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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness

Plants are characterized by the iso/anisohydry continuum depending on how they regulate leaf water potential (?L). However, how iso/anisohydry changes over time in response to year-to-year variations in environmental dryness and how such responses vary across different regions remains poorly characterized. We investigated how dryness, represented by aridity index, affects the interannual variability of ecosystem iso/anisohydry at the regional scale, estimated using satellite microwave vegetation optical depth (VOD) observations. This ecosystem-level analysis was further complemented with published field observations of ?L at the species level. We found different behaviors in the directionality and sensitivity of isohydricity (s) with respect to the interannual variation of dryness in different ecosystems. These behaviors can largely be differentiated by the average dryness of the ecosystem itself: in mesic ecosystems, s decreases in drier years, albeit at a higher rate; in xeric ecosystems, s increases in drier years, albeit at a lower rate. These results were supported by the species-level synthesis. Our study suggests that how plants adjust their water use across years – as revealed by their interannual variability in isohydricity – depends on the dryness of plants’ living environment. This finding advances our understanding of plant responses to drought at regional scales.

Wu, Genghong↗
NASA NTRS2007

Seasonal Evolution and Interannual Variability of the Local Solar Energy Absorbed by the Arctic Sea Ice-Ocean System

The melt season of the Arctic sea ice cover is greatly affected by the partitioning of the incident solar radiation between reflection to the atmosphere and absorption in the ice and ocean. This partitioning exhibits a strong seasonal cycle and significant interannual variability. Data in the period 1998, 2000-2004 were analyzed in this study. Observations made during the 1997-1998 SHEBA (Surface HEat Budget of the Arctic Ocean) field experiment showed a strong seasonal dependence of the partitioning, dominated by a five-phase albedo evolution. QuikSCAT scatterometer data from the SHEBA region in 1999-2004 were used to further investigate solar partitioning in summer. The time series of scatterometer data were used to determine the onset of melt and the beginning of freezeup. This information was combined with SSM/I-derived ice concentration, TOVS-based estimates of incident solar irradiance, and SHEBA results to estimate the amount of solar energy absorbed in the ice-ocean system for these years. The average total solar energy absorbed in the ice-ocean system from April through September was 900 MJ m(sup -2). There was considerable interannual variability, with a range of 826 to 1044 MJ m(sup -2). The total amount of solar energy absorbed by the ice and ocean was strongly related to the date of melt onset, but only weakly related to the total duration of the melt season or the onset of freezeup. The timing of melt onset is significant because the incident solar energy is large and a change at this time propagates through the entire melt season, affecting the albedo every day throughout melt and freezeup.

Perovich, Donald K.↗
NASA NTRS1999

Interannual Variability of the Mosaic Land-Surface Model

Recently, NASA Goddard Earth Observing System (GEOS-1) reanalysis data has been used to provide forcing for the Koster and Suarez Mosaic Land-surface Model (LSM). The LSM was integrated off-line at all global land points for the period of 1983 - 1995 by the Off-line Land- surface GEOS Assimilation system (OLGA). Here, we compare the interannual variability of OLGA, GEOS-1 and surface observing stations temperature and moisture. Particular attention is given to the United States because of the extreme seasons of 1988 and 1993. Furthermore, the comparison of OLGA is extended to include the analysis of data on the'tiles' (different surface types) in the Mosaic LSM. Results indicate that the GEOS-1 near-surface temperature and moisture reasonably represents the interannual variability in more normal years. However, OLGA also simulates the extreme drought and floods years well. The analysis of the tile information shows that the "Bare soil" surface type is most sensitive to the climate extremes. Off-line testing has provided valuable information on the performance of the Mosaic LSM prior to its incorporation into the new version of the GEOS Data Assimilation System and the integration of a new long reanalysis.

Bosilovich, Michael G.↗
NASA NTRS2020

Decadal Changes in the Interannual Variability of Heat Waves in East Asia Caused by Atmospheric Teleconnection Changes

The heat wave in East Asia is examined by using empirical orthogonal function analysis to isolate dominant heat-wave patterns in the ground-based temperature observations over the Korean Peninsula and China and related large-scale atmospheric circulations obtained from the National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis 1 during 1973–2012. This study focuses particularly on the interannual variability of heat waves and its decadal change. The analysis identifies two major atmospheric teleconnection patterns playing an important role in developing typical heat-wave patterns in East Asia—the Scandinavian (SCAND) and the circumglobal teleconnection (CGT) patterns, which exhibit a significant decadal change in the interannual variability in the mid-1990s. Before the mid-1990s, heat-wave occurrence was closely related to the CGT pattern, whereas the SCAND pattern is more crucial to explain heat-wave variability in the recent period. The stationary wave model experiments suggest an intensification of the SCAND pattern in the recent period driven by an increase in land–atmosphere interaction over Eurasia and decadal change in the dominant heat-wave patterns in East Asia.

heat wave patterns↗
DOE OSTI2018

Forests dominate the interannual variability of the North American carbon sink

Understanding what drives the interannual variability (IAV) of the land carbon sink is crucial for improving future predictions of this important, yet uncertain, component of the climate system. While drivers of global and hemispheric-scale net ecosystem exchange (NEE) IAV have been investigated, our understanding of the drivers of NEE IAV at regional scales (e.g. sub-continental, biome-level) is quite poor. Here we explore the biome-level attribution and drivers of North American NEE using inverse estimates derived from a dense network of atmospheric CO2 observations. We find that deciduous broadleaf and mixed forests are the primary regions responsible for North American NEE IAV, which differs from the ecoregions identified for the globe and Northern Hemisphere. We also find that a suite of terrestrial biosphere models (TBMs) do not agree on the dominant biome contributing to NEE IAV, with TBMs falling along an apparent spectrum ranging between those with IAV dominated primarily by forested ecosystems to those with IAV dominated by non-forested ecosystems. Furthermore, this regional trade-off in TBM NEE IAV is found to be linked to differing regional responses to environmental drivers among TBMs. This work displays the importance of extra-tropical forests in driving continental NEE IAV and also highlights the challenges and limitations of using TBMs to inform regional-scale carbon flux dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Quantifying the Seasonal and Interannual Variability of North American Isoprene Emissions Using Satellite Observations of the Formaldehyde Column

Quantifying isoprene emissions using satellite observations of the formaldehyde (HCHO) columns is subject to errors involving the column retrieval and the assumed relationship between HCHO columns and isoprene emissions, taken here from the GEOS-CHEM chemical transport model. Here we use a 6-year (1996-2001) HCHO column data set from the Global Ozone Monitoring Experiment (GOME) satellite instrument to (1) quantify these errors, (2) evaluate GOME-derived isoprene emissions with in situ flux measurements and a process-based emission inventory (Model of Emissions of Gases and Aerosols from Nature, MEGAN), and (3) investigate the factors driving the seasonal and interannual variability of North American isoprene emissions. The error in the GOME HCHO column retrieval is estimated to be 40%. We use the Master Chemical Mechanism (MCM) to quantify the time-dependent HCHO production from isoprene, alpha- and beta-pinenes, and methylbutenol and show that only emissions of isoprene are detectable by GOME. The time-dependent HCHO yield from isoprene oxidation calculated by MCM is 20-30% larger than in GEOS-CHEM. GOME-derived isoprene fluxes track the observed seasonal variation of in situ measurements at a Michigan forest site with a -30% bias. The seasonal variation of North American isoprene emissions during 2001 inferred from GOME is similar to MEGAN, with GOME emissions typically 25% higher (lower) at the beginning (end) of the growing season. GOME and MEGAN both show a maximum over the southeastern United States, but they differ in the precise location. The observed interannual variability of this maximum is 20-30%, depending on month. The MEGAN isoprene emission dependence on surface air temperature explains 75% of the month-to-month variability in GOME-derived isoprene emissions over the southeastern United States during May-September 1996-2001.

Palmer, Paul I.↗
NASA NTRS2018

Average Versus High Surface Ozone Levels over the Continental USA: Model Bias, Background Influences, and Interannual Variability

US background ozone (O3) includes O3 produced from anthropogenic O3 precursors emitted outside of the USA, from global methane, and from any natural sources. Using a suite of sensitivity simulations in the GEOS-Chem global chemistry transport model, we estimate the influence from individual background sources versus US anthropogenic sources on total surface O3 over 10 continental US regions from 2004 to 2012. Evaluation with observations reveals model biases of +0-19ppb in seasonal mean maximum daily 8h average (MDA8) O3, highest in summer over the eastern USA. Simulated high-O3 events cluster too late in the season. We link these model biases to excessive regional O3 production (e.g., US anthropogenic, biogenic volatile organic compounds (BVOCs), and soil NOx, emissions), or coincident missing sinks. On the 10 highest observed O3 days during summer (O3_top10obs_JJA), US anthropogenic emissions enhance O3 by 5-11ppb and by less than 2ppb in the eastern versus western USA. The O3 enhancement from BVOC emissions during summer is 1-7 ppb higher on O3_top10obs_JJA days than on average days, while intercontinental pollution is up to 2ppb higher on average versus on O3_top10obs_JJA days. During the summers of 2004-2012, monthly regional mean US background O3 MDA8 levels vary by up to 15ppb from year to year. Observed and simulated summertime total surface O3 levels on O3_top10obs_JJA days decline by 3ppb (averaged over all regions) from 2004-2006 to 2010-2012, reflecting rising US background (+2ppb) and declining US anthropogenic O3 emissions (6ppb) in the model. The model attributes interannual variability in US background O3 on O3_top10obs days to natural sources, not international pollution transport. We find that a 3-year averaging period is not long enough to eliminate interannual variability in background O3 on the highest observed O3 days.

Guo, Jean J.↗
NASA NTRS2005

Interannual Variability in Surface LW Fluxes Over the Tropical Oceans As Seen in ISCCP-FD and GEWEX SRB Data Sets

One notable aspect of Earth s climate is that although the planet appears to be very close to radiative balance at top-of-atmosphere (TOA), the atmosphere itself and underlying surface are not. Profound exchanges of energy between the atmosphere and oceans, land and cryosphere occur over a range of time scales. Recent evidence from broadband satellite measurements suggests that even these TOA fluxes contain some detectable variations. Our ability to measure and reconstruct radiative fluxes at the surface and at the top of atmosphere is improving rapidly. In this work we will evaluate two recently released estimates of radiative fluxes, focusing primarily on surface estimates. The International Satellite Cloud Climatology Project FD radiative flux profiles are available from mid-1 983 to near present and have been constructed by driving the radiative transfer physics from the Goddard Institute for Space Studies (GISS) global model with ISCCP clouds and TOVS (TIROS Operational Vertical Sounder)thermodynamic profiles. Fu!l and clear sky SW and LW fluxes are produced. A similar product from the NASA/GEWEX Surface Radiation Budget Project using different radiative flux codes and thermodynamics from the NAS/Goddard Earth Observing System (GEOS-1) assimilation model makes a similar calculation of surface fluxes. However this data set currently extends only through 1995. Significant differences in both interannual variability as well as trends are found between among these data sets. For radiative fluxes these differences are traced to TOVS thermodynamic soundings used to drive the ISCCP-FD calculations. Errors in near surface temperature and precipitable water cascade into ISCCP upward and downward IR flux components, demonstrably affecting interannual variability. Revised estimates of clear-sky fluxes over ocean are made using statistical algorithms and water vapor from the (SSM/I) Special Sensor Microwave Imager. These calculations show strong near-surface water vapor feedback over the tropical oceans in association with SST changes. However, it is also shown that ISCCP longwave cloud forcing, common to both the ISCCP-FD and GEWEX SRB retrievals, is the main driver of a long-term decrease in net LW flux to the surface during the near-20 year period covered by these revised estimates.

Robertson, F. R.↗
NASA NTRS2019

Maximum Carbon Uptake Rate Dominates the Interannual Variability of Global Net Ecosystem Exchange

Terrestrial ecosystems contribute most of the interannual variability (IAV) in atmospheric carbon dioxide (CO2) concentrations, but processes driving the IAV of net ecosystem CO2 exchange (NEE) remain elusive. For a predictive understanding of the global C cycle, it is imperative to identify indicators associated with ecological processes that determine the IAV of NEE. Here, we decompose the annual NEE of global terrestrial ecosystems into their phenological and physiological components, namely maximum carbon uptake (MCU) and release (MCR), the carbon uptake period (CUP), and two parameters, α and β, that describe the ratio between actual versus hypothetical maximum C sink and source, respectively. Using long‐term observed NEE from 66 eddy covariance sites and global products derived from FLUXNET observations, we found that the IAV of NEE is determined predominately by MCU at the global scale, which explains 48% of the IAV of NEE on average while α, CUP, β, and MCR explain 14%, 25%, 2%, and 8%, respectively. These patterns differ in water‐limited ecosystems versus temperature‐ and radiation‐limited ecosystems; 31% of the IAV of NEE is determined by the IAV of CUP in water‐limited ecosystems, and 60% of the IAV of NEE is determined by the IAV of MCU in temperature‐ and radiation‐limited ecosystems. The Lund‐Potsdam‐Jena (LPJ) model and the Multi‐scale Synthesis and Terrestrial Model Inter‐comparison Project (MsTMIP) models underestimate the contribution of MCU to the IAV of NEE by about 18% on average, and overestimate the contribution of CUP by about 25%. This study provides a new perspective on the proximate causes of the IAV of NEE, which suggest that capturing the variability of MCU is critical for modeling the IAV of NEE across most of the global land surface.

Fu, Zheng↗
NASA NTRS1983

Interannual variability and predictability of 500 mb geopotential heights over the Northern Hemisphere

The interannual variability of monthly mean 500 mb heights in a 15-year sample of observed data is compared to the variance expected from sampling errors associated with high-frequency fluctuations using the analysis of variance approach. The monthly mean 'signal' stands out significantly from the 'noise' over a substantial fraction of the Northern Hemisphere during the winter. The expected spectrum of variance at very low frequencies is assumed to be white at frequencies lower than per (30 days) rather than the per (96 days) cutoff used by Madden. This difference is justified by observing that the effective time between independent samples T(0) is relatively insensitive to changes in the maximum lag over which the local autocorrelation is integrated to calculate T(0). Further non-randomness in the variance of 500 mb heights is evidenced by the correlation between monthly mean height and contemporaneous daily variability.

Shukla, J.↗
NASA NTRS1990

Seasonal and interannual variability of pigment concentrations across a California Current frontal zone

The seasonal and interannual variability of the latitudinal position of the California Current frontal zone was investigated by examining satellite images of phytoplankton pigment from the coastal-zone color scanner for the periods 1979-1983 and 1986. The pigment concentrations associated with the zonal front were also determined. A general seasonal cycle of pigment concentrations is was established. It was found that variations in the frontal structure are controlled primarily by changes in pigment concentration north of the front. Seasonal variations were found to be minimal south of the front, where pigment concentrations remain low throughout the spring, summer, and fall.

Thomas, A. C.↗
NASA NTRS1984

Interannual variability versus seasonal variability in the tropical Atlantic

Monthly fields of sea surface temperature and wind stress for the tropical Atlantic are constructed for January 1964 to December 1979. Inside the Gulf of Guinea the amplitude of the seasonal variability of SST ranges between 2.5 and 4 times greater than the interannual variability. In the remainder of the equatorial Atlantic this measure is less than 2. Standard deviations of wind stress anomalies indicate that, except near the Intertropical Convergence Zone, the magnitude of interannual fluctuations is greater than that of seasonal ones. The joint analyses of these SST and wind stress fields indicate the largest positive SST anomaly in the Gulf of Guinea (July, 1968) was immediately preceded by the only reversal of the trade winds west along the equator.

Picaut, J.↗
DOE OSTI2017

Interannual variability of ecosystem carbon exchange: From observation to prediction

Here, terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location: Global terrestrial ecosystems. Furthermore, we conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. As a result, the phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi-arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes less contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. In conclusion, to improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time-series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Causes of Interannual Variability over the Southern Hemispheric Tropospheric Ozone Maximum

We examine the relative contribution of processes controlling the interannual variability (IAV) of tropospheric ozone over four sub-regions of the southern hemispheric tropospheric ozone maximum (SHTOM) over a 20-year period. Our study is based on hindcast simulations from the National Aeronautics and Space Administration Global Modeling Initiative chemistry transport model (NASA GMI-CTM) of tropospheric and stratospheric chemistry, driven by assimilated Modern Era Retrospective Analysis for Research and Applications (MERRA) meteorological fields. Our analysis shows that over SHTOM region, the IAV of the stratospheric contribution is the most important factor driving the IAV of upper tropospheric ozone (270 hectopascals), where ozone has a strong radiative effect. Over the South Atlantic region, the contribution from surface emissions to the IAV of ozone exceeds that from stratospheric input at and below 430 hectopascals. Over the South Indian Ocean, the IAV of stratospheric ozone makes the largest contribution to the IAV of ozone with little or no influence from surface emissions at 270 and 430 hectopascals in austral winter. Over the tropical South Atlantic region, the contribution from IAV of stratospheric input dominates in austral winter at 270 hectopascals and drops to less than half but is still significant at 430 hectopascals. Emission contributions are not significant at these two levels. The IAV of lightning over this region also contributes to the IAV of ozone in September and December. Over the tropical southeastern Pacific, the contribution of the IAV of stratospheric input is significant at 270 and 430 hectopascals in austral winter, and emissions have little influence.

Global Modeling Initiative chemistry transport mod↗
NASA NTRS2001

Two-Dimensional Model Simulations of Interannual Variability in the Tropical Stratosphere

Meteorological data from the United Kingdom Meteorological Office (UKMO) and constituent data from the Upper Atmospheric Research Satellite (UARS) are used to construct yearly zonal mean dynamical fields for the 1990s for use in the GSFC 2-D chemistry and transport model. This allows for interannual dynamical variability to be included in the model constituent simulations. In this study, we focus on the tropical stratosphere. We find that the phase of quasi-biennial oscillation (QBO) signals in equatorial CH4, and profile and total column 03 data is resolved quite well using this empirically- based 2-D model transport framework. However. the QBO amplitudes in the model constituents are systematically underestimated relative to the observations at most levels. This deficiency is probably due in part to the limited vertical resolutions of the 2-D model and the UKMO and UARS input data sets. We find that using different heating rate calculations in the model affects the interannual and QBO amplitudes in the constituent fields, but has little impact on the phase. Sensitivity tests reveal that the QBO in transport dominates the ozone interannual variability in the lower stratosphere. with the effect of the temperature QBO being dominant in the tipper stratosphere via the strong temperature dependence of the ozone loss reaction rates. We also find that the QBO in odd nitrogen radicals, which is caused by the QBO modulated transport of NOy, plays a significant but not dominant role in determining the ozone QBO variability in the middle stratosphere. The model mean age of air is in good overall agreement with that determined from tropical lower,middle stratospheric OMS balloon observations of SF6 and CO2. The interannual variability of tile equatorial mean age in the model increases with altitude and maximizes near 40 km, with a range, of 4-5 years over the 1993-2000 time period.

Fleming, Eric L.↗
NASA NTRS2013

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

interference↗
NASA NTRSDate not supplied

Interannual Variability of Aerosols and CO in the Upper Troposphere/Lower Stratosphere (UTLS): Connection to the Climate Variability, Asian Summer Monsoon Strengths, and Emissions

We present our study of decadal variations of UTLS aerosol composition in terms of their sources and convective transport mechanisms associated with the Asian summer monsoon. We use the NASA global model GEOS that incorporates emissions from anthropogenic, biomass burning, volcanic, and other natural sources to simulate the aerosols and related gases, and satellite observations of aerosols and CO in the UTLS from 2010-2020 to investigate (1) the interannual variability of aerosol composition in the UTLS, (2) such variability in relationship to the ENSO and Asian summer monsoon strengths, and (3) the connections of UTLS aerosol with the anthropogenic and natural emissions.

decadal variations↗