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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Seasonal-to-Interannual Response of Southern Ocean Mixed Layer Depth to the Southern Annular Mode from a Global 1/10° Ocean Model

The relationship between the southern annular mode (SAM) and Southern Ocean mixed layer depth (MLD) is investigated herein using a global 0.1° resolution ocean model. The SAM index is defined as the principal component time series of the leading empirical orthogonal function of extratropical sea level pressure from September to December, when the zonally symmetric SAM feature is most prominent. Following positive phases of the SAM, anomalous deep mixed layers occur in the subsequent fall season, starting in May, particularly in the southeast Pacific. Composite analyses reveal that for positive SAM phases enhanced surface cooling caused by anomalously strong westerlies weakens the stratification of the water column, leading to deeper mixed layers during spring when the SAM signal is at its strongest. During the subsequent summer, the surface warms and the mixed layer shoals. However, beneath the warm surface layer, anomalously weak stratification persists throughout the summer and into fall. When the surface cools again during fall, the mixed layer readily deepens due to this weak interior stratification, a legacy from the previous springtime conditions. Therefore, the spring SAM–fall MLD relationship is interpreted here as a manifestation of reemergence of interior water mass anomalies. The opposite occurs after negative phases of the SAM, with anomalously shallow mixed layers resulting. Additional analyses reveal that for the MLD region in the southeast Pacific, the effects of salinity variations and Ekman heat advection are negligible, although Ekman heat transport may play an important role in other regions where mode water is formed, such as south of Australia and in the Indian Ocean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Application of global weather and climate model output to the design and operation of wind-energy systems

This project addressed the challenge of providing weather and climate information to support the operation, management and planning for wind-energy systems. The need for forecast information is extending to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. Maintenance planning and natural gas trading is being influenced increasingly by anticipation of wind generation on timescales of weeks to months. Future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, long-term wind purchase agreements and the regulatory environment. The challenge of making wind forecasts on these longer time scales is associated with a wide range of uncertainties in general circulation and regional climate models that make them unsuitable for direct use in the design and planning of wind-energy systems. To address this challenge, CFAN has developed a hybrid statistical/dynamical forecasting scheme for delivering probabilistic forecasts on time scales from one day to seven months using what is arguably the best forecasting system in the world (European Centre for Medium Range Weather Forecasting, ECMWF). The project also provided a framework to assess future wind power through developing scenarios of interannual to decadal climate variability and change. The Phase II research has successfully developed an operational wind power forecasting system for the U.S., which is being extended to Europe and possibly Asia.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

58 GEOSCIENCES↗
NASA NTRS2000

Predictability of Seasonal Means in the NSIPP-1 AGCM

The predictability of seasonal means during 1980-99 is examined from 720 seasonal integrations with version 1 of NASA's Seasonal to Interanual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM). The AGCM is the atmospheric (and land) component of the NSIPP fully-coupled atmosphere-land-ocean model. For these runs, the initial atmospheric conditions are taken from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalyses, and sea surface temperatures and sea ice are specified from observations. Results from the northern winter integrations show that the model has a very realistic El Nino/Southern Oscillation (ENSO) response in both the tropics and extratropics. Early results from the northern summer runs show a robust extratropical ENSO response in the Southern Hemisphere Pacific, as well as, a pronounced zonally-symmetric component to the ENSO response in both hemispheres. Results will be presented at the meeting highlighting the seasonal evolution in predictability and skill of the NSIPP model on both global and regional scales. A further analysis of the zonally-symmetric response will be discussed in terms of its potential impact on the predictability of middle-latitude climate variability on seasonal to interannual time scales.

Schubert, Siegfried↗
NASA NTRS2010

MERRA: Progress, Applications, and Challenges for the Future

This presentation gives an overview of the results from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) project, an atmospheric global reanalysis, recently completed at the NASA/Global Modeling and Assimilation Office (GMAO). Comparisons are made with previous and other recent reanalyses to highlight improvements as well as remaining challenges regarding the quality of the reanalyses on diurnal to decadal and longer time scales. Several examples will be presented that highlight some of the strengths of the MERRA product in addressing issues of climate variability on subseasonal to interannual time scales.

Schubert, Siegfried D.↗
NASA NTRS2014

Assessment of Satellite Radiometry in the Visible Domain

Marine reflectance and chlorophyll-a concentration are listed among the Essential Climate Variables by the Global Climate Observing System. To contribute to climate research, the satellite ocean color data records resulting from successive missions need to be consistent and well characterized in terms of uncertainties. This chapter reviews various approaches that can be used for the assessment of satellite ocean color data. Good practices for validating satellite products with in situ data and the current status of validation results are illustrated. Model-based approaches and inter-comparison techniques can also contribute to characterize some components of the uncertainty budget, while time series analysis can detect issues with the instrument radiometric characterization and calibration. Satellite data from different missions should also provide a consistent picture in scales of variability, including seasonal and interannual signals. Eventually, the various assessment approaches should be combined to create a fully characterized climate data record from satellite ocean color.

ocean color↗
NASA NTRS2021

The Scientific Legacy of NASA’s Operation IceBridge

The National Aeronautics and Space Administration (NASA)’s Operation IceBridge (OIB) was a 13-year (2009–2021) airborne mission to survey land and sea ice across the Arctic, Antarctic, and Alaska. Here, we review OIB’s goals, instruments, campaigns, key scientific results, and implications for future investigations of the cryosphere. OIB’s primary goal was to use airborne laser altimetry to bridge the gap in fine-resolution elevation measurements of ice from space between the conclusion of NASA’s Ice, Cloud, and land Elevation Satellite (ICESat; 2003–2009) and its follow-on, ICESat-2 (launched 2018). Additional scientific requirements were intended to contextualize observed elevation changes using a multisensor suite of radar sounders, gravimeters, magnetometers, and cameras. Using 15 different aircraft, OIB conducted 968 science flights, of which 42% were repeat surveys of land ice, 42% were surveys of previously unmapped terrain across the Greenland and Antarctic ice sheets, Arctic ice caps, and Alaskan glaciers, and 16% were surveys of sea ice. The combination of an expansive instrument suite and breadth of surveys enabled numerous fundamental advances in our understanding of the Earth’s cryosphere. For land ice, OIB dramatically improved knowledge of interannual outlet-glacier variability, ice-sheet, and outlet-glacier thicknesses, snowfall rates on ice sheets, fjord and sub-ice-shelf bathymetry, and ice-sheet hydrology. Unanticipated discoveries included a reliable method for constraining the thickness within difficult-to-sound incised troughs beneath ice sheets, the extent of the firn aquifer within the Greenland Ice Sheet, the vulnerability of many Greenland and Antarctic outlet glaciers to ocean-driven melting at their grounding zones, and the dominance of surface-melt-driven mass loss of Alaskan glaciers. For sea ice, OIB significantly advanced our understanding of spatiotemporal variability in sea ice freeboard and its snow cover, especially through combined analysis of fine-resolution altimetry, visible imagery, and snow radar measurements of the overlying snow thickness. Such analyses led to the unanticipated discovery of an interdecadal decrease in snow thickness on Arctic sea ice and numerous opportunities to validate sea ice freeboards from satellite radar altimetry. While many of its data sets have yet to be fully explored, OIB’s scientific legacy has already demonstrated the value of sustained investment in reliable airborne platforms, airborne instrument development, interagency and international collaboration, and open and rapid data access to advance our understanding of Earth’s remote polar regions and their role in the Earth system.

Joseph A. MacGregor↗
DOE OSTI2024

The role of the tropical Atlantic in tropical Pacific climate variability

Abstract Interactions between Atlantic and Pacific Oceans can affect tropical Pacific variability and its global impacts at both interannual and decadal timescales. Thus, a deepened understanding of the coupled Atlantic-Pacific interactions is needed. While possible dynamical mechanisms by which the Atlantic can influence the Pacific have been identified, the effectiveness of those mechanisms is difficult to establish using climate model simulations where Atlantic sea surface temperatures (SSTs) are prescribed and Pacific feedbacks cannot be realistically included. As an alternative approach, here we use a Linear Inverse Model (LIM) trained on observations and capable of correctly reproducing the observed statistics, to assess the relative role of the Atlantic-to-Pacific and Pacific-to-Atlantic influences on tropical Pacific variability. Our results indicate that Atlantic internal variability can enhance interannual SST anomalies in the eastern equatorial Pacific, and decadal SST anomalies in the central equatorial Pacific, while Pacific influences on the Atlantic significantly damp tropical Pacific decadal variability. This methodological framework could also be used to assess climate model fidelity in representing tropical basin interactions, helping to reconcile existing differences among models’ results.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Multiscale Temporal Variability of the Global Air‐Sea CO 2 Flux Anomaly

Abstract The global air‐sea CO 2 flux (F) impacts and is impacted by a plethora of climate‐related processes operating at multiple time scales. In bulk mass transfer formulations, F is driven by physico‐ and bio‐chemical factors such as the air‐sea partial pressure difference (∆pCO 2 ), gas transfer velocity, sea surface temperature, and salinity–all varying at multiple time scales. To de‐convolve the impact of these factors on variability in F at different time scales, time‐resolved estimates of F were computed using a global data set assembled between 1988 and 2015. The F anomalies were defined as temporal deviations from the 28‐year time‐averaged value. Spectral analysis revealed four dominant timescales of variability in F–subseasonal, seasonal, interannual, and decadal with relative amplitude differences varying across regions. A second‐order Taylor series expansion was then conducted along these four timescales to separate drivers across differing regions. The analysis showed that on subseasonal timescales, wind speed variability explains some 66% of the global F anomaly and is the dominant driver. On seasonal, interannual, and decadal timescales, the ∆pCO 2 effect controlled by the ∆pCO 2 anomaly, explained much of the F anomaly. On decadal timescales, the F anomaly was almost entirely governed by the ∆pCO 2 effect with large contributions from high latitudes. The main drivers across timescales also dominate the regional F anomaly, particularly in the mid‐high latitude regions. Finally, the driver of the ∆pCO 2 effect was closely connected with the relative strength of atmospheric pCO 2 and the nonthermal component of oceanic pCO 2 anomaly associated with dissolved inorganic carbon and alkalinity.

Environmental Sciences & Ecology↗
NASA NTRS2004

Contrasting Indian Ocean SST Variability With and Without ENSO Influence: A Coupled Atmosphere-Ocean GCM Study

In this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO's influence on the interannual sea surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSOs influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3-5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin- wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east-west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.

Yu, Jin-Yi↗
DOE OSTI2019

Predicting near-term variability in ocean carbon uptake

Abstract. Interannual variations in air–sea fluxes of carbon dioxide ( CO 2 ) impact the global carbon cycle and climate system, and previous studies suggest that these variations may be predictable in the near term (from a year to a decade in advance). Here, we quantify and understand the sources of near-term predictability and predictive skill in air–sea CO 2 flux on global and regional scales by analyzing output from a novel set of retrospective decadal forecasts of an Earth system model. These forecasts exhibit the potential to predict year-to-year variations in the globally integrated air–sea CO 2 flux several years in advance, as indicated by the high correlation of the forecasts with a model reconstruction of past CO 2 flux evolution. This potential predictability exceeds that obtained solely from foreknowledge of variations in external forcing or a simple persistence forecast, with the longest-lasting forecast enhancement in the subantarctic Southern Ocean and the northern North Atlantic. Potential predictability in CO 2 flux variations is largely driven by predictability in the surface ocean partial pressure of CO 2 , which itself is a function of predictability in surface ocean dissolved inorganic carbon and alkalinity. The potential predictability, however, is not realized as predictive skill, as indicated by the moderate to low correlation of the forecasts with an observationally based CO 2 flux product. Nevertheless, our results suggest that year-to-year variations in ocean carbon uptake have the potential to be predicted well in advance and establish a precedent for forecasting air–sea CO 2 flux in the near future.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Tropical Intraseasonal Air-Sea Exchanges during the 1997 Pacific Warming

The Madden Julian Oscillations (MJO) and associated westerly wind (WW) events account for much of the tropical intraseasonal variability (TISV). The TISV has been suggested as an important stochastic forcing that may be one of the underlying causes for the observed irregularities of the El Nino-Southern Oscillation (ENSO). Recent observational studies and theories of interannual to interdecadal-scale variability suggest that ENSO may arise from different mechanisms depending on the basic states. The Pacific warming event of 1997, being associated with a period of strong MJO and WW events, serves as a natural experiment for studying the possible role of TISV in triggering an ENSO event. We have performed a combined statistical and composite analysis of surface WW events based on the assimilated surface wind and sea level pressure for the period of 1980-1993, the SSM/I wind for the period of 1988-1997, and OLR. Results indicates that extratropical forcing contribute significantly to the evolution of MJO and establishment of WW events over the Pacific warm pool. Following the major WW events, there appeared an eastward extension of equatorial warm SST anomalies from the western Pacific warm pool. Such tropical-extratropical interaction is particularly clear in the winter of 96-97 that leads to the recent warming event in 1997/98. From the above discussion, our current study on this subject is based on the hypothesis that 1) there is an enhanced air-sea interaction associated with TISV and the northerly surges from the extratropics in the initial phase of the 97/98 warming event, and 2) the relevant mechanisms are functions of the basic state of the coupled system (in terms of SST distribution and atmospheric mean circulation) that varies at the interannual and interdecadal time scale. We are analyzing the space-time structure of the northerly surges, their association with air-sea fluxes and upper ocean responses during the period of September 1996 to June 1997. The estimate of daily values of latent heat fluxes is based on NSCAT wind, SST, and ECMWF surface air temperature and SSM/I water vapor data (Chou et al. 1997). To understand the relevant mechanisms, we will analyze the origin of the northerly surges in terms of atmospheric instability associated with the extratropical circulation, and the mutual influence between the tropical heating and the extratropical circulation. In this meeting, we will report the analysis addressing the first part of the above hypothesis.

Sui, C.-H.↗
NASA NTRS2001

Responses of Precipitation and Hydrologic Processes to Tropical SST

The goal of the research is to identify the mechanisms in the response of tropical precipitation and atmospheric hydrologic cycle to sea surface temperature (SST) variability at seasonal-to-interannual time scales, and to utilize the knowledge for better understanding of climate feedback processes relevant to global change. As a first step to achieve the goal, we characterize the inter-relationship among convective/stratiform rain, ice/water clouds water vapor, and SST using TRMM satellite data and a cloud-resolving model. We examined the daily hydrologic variables [column water vapor (PW), cloud liquid water (CW), rainfall rates (RR)] as a function of SST using high-resolution data (0.25 x 0.25, daily) derived from TRMM satellite measurements. Comparing the winter of 97/98 (El Nino condition) against the winter of 99/00 (La Nina condition), area-mean values of all four hydrologic variables in cloudy areas within the tropical Pacific are higher in the El Nino winter than in the La Nina winter. This is consistent with previous observational analyses and SST warming experiments (idealized or ENSO-like) that showed the interaction between hydrologic cyclic and radiation at the seasonal to interannual time scales leads to intensified tropical circulation and hydrologic cycle. However, there is evidence that the enhanced hydrologic cycle over the warm pool is accompanied by an expansion of radiatively -driven subsidence in response to a stronger SST gradient between warm pool and surrounding cold pool. The expanding subsidence effectively reduces cloud amounts over the warm pool. Our analysis of daily variability further indicates a more vigorous water cycle characterized by higher PW, CW, and RR in response to overall warming. This is expected from the Clausius Clapeyron relation as a thermodynamic response to warming. However cloudy areas decrease in response to overall warming. This may be due to factors that are fundamentally different. One possibility is that in a warmer climate, there may be alteration in the microphysical processes in clouds, e.g., increased coalescence of cloud size droplets and increased entrainment of dry air from above due to the invigorated convective motions in response to overall warming. As a result, cloud amounts are less. Another interpretation is that, in colder air masses, more ice particles will be produced and, because of their lower densities, are less likely to precipitate, hence the higher cloud amount. This suggests that, when averaged over a sufficiently large area covering both the rising and sinking branches of the tropical circulation, there maybe an increase in the precipitation efficiency in stratiform clouds, in conjunction with increased subsidence in an enhanced water cycle. This is supported by the residence time at different rainrates.

Sui, C.-H.↗
DOE OSTI2017

Benchmarking carbon fluxes of the ISIMIP2a biome models

The purpose of this study is to evaluate the eight ISIMIP2a biome models against independent estimates of long-term net carbon fluxes (i.e. Net Biome Productivity, NBP) over terrestrial ecosystems for the recent four decades (1971–2010). Here, we evaluate modeled global NBP against 1) the updated global residual land sink (RLS) plus land use emissions (E LUC ) from the Global Carbon Project (GCP), presented as R + L in this study by Le Quéré et al (2015), and 2) the land CO 2 fluxes from two atmospheric inversion systems: Jena CarboScope s81_v3.8 and CAMS v15r2, referred to as F Jena and F CAMS respectively. The model ensemble-mean NBP (that includes seven models with land-use change) is higher than but within the uncertainty of R + L, while the simulated positive NBP trend over the last 30 yr is lower than that from R + L and from the two inversion systems. ISIMIP2a biome models well capture the interannual variation of global net terrestrial ecosystem carbon fluxes. Tropical NBP represents 31 ± 17% of global total NBP during the past decades, and the year-to-year variation of tropical NBP contributes most of the interannual variation of global NBP. According to the models, increasing Net Primary Productivity (NPP) was the main cause for the generally increasing NBP. Significant global NBP anomalies from the long-term mean between the two phases of El Niño Southern Oscillation (ENSO) events are simulated by all models (p < 0.05), which is consistent with the R + L estimate (p = 0.06), also mainly attributed to NPP anomalies, rather than to changes in heterotrophic respiration (Rh). The global NPP and NBP anomalies during ENSO events are dominated by their anomalies in tropical regions impacted by tropical climate variability. Multiple regressions between R + L, F Jena and F CAMS interannual variations and tropical climate variations reveal a significant negative response of global net terrestrial ecosystem carbon fluxes to tropical mean annual temperature variation, and a non-significant response to tropical annual precipitation variation. According to the models, tropical precipitation is a more important driver, suggesting that some models do not capture the roles of precipitation and temperature changes adequately.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Report of the Second ARTMIP Workshop

Atmospheric rivers (ARs) have for the last decade been broadly recognized for their global and regional significance in mediating energy and water cycles. As a distinct large-scale circulation feature, ARs can be characterized by long, narrow bands of atmospheric moisture transport from the tropics to higher latitudes. They are both an important source of water supply to coastal regions as well as a hazard because of their predisposition to increase flood risk. However, predicting ARs poses a significant challenge to the scientific community, as they exhibit large variability from subseasonal-to-interannual time scales. On multi-decadal and longer time scales, it is unclear how the frequency and intensity of ARs will change with a warming climate. Hence ARs play a significant role in understanding predictability of water cycle variability and extremes as well as becoming a factor in assessing risks to future infrastructures. There is a large body of literature that has explored ARs from both global and regional perspectives and from timescales spanning hourly to centennial. Despite significant progress in understanding ARs, significant gaps remain, e.g., in characterizing the dynamical and thermodynamical processes associated with ARs, improving predictions of ARs at weather and subseasonal-to-seasonal timescales, and understanding and quantifying the impacts of ARs on the design and management of built infrastructures. Furthermore, the consensus definition of ARs remains essentially qualitative, and investigators have had to rely on heuristic definitions of ARs for quantitative studies. In the First Atmospheric River Tracking Method Intercomparison Project (ARTMIP) workshop held in May 2017, it was recognized that (1) there are many heuristic AR tracking algorithms employed in the literature, (2) our quantitative—and possibly qualitative— understanding of ARs and their impacts may depend on the details of the algorithm used, (3) no data set yet exists to systematically explore the impact of AR tracking algorithm choice on scientific results, and (4) the broader scientific community therefore lacks any formal guidance on the advantages and disadvantages of different AR tracking methods. The First ARTMIP workshop defined and launched a multi-tiered intercomparison experiment designed to fill this community need. The first tier of ARTMIP was aimed at understanding the impact of AR algorithms on quantitative baseline statistics and characteristics of ARs, and the second tier includes sensitivity studies designed around specific science questions, such as reanalysis uncertainty and influences associated with climate change. The Second ARTMIP workshop was convened on April 23-24, 2018, as a two-day event, and following the completion of Tier 1 of the ARTMIP effort: an experiment in which most existing AR tracking algorithms were run on a standardized data set of reanalyzed weather conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Explaining the trends and variability in the United States tornado records using climate teleconnections and shifts in observational practices

The annual frequency of tornadoes during 1950–2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefficients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other States, thereby reducing their uncertainty. The influence of the anthropogenic factors and the large-scale climate variables are modeled in a nested framework to unravel secular trend from cyclical variability. Population density explains the long-term trend in Dixie Alley. The step-increase induced due to the installation of the Doppler Radar systems explains the long-term trend in Tornado Alley. NAO and the interplay between NAO and ENSO explained the interannual to multi-decadal variability in Tornado Alley. PDO and AMO are also contributing to this multi-time scale variability. SOI and AO explain the cyclical variability in Dixie Alley. This improved understanding of the variability and trends in tornadoes should be of immense value to public planners, businesses, and insurance-based risk management agencies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

GPP↗
DOE OSTI2017

Causes of Extreme Ridges That Induce California Droughts

California droughts are often caused by high-amplitude and persistent ridges near and off the west coast of North America without apparent connections with ENSO. Here with a hierarchy of climate models, it is demonstrated that extreme ridges in this region are associated with a continuum of zonal wavenumber-5 circumglobal teleconnection patterns that originate from midlatitude atmospheric internal dynamics. Although tropical diabatic heating anomalies are not essential to the formation and maintenance of these wave patterns, certain persistent heating anomalies may double the probability of ridges with amplitudes in the 90th percentile occurring on interannual time scales. Those heating anomalies can be caused by either natural variability or possibly by climate change, and they do not necessarily depend on ENSO. The extreme ridges that occurred during the 2013/14 and 2014/15 winters could be examples of ridges produced by heating anomalies that are not associated with ENSO. As a result, this mechanism could provide a source of subseasonal-to-interannual predictability beyond the predictability provided by ENSO.

54 ENVIRONMENTAL SCIENCES↗