UV spectral regions quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. The computation speed is 3 to 4 orders of magnitude faster than the medium speed correlated-k option MODTRAN5 and LBLRTM. The PCRTM calculated radiance spectra agree with the Modtran and LBLRTM within 0.02%. We will demonstrate the application of the PCRTM forward model for atmospheric and surface property inversions and for climate observation studies.

X Liu↗

Climate-Induced Northerly Expansion of Siberian Silkmoth Range

Siberian silkmoth (Dendrolimus sibiricus Tschetv.) is a dangerous pest that has affected nearly 2.5 x 10(exp 6) ha of “dark taiga” stands (composed of Abies sibirica, Pinus sibirica and Picea obovata) within the latitude range of 52°–59° N. Here we describe a current silkmoth outbreak that is occurring about half degree northward of its formerly documented outbreak range. This outbreak has covered an area of about 800 thousand ha with mortality of conifer stands within an area of about 300 thousand ha. The primary outbreak originated in the year 2014 within stands located on gentle relatively dry southwest slopes at elevations up to 200 m above sea level (a.s.l.) Then the outbreak spread to the mesic areas including northern slopes and the low-elevation forest belts along the Yenisei ridge. Within the outbreak area, the northern Siberian silkmoth population has reduced generation length from two to one year. Our study showed that the outbreak was promoted by droughts in prior years, an increase of the sum of daily temperatures (t > +10 °C), and a decrease in ground cover moisture. Within the outbreak area, secondary pests were also active, including the aggressive Polygraphus proximus bark borer beetle. The outbreak considered here is part of the wide-spread (panzonal) Siberian silkmoth outbreak that originated during 2014–2015 with a range of up to 1000 km in southern Siberia. Our work concludes that observed climate warming opens opportunities for Siberian silkmoth migration into historically outbreak free northern “dark taiga” stands.

Siberian taiga↗

Decoding the dynamics of poleward shifting climate zones using aqua-planet model simulations

Growing evidence indicates that the atmospheric and oceanic circulation experiences a systematic poleward shift in a warming climate. However, the complexity of the climate system, including the coupling between the ocean and the atmosphere, natural climate variability and land-sea distribution, tends to obfuscate the causal mechanism underlying the circulation shift. Here, using an idealised coupled aqua-planet model, we explore the mechanism of the shifting circulation, by isolating the contributing factors from the direct CO 2 forcing, the indirect ocean surface warming, and the wind-stress feedback from the ocean dynamics. We find that, in contrast to the direct CO 2 forcing, ocean surface warming, in particular an enhanced subtropical ocean warming, plays an important role in driving the circulation shift. This enhanced subtropical ocean warming emerges from the background Ekman convergence of surface anomalous heat in the absence of the ocean dynamical change. Additionally, it expands the tropical warm water zone, causes a poleward shift of the mid-latitude temperature gradient, hence forces a corresponding shift in the atmospheric circulation and the associated wind pattern. The shift in wind, in turn drives a shift in the ocean circulation. Our simulations, despite being idealised, capture the main features of the observed climate changes, for example, the enhanced subtropical ocean warming, poleward shift of the patterns of near-surface wind, sea level pressure, storm tracks, precipitation and large-scale ocean circulation, implying that increase in greenhouse gas concentrations not only raises the temperature, but can also systematically shift the climate zones poleward.

54 ENVIRONMENTAL SCIENCES↗

Mechanical Description of the Mars Climate Sounder Instrument

This paper introduces the Mars Climate Sounder (MCS) Instrument of the Mars Reconnaissance Orbiter (MRO) spacecraft. The instrument scans the Martian atmosphere almost continuously to systematically acquire weather and climate observations over time. Its primary components are an optical bench that houses dual telescopes with a total of nine channels for visible and infrared sensing, and a two axis gimbal that provides pointing capabilities. Both rotating joints consist of an integrated actuator with a hybrid planetary/harmonic transmission and a twist cap section that enables the electrical wiring to pass through the rotating joint. Micro stepping is used to reduce spacecraft disturbance torques to acceptable levels while driving the stepper motors. To ensure survivability over its four year life span, suitable mechanical components, lubrication, and an active temperature control system were incorporated. Some life test results and lessons learned are provided to serve as design guidelines for actuator parts and flex cables.

rotating joints↗

Elastic Changepoint Detection for Globally-indexed Functional Time Series Data with Climate Applications

Changepoint detection is a vital tool in the application of climate data analysis. Numerous types of climate observation data are most properly represented by functional time series, implying a need for accurate changepoint detection methods applicable to functional time series data. Such data taken at a global scale often contain both spatial heterogeneity and dependence as well as phase (time) misalignment. In this report, we present methods which can detect spatially-dependent changepoints while allowing different estimates of change time and change strength depending on location. Additionally, we provide extensions to this spatially-predicted model which controls for phase variability among observations. Our methods provide the ability to detect a single change, or control for epidemic changes (where a “return-to-normal” change is more likely to be detected than the initial change). We showcase results analyzing the June 1991 eruption of Mt. Pinatubo, where our methods demonstrate the ability to accurately detect both single and epidemic changepoints even in the presence of strong seasonal variability. We find that our spatially-predicted model improves the detection of relevant changepoints versus methods which do not take spatial information into account, and we find that controlling for phase variability helps to control the false discovery rate during the detection process.

54 ENVIRONMENTAL SCIENCES↗

Present-day correlations are insufficient to predict cloud albedo change by anthropogenic aerosols in E3SM v2

Cloud albedo susceptibility to droplet number perturbation remains a source of uncertainty in understanding aerosol–cloud interactions and thus both past and present climate states. Through the Energy Exascale Earth System Model (E3SM) v2 experiments, we probe the effects of competing processes on cloud albedo susceptibility of low-lying marine stratocumulus in the northeast Pacific. In present-day conditions, we find that increasing precipitation suppression by aerosols increases cloud albedo susceptibility, whereas increasing cloud sedimentation decreases it. By constructing a hypothetical model configuration exhibiting negative susceptibility under all conditions, we conclude that cloud albedo change due to aerosol perturbation cannot be predicted by present-day co-variabilities in E3SM v2. As such, our null result herein challenges the assumption that present-day climate observations are sufficient to constrain past states, at least in the context of cloud albedo changes to aerosol perturbation.

54 ENVIRONMENTAL SCIENCES↗

Aircraft remote sensing of soil moisture and hydrologic parameters, Taylor Creek, Florida, and Little River, Georgia, 1979 data report

Experiments were conducted to evaluate aircraft remote sensing techniques for hydrology in a wide range of physiographic and climatic regions using several sensor platforms. The data were collected in late 1978 and during 1979 in two humid areas--Taylor Creek, Fla., and Little River, Ga. Soil moisture measurements and climatic observations are presented as well as the remote sensing data collected using thermal infrared, passive microwave, and active microwave systems.

Jackson, T. J.↗