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At least 91 records · Page 5

Soil Moisture–Atmosphere Feedbacks Dominate Land Carbon Uptake Variability

Year-to-year changes in carbon uptake by terrestrial ecosystems play an essential role in determining atmospheric carbon dioxide concentrations. It remains uncertain to what extent temperature and water availability can explain these variations at the global scale. Here we use factorial climate model simulations and show that variability in soil moisture drives 90% of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture–atmosphere feedbacks amplify temperature and humidity anomalies, and enhance the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate a dominant role of soil moisture which is not readily apparent in land surface model simulations and observational analyses. These findings highlight the need to account for feedbacks between soil and atmospheric dryness when estimating the carbon cycle’s response to climatic change globally, as well as when conducting field-scale investigations of the ecosystem response to droughts. Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects which are controlled by soil moisture.

Atmospheric dynamics↗

Open-Source Science-Driven Development of the Science Data System (SDS) for Earth System Observatory (ESO) Atmospheric Missions

The NASA Earth System Observatory (ESO) atmospheric missions will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The Science Data System (SDS) will deploy the adaptive processing system (APS) developed within the Cloud to manage the research and operational processing of ESO atmospheric mission orbital and suborbital sensors and curate these data for near real-time and collection reprocessing and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage and distribution. Further, the SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The SDS follows NASA’s commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the SDS system components will be developed with open-source concepts including components of APS itself as well as ESO atmospheric mission algorithms. This presentation describes the framework of the SDS and its integral part in facilitating OSS within the ESO atmospheric missions.

David M. Giles↗

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗

Open-Source Science-led Development of the AOS Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David M. Giles↗

Stochastic modeling of the time-advanced equations for climate dynamics

Long term, climatologically significant statistical properties of the atmospheric component of the climate system are examined in an effort to correctly and efficiently incorporate this component into larger models for climate that include oceanic and cryospheric influences and deal realistically with climate replication. The magnetic of the unpredictable (noise) component of long term atmospheric behavior is also studied in order to develop the potential for viable climatological forecasting.

Laurmann, J. A.↗

Satellite-derived attributes of cloud vortex systems and their application to climate studies

Defense Meteorological Satellite Program (DMSP) visible and infrared mosaics are analyzed in conjunction with synoptic meteorological observations of sea level pressure (SLP) and upper-air height to derive composite patterns of cyclonic cloud vortices for the Northern Hemisphere. The patterns reveal variations in the structure and implied dynamics of cyclonic systems at different stages of development that include: (1) increasing vertical symmetry of the lower-level and upper-air circulations and (2) decreasing lower-tropospheric thicknesses and temperature advection, associated with increasing age of the vortex. Cloud vortices are more intense in winter than in summer and typically reach maximum intensity in the short-lived prespiral signature stage. There are major structural differences among frontal wave, polar air, and 'instant occlusion' cyclogenesis types. Cyclones in the dissipation stage may reintensify (deepen), as denoted by the appearance in the imagery of an asymmetric cloud band or a tightened spiral vortex. The satellite-derived statistics on cloud vortex intensity, which are seasonal- and latitude- as well as type-dependent, are applied to a preliminary examination of the synoptic manifestations of seasonal climate variability. An apparently close relationship is found, for two winter and spring seasons, between Northern Hemisphere cyclonic activity and variations in cryosphere variables, particularly the extent of Arctic sea ice. The results may indicate that increased snow and ice extent accompany a southward displacement of cyclonic activity and/or a predominance of deeper systems. However, there is also a strong regional dependence to the ice-synoptics feedback. This study demonstrates the utility of high resolution meteorological satellite imagery for studies of climate variations (climate dynamics).

Carleton, Andrew M.↗

Improved Representations of Land‐Atmosphere Interactions Over the Continental U.S. Through Dynamic Root Modeling

Previous studies have identified the oversimplified root system representation as a key factor leading to inaccuracies in vegetation‐atmosphere feedbacks. In this study, a dynamic root water uptake scheme in the Noah‐MP land surface model has been coupled to the Weather Research and Forecasting (WRF) model to investigate its impact on the surface hydroclimate variables and land‐atmosphere interactions. To evaluate the impact of the dynamic root, two coupled simulations were conducted, one with the dynamic root water uptake scheme (DynRt) and one with the static root water uptake scheme (StcRt), which is based on the default root representation in Noah‐MP, with slight modifications, primarily in vegetation‐related parameters. Both DynRt and StcRt simulations were conducted with a small ensemble of three members to account for variations in physical parameterizations, initial and boundary forcing and model setup. When compared with reference data sets, the DynRt simulations show improved results than the StcRt simulations, reducing biases in the simulated leaf area index, surface energy fluxes, soil moisture and precipitation. Two different mechanisms through which roots affect land‐atmosphere coupling have been identified. Over the transitional climate zone between the dry and wet climate, the dynamic root scheme affects surface climate and land‐atmosphere coupling mainly through changes in soil moisture through hydraulic redistribution by plant root system. Over the energy‐limited mesic zone, the dynamic root affects regional land‐atmosphere coupling mainly through changes in carbon allocation. This work highlights the importance of dynamic root representation in improving vegetation‐atmosphere simulations by enhancing predictions of water, energy, and carbon fluxes.

54 ENVIRONMENTAL SCIENCES↗

Observational benchmarks inform representation of soil organic carbon dynamics in land surface models

Abstract. Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Machine learning models can help identify dominant environmental controllers and establish their functional relationships with SOC stocks. The resulting knowledge can be integrated into ESMs to reduce uncertainty and improve predictions of SOC dynamics over space and time. In this study, we used a large number of SOC field observations (n=54 000), geospatial datasets of environmental factors (n=46), and two machine learning approaches (namely random forest, RF, and generalized additive modeling, GAM) to (1) identify dominant environmental controllers of global and biome-specific SOC stocks, (2) derive functional relationships between environmental controllers and SOC stocks, and (3) compare the identified environmental controllers and predictive relationships with those in models used in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Our results showed that the diurnal temperature, drought index, cation exchange capacity, and precipitation were important observed environmental predictors of global SOC stocks. While the RF model identified 14 environmental factors that describe climatic, vegetation, and edaphic conditions as important predictors of global SOC stocks (R2=0.61, RMSE = 0.46 kg m−2), current ESMs oversimplify the relationships between environmental factors and SOC, with precipitation, temperature, and net primary productivity explaining > 96 % of the variability in ESM-modeled SOC stocks. Further, our study revealed notable disparities among the functional relationships between environmental factors and SOC stocks simulated by ESMs compared with observed relationships. To improve SOC representations in ESMs, it is imperative to incorporate additional environmental controls, such as the cation exchange capacity, and refine the functional relationships to align more closely with observations.

54 ENVIRONMENTAL SCIENCES↗

On the dynamic forcing of short-term climate fluctuations by feedback mechanisms

Various internal feedback mechanisms in the ocean atmosphere system were studied. A variability pattern of sea surface temperature with a quasibiennial oscillation (QBO) was detected off the coast of Senegal, in the Gulf of Guinea and even in the Gulf Stream as it leaves the North American continental shelf. Possible physical connections between some of these QBO's were pointed out by a hypothetical feedback model. Interaction of a QBO with the annual cycle may lead to beating frequencies resembling climatic trends of a duration of several years.

Reiter, E. R.↗

Accelerating Climate and Weather Simulations through Hybrid Computing

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

hybrid computing↗

Obliquity-oblateness feedback: Are climatically sensitive values of obliquity dynamically unstable?

A new model is presented for feedback between rotational and climatic variations, operative on time scales of 10(exp 4) - 10(exp 7) years. Due to the combined effect of planetary perturbations to the Earth's orbit plane and luni-solar torques on the oblate figure of the Earth, the obliquity varies by approximately 1 deg on a 4 x 10(exp 4) year time scale. Associated changes in the seasonal and latitudinal pattern of incident solar radiation cause major glaciations. Mass transport from the oceans to the polar ice sheets during these glaciations can change the gravitational oblateness of the Earth by amounts approaching 1%. As the rate of spin axis precession is directly proportional to the oblateness, the climatically forced mass transport can by dynamically significant. A simple parameterization of this coupled orbital-rotational-climatic system suggests that there is a strong tendency for the system to evolve away from climatically sensitive values of the obliquity. This may explain the mid-Pleistocene transition from an obliquity dominated regime to the present regime in which most climatic variability is concentrated at longer (10(exp 5) year) periods.

Bills, Bruce G.↗

The Cloud Radar System

Improvement in our understanding of the radiative impact of clouds on the climate system requires a comprehensive view of clouds including their physical dimensions, dynamical generation processes, and detailed microphysical properties. To this end, millimeter vave radar is a powerful tool by which clouds can be remotely sensed. The NASA Goddard Space Flight Center has developed the Cloud Radar System (CRS). CRS is a highly sensitive 94 GHz (W-band) pulsed-Doppler polarimetric radar that is designed to fly on board the NASA high-altitude ER-2 aircraft. The instrument is currently the only millimeter wave radar capable of cloud and precipitation measurements from above most all clouds. Because it operates from high-altitude, the CRS provides a unique measurement perspective for cirrus cloud studies. The CRS emulates a satellite view of clouds and precipitation systems thus providing valuable measurements for the implementation and algorithm validation for the upcoming NASA CloudSat mission that is designed to measure ice cloud distributions on the global scale using a spaceborne 94 GHz radar. This paper describes the CRS instrument and preliminary data from the recent Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE). The radar design is discussed. Characteristics of the radar are given. A block diagram illustrating functional components of the radar is shown. The performance of the CRS during the CRYSTAL-FACE campaign is discussed.

Racette, Paul↗

Dynamical Forecasts of Tropical Terrestrial Carbon Fluxes with the NASA S2S Retrospective Forecast System

Recent advances in the ability to predict climate anomalies at sub-seasonal to seasonal (S2S) timescales allow us to explore the possibility of forecasting carbon flux anomalies. Although carbon flux forecasting is a relatively new concept, it is potentially beneficial as it can help us better understand global and regional land-atmosphere carbon feedbacks associated with climate variations and can provide guidance for future field mission design. Here we evaluate the skill of forecasted terrestrial carbon anomalies generated from meteorological anomalies produced with the NASA Global Modeling and Assimilation Office (GMAO) S2S forecast system. We focus here on three representative time periods (the most recent 2015-2016 El Nino, 2011 La Nina, and 2014 as a neutral year), with each corresponding 9-month forecast comprising four ensemble members initialized in the preceding December. The meteorological variables produced by the GMAO forecast system were bias-corrected using a climatology derived from the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) before being used to drive a suite of offline simulations with the NASA Catchment-CN terrestrial biosphere model, a model that computes water-energy-carbon dynamics. Forecasts are evaluated by comparing against satellite-driven estimates of gross primary production (GPP) and inverse model estimates of net carbon flux that incorporate satellite carbon dioxide measurements. We find that the restrospectively predicted carbon fluxes in the tropics reasonably reproduce the signs and magnitudes of the observed anomalies between the 2015-2016 El Nino and the 2011 La Nina for both net flux and GPP. For instance, for the El Nino period, the magnitude of the forecasted negative GPP anomaly in the South American tropics (which undergoes anomalously warm and dry conditions) agrees with the observed GPP anomaly at leads of up to three or four months. Overall, this study demonstrates potential skill in the forecast of biospheric carbon fluxes a few months in advance, a capability that could contribute to attribution studies focusing on carbon flux variations and support innovative observation strategies in the future.

Lee, Eunjee↗

GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model

Abstract. Reservoirs play a significant role in modifying the spatiotemporal availability of surface water to meet multi-sector human demands, despite representing a relatively small fraction of the global water budget. Yet the integrated modeling frameworks that explore the interactions among climate, land, energy, water, and socioeconomic systems at a global scale often contain limited representations of water storage dynamics that incorporate feedbacks from other systems. In this study, we implement a representation of water storage in the Global Change Analysis Model (GCAM) to enable the exploration of the future role (e.g., expansion) of reservoir water storage globally in meeting demands for, and evolving in response to interactions with, the climate, land, and energy systems. GCAM represents 235 global water basins, operates at 5-year time steps, and uses supply curves to capture economic competition among renewable water (now including reservoirs), non-renewable groundwater, and desalination. Our approach consists of developing the GLObal Reservoir Yield (GLORY) model, which uses a linear programming (LP)-based optimization algorithm and dynamically linking GLORY with GCAM. The new coupled GCAM–GLORY approach improves the representation of reservoir water storage in GCAM in several ways. First, the GLORY model identifies the cost of supplying increasing levels of water supply from reservoir storage by considering regional physical and economic factors, such as evolving monthly reservoir inflows and demands, and the leveled cost of constructing additional reservoir storage capacity. Second, by passing those costs to GCAM, GLORY enables the exploration of future regional reservoir expansion pathways and their response to climate and socioeconomic drivers. To guide the model toward reasonable reservoir expansion pathways, GLORY applies a diverse array of feasibility constraints related to protected land, population, water sources, and cropland. Finally, the GLORY–GCAM feedback loop allows evolving water demands from GCAM to inform GLORY, resulting in an updated supply curve at each time step, thus enabling GCAM to establish a more meaningful economic value of water. This study improves our understanding of the sensitivity of reservoir water supply to multiple physical and economic dimensions, such as sub-annual variations in climate conditions and human water demands, especially for basins experiencing socioeconomic droughts.

54 ENVIRONMENTAL SCIENCES↗

Terrestrial Planets Comparative Climatology (TPCC) mission concept

The authors and co-signers of the Terrestrial Planets Comparative Climatology (TPCC) mission concept white paper advocate that planetary science in the next decade would greatly benefit from comparatively studying the fundamental behavior of the atmospheres of Venus and Mars, contemporaneously and with the same instrumentation, to capture atmospheric response to the same solar forcing, and with a minimum of instrument-related variability. NASA’s vision is to understand the effects of the Sun on the solar system and the potential for life elsewhere (Obj,1.1 of [1]). This vision directly motivates the study of terrestrial climate histories and evolution, with the ultimate goal of understanding what factors allow the emergence and sustainability of life/biosphere. It is widely accepted that Venus, Mars, and Earth were formed at the same time and in the same neighborhood of the solar nebula [2,3], and had water—a necessary ingredient for life. In spite of strong overlap in the atmospheric composition of these planets, their current climatic states are vastly different. While Earth retains water, both Mars and Venus’ surfaces are now dry. The manner in which these terrestrial bodies evolved, and whether Mars or Venus currently hosts or previously hosted life, are fundamental mysteries in planetary science. As such, the TPCC mission concept has been developed.The TPCC guiding science goals are:(1) to understand Venus’ evolutionary history compared to Mars and Earth, and (2) to elucidate the driving forces and mechanisms of global circulation at Mars and Venus. These goals address the science question: Why have Mars’ and Venus’ climates evolved so differently from each other and from Earth’s? Furthermore, a greater depth of understanding our own solar system, enables us to understand the variability and likelihood of habitable conditions within extra-solar planetary systems.We suggest a mission architecture and payload that would determine the noble gas content and isotopic ratios, including the D/H ratio, at Venus with sufficient accuracy to identify the timeline of Venus’ climatic evolution for comparison with Mars. In addition, our concept would systematically “follow the energy” at Mars and Venus, in order to establish how solar forcing on the two atmospheric systems leads to the current balance of dynamical, chemical, and radiative processes responsible for each planet’s climatic state.This would include acquisition of the first global atmospheric wind profiles on either planet;global, continuous profiles of aerosols, gases, and water vapor at vertical resolutions higher than any previous mission;and regular UV and IR night glow observations tracking global circulation on both planets.To increase the fidelity of the planned planetary comparisons, the TPCC mission concept baseline (estimated to be New Frontiers Class)would send a single spacecraft to visit one planet and then the next, allowing measurements of each planet with the same instrumentation within similar parts of the solar cycle. The concept uses commercial solar-electric propulsion (SEP; e.g., [4])similar to the Psyche mission [5], plus a probesent deep into Venus’ atmosphere(e.g., LLISSE concept; [6]).Alternatively, “twin” spacecraft (with added probe to the Venus craft),developed at the same time,and launched close in time,would increase the overlap in operation periods and should also be studied. Either architecture is a timely alternative to independently developed and launched spacecraft payloads, which ultimately are more costly and difficult to inter-calibrate.

Leslie K. Tamppari↗

Clouds and Water Vapor in the Climate System and Radiative Transfer in Clear Air and Cirrus Clouds in the Tropics

Research supported under this grant was aimed at attacking unanswered scientific questions that lie at the intersection of radiation, dynamics, chemistry, and climate. Considerable emphasis was placed on scientific collaboration and the innovative development of instruments required to address these issues. Specific questions include water vapor distribution in the tropical troposphere, atmospheric radiation, thin cirrus clouds, stratosphere-troposphere exchange, and correlative science with satellite observations.

Anderson, James G.↗

Bias Correction of Hydrologic Projections Strongly Impacts Inferred Climate Vulnerabilities in Institutionally Complex Water Systems

Water-resources planners use regional water management models (WMMs) to identify vulnerabilities to climate change. Frequently, dynamically downscaled climate inputs are used in conjunction with land-surface models (LSMs) to provide hydrologic streamflow projections, which serve as critical inputs for WMMs. Here, we show how even modest projection errors can strongly affect assessments of water availability and financial stability for irrigation districts in California. Specifically, our results highlight that LSM errors in projections of flood and drought extremes are highly interactive across timescales, path-dependent, and can be amplified when modeling infrastructure systems (e.g., misrepresenting banked groundwater). Common strategies for reducing errors in deterministic LSM hydrologic projections (e.g., bias correction) can themselves strongly distort projected climate vulnerabilities and misrepresent their inferred financial consequences. Overall, our results indicate a need to move beyond standard deterministic climate projection and error management frameworks that are dependent on single simulated climate change scenario outcomes.

Keyvan Malek↗

Cloud and ice in the planetary scale circulation and in climate

The roles of the cryosphere, and of cloud-radiative interactions are investigated. The effects clouds and ice have in the climate system are examined. The cloud radiation research attempts explain the modes of interaction (feedback) between raditive transfer, cloud formation, and atmospheric dynamics. The role of sea ice in weather and climate is also discussed. Models are used to describe the ice and atmospheric dynamics under study.

Herman, G. F.↗