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DOE OSTI2021

Quantifying carbon budget, crop yields and their responses to environmental variability using the ecosys model for U.S. Midwestern agroecosystems

As one of the major agricultural production areas in the world, the United States (U.S.) Midwest plays a vital role in the global food supply and agricultural ecosystem services. Although significant efforts have been made in modeling the carbon cycle dynamics over this area, large uncertainty still exists in the previous simulations in terms of reproducing individual components of the carbon cycle and their responses to environmental variability. Here we evaluated the performance of an advanced agroecosystem model, ecosys, in simulating carbon budgets over the U.S. Midwest, considering both the magnitude of carbon flux/yield and its response to environmental (climate and soil) variability. We conducted model simulations and evaluations at 7 cropland eddy-covariance sites as well as over 293 counties of Illinois, Indiana, and Iowa in the U.S. Midwest. The site-level simulations showed that ecosys captured both the magnitude and seasonal patterns of carbon fluxes (i.e., net ecosystem carbon exchange (NEE), ecosystem gross primary production (GPP), and ecosystem respiration (Reco)), leaf area index (LAI), and dynamic plant carbon allocation processes, with R2 equal to 0.92, 0.87, 0.87, and 0.78 for GPP, NEE, Reco, and LAI, respectively across all the sites compared with the observations. For regional scale simulations, ecosys reproduced the spatial distribution and interannual variability of corn and soybean yields with the constraints of observed yields and a new remotely sensed GPP product, with R2 of multi-year averaged simulated and observed yield equal 0.83 and 0.80 for corn and soybean, respectively. The simulated responses of carbon cycle dynamics to environmental variability were consistent with that from the empirical observations at both site and regional scales. Furthermore, our results demonstrated the applicability of ecosys in simulating the carbon cycle and soil carbon dynamics of the U.S. Midwestern agroecosystems under different climate and soil conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Empirical estimation of weather-driven yield shocks using biophysical characteristics for U.S. rainfed and irrigated maize, soybeans, and winter wheat

Agricultural yields are highly susceptible to changes in weather system patterns, including both annual and sub-annual changes in temperature and precipitation. Understanding the impacts of future changes in meteorological variables on crop yields have been widely studied in both empirical and process-based models. This work presents a structural econometric approach that combines historical weather data with information about the biophysical growth cycles of maize, winter wheat, and soy to predict the year-to-year yield responses for rainfed crops. Modeled soil moisture and temperature are taken as key predictors, which allows testing the fitted rainfed model’s ability to predict irrigated yields by assuming irrigation produces the numerically optimal level of soil moisture. This approach is grounded in known biophysical processes, which improves confidence in the model predictions. It produces estimates of interannual variability in yields, which enable study of the effects of extreme events on agricultural productivity. Finally, it enables prediction of the potential impacts of changing weather patterns on irrigated crops in areas that are currently primarily rainfed. We present the results of the empirical model, fitted with rainfed data; out-of-sample validation on irrigated crops; and projections of yield shocks under multiple future climate scenarios. Under a bias-corrected GFDL RCP8.5 scenario, this approach predicts average yield change, relative to 2006-2020 average yields, across U.S. counties in the 2040-2060 period of -16.9% and -13.4% for rainfed and irrigated maize, of -19.1% and -18.4% for rainfed and irrigated soy, and of -4.0% and -2.0% for rainfed and irrigated winter wheat. And in the 2070-2090 period of -30.3% and -28.8 % for rainfed and irrigated maize, of -33.1% and -32.8% for rainfed and irrigated soy, and of -6.5% and -5.2%for rainfed and irrigated winter wheat.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Signatures of aerosol-cloud interactions in GiOcean: a coupled global reanalysis with two-moment cloud microphysics

Aerosols influence the Earth's radiative balance through direct interactions with radiation and by affecting cloud properties. Anthropogenic aerosols have led to cooling during the industrial era through aerosol–cloud interactions (ACI), including aerosol effects on cloud microphysical properties and the subsequent adjustments. However, large uncertainties remain in Earth system models (ESMs) regarding the magnitude of this cooling. In part, ESMs substantially disagree on cloud properties, thermodynamics, the hydrological cycle, and general circulation. Reanalysis provides a useful avenue for exploring the impact of ACI on clouds and radiation because its atmosphere is forced to match realistic conditions through the assimilation of observations. Here, we explore the impact of ACI on clouds in the GiOcean reanalysis – the first to incorporate aerosol-cloud interactions. We contrast variables important for ACI between GiOcean and satellite observations and develop 2-dimensional lookup tables of ACI for both using a source-sink budget perspective to attribute the changes in cloud droplet number (Nd) and liquid water path (LWP) to aerosol and meteorology. A compositing analysis using lookup tables shows that GiOcean captures key aspects of aerosol–cloud–precipitation interactions, including (1) activation of aerosol into cloud droplets, (2) effective precipitation scavenging of Nd, (3) suppression of precipitation by high Nd in regions with heavy aerosol emissions. In contrast, satellite observations do not exhibit clear patterns for processes (2) and (3). Random Forest analysis shows that interannual variability in Nd and LWP over the Northern Hemisphere ocean in GiOcean is primarily driven by precipitation, consistent with satellite observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1994

Stratospheric ozone variations in the equatorial region as seen in Stratiospheric Aerosol and Gas Experiment data

An analysis is made of equatorial ozone variations for 5 years, 1984-1989, using the ozone profile data derived from the Stratospheric Aerosol and Gas Experiment II (SAGE II) instrument. Attention is focused on the annual cycle and also on interannual variability, particularly the quasi-biennial oscillation (QBO) and El Nino-Southern Oscillation (ENSO) variations in the lower stratosphere, where the largest contribution to total column ozone takes place. The annual variation in zonal mean total ozone around the equator is composed of symmetric and asymmetric modes with respect to the equator, with maximum contributions being around 19 km for the symmetric mode and around 25 km for the asymmetric mode. The persistent zonal wavenumber 1 structure observed by the total ozone mapping spectrometer over the equator is almost missing in the SAGE-derived column amounts integrated in the stratosphere, suggesting a significant contribution from tropospheric ozone. Interannual variations in the equatorial ozone are dominated by the QBO above 20 km and the ENSO-related variation below 20 km. The ozone QBO is characterized by zonally uniform phase changes in association with the zonal wind QBO in the equatorial lower stratosphere. The ENSO-related ozone variation consists of both the east-west vacillation and the zonally uniform phase variation. During the El Nino event, the east-west contrast with positive (negative) deviations in the eastern (western) hemisphere is conspicuous, while the decreasing tendency of the zonal mean values is maximum at the same time.

Shiotani, Masato↗

NASA NTRS2015

The Global Structure of UTLS Ozone in GEOS-5: A Multi-Year Assimilation of EOS Aura Data

Eight years of ozone measurements retrieved from the Ozone Monitoring Instrument (OMI) and the Microwave Limb Sounder, both on the EOS Aura satellite, have been assimilated into the Goddard Earth Observing System version 5 (GEOS-5) data assimilation system. This study thoroughly evaluates this assimilated product, highlighting its potential for science. The impact of observations on the GEOS-5 system is explored by examining the spatial distribution of the observation-minus-forecast statistics. Independent data are used for product validation. The correlation coefficient of the lower-stratospheric ozone column with ozonesondes is 0.99 and the bias is 0.5%, indicating the success of the assimilation in reproducing the ozone variability in that layer. The upper-tropospheric assimilated ozone column is about 10% lower than the ozonesonde column but the correlation is still high (0.87). The assimilation is shown to realistically capture the sharp cross-tropopause gradient in ozone mixing ratio. Occurrence of transport-driven low ozone laminae in the assimilation system is similar to that obtained from the High Resolution Dynamics Limb Sounder (HIRDLS) above the 400 K potential temperature surface but the assimilation produces fewer laminae than seen by HIRDLS below that surface. Although the assimilation produces 5 - 8 fewer occurrences per day (up to approximately 20%) during the three years of HIRDLS data, the interannual variability is captured correctly. This data-driven assimilated product is complementary to ozone fields generated from chemistry and transport models. Applications include study of the radiative forcing by ozone and tracer transport near the tropopause.

GEOS-5↗

NASA NTRSDate not supplied

Composition Reanalyses at NASA’s Global Modeling and Assimilation Office

Scientific Assessments of Ozone Depletion 2018 and 2022 report the recovery of Antarctic ozone, consistent with diminishing concentrations of halogens in the stratosphere. Both the size and the depth of the springtime ozone holes exhibit downward trends, particularly in September. Superimposed on the recovery trend are significant year-to-year fluctuations arising from dynamical variability potentially influenced by climate forcing and volcanic eruptions. Since 2018 the Antarctic stratosphere has experienced a wild parade of austral spring seasons with a sudden stratospheric warming and exceptionally high ozone in 2019 followed by large and long-lasting ozone holes in the following years, prompting questions about the speed and detectability of Antarctic ozone recovery and its potential connections to human-induced climate change. From the Australian New Years’ wildfires of 2020 to volcanic aerosols to the unprecedented injection of water vapor by the Hunga volcanic eruption, recent scientific literature on the subject investigates many factors that may or may not have contributed to this remarkable interannual variability. This presentation summarizes dynamical influences on springtime Antarctic stratospheric ozone in recent years and discusses these results in the context of long-term trends. In particular, this work seeks to isolate dynamical and chemical contributions to the Antarctic springs since 2019 using a consistent methodological framework. Our analysis uses constituent and meteorological fields from the MERRA-2 Stratospheric Composition Reanalysis of Aura MLS (M2-SCREAM) in combination with data from the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer and from ozone sondes. Using the high spatial and temporal resolution of M2-SCREAM, we analyze the daily evolution of southern polar ozone, HCl, N2O, and water vapor in dynamical flow-following coordinates relative to the location, size, and shape of the polar vortex. For vertically integrated stratospheric ozone we emphasize the importance of the wave-influenced geometry of the polar vortex and its vertical alignment. The ultimate purpose of this project is to contribute to the quantification of the speed of the Antarctic ozone recovery and associated uncertainties.

Krzysztof Wargan↗

NASA NTRS2022

Linkages Between GRACE Water Storage, Hydrologic Extremes, and Climate Teleconnections in Major African Aquifers

Water resources management is a critical issue in Africa where many regions are subjected to sequential droughts and floods. The objective of our work was to assess spatiotemporal variability in water storage and related controls (climate, human intervention) in major African aquifers and consider approaches toward more sustainable development. Different approaches were used to track water storage, including GRACE/GRACE Follow On satellites for Total Water Storage (TWS); satellite altimetry for reservoir storage, MODIS satellites for vegetation indices, and limited ground-based monitoring. Results show that declining trends in TWS (60–73 km3 over the 18 yr GRACE record) were restricted to aquifers in northern Africa, controlled primarily by irrigation water use in the Nubian and NW Saharan aquifers. Rising TWS trends were found in aquifers in western Africa (23–49 km3), attributed to increased recharge from land use change and cropland expansion. Interannual variability dominated TWS variability in eastern and southern Africa, controlled primarily by climate extremes. Climate teleconnections, particularly El Nino Southern Oscillation and Indian Ocean Dipole, strongly controlled droughts and floods in eastern and southern Africa. Huge aquifer storage in northern Africa suggests that the recent decadal storage declines should not impact the regional aquifers but may affect local conditions. Increasing groundwater levels in western Africa will need to be managed because of locally rising groundwater flooding. More climate resilient water management can be accomplished in eastern and southern Africa by storing water from wet to dry climate cycles. Accessing the natural water storage provided by aquifers in Africa is the obvious way to manage the variability between droughts and floods.

Africa water storage↗

NASA NTRS2017

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

evapotranspiration↗

NASA NTRS1994

Mean motions and tidal and two-day structure and variability in the mesosphere and lower thermosphere over Hawaii

An overview of the motion field and an analysis of the tidal and 2-day wave motions observed in the mesosphere and lower thermosphere over the central Pacific from 1 October 1990 through 19 August 1992 is presented. Characteristics and interactions of motions at lower and higher frequencies will be addressed elsewhere. Wind measurements were obtained with an MF radar operating on Kauai, Hawaii (22 deg N, 160 deg W), using the partial reflection drift technique. Results presented in this paper reveal a zonal mean motion reflecting the mesopause semiannual oscillation (MSAO) observed at more equatorial latitudes from approximately January to July, coinciding with the period during which the MSAO and the annual cycle of the zonal mean wind at higher latitudes are in phase. Eastward and westward maxima are 55 m/s below 80 km and 45 m/s near 85 km during the first year, with maxima of 57 and 53 m/s during the second year and evidence of substantial interannual variability. The second MSAO cycle is greatly suppressed in the Hawaiian data due to the reversal of the correlation between this and the annual cycle at higher latitudes from approximately July to December and because the second cycle is weaker climatologically at equatorial latitudes. Significant planetary wave activity is observed during periods of mean eastward motions, and tidal and 2-day motions are found to be large and variable. The maximum diurnal tides were observed during October and November 1990, and February, March, April, July, and August of 1991 and 1992. Maximum 2-day amplitudes occurred during February, July, and August of 1991 and 1992. Significantly, the large diurnal amplitude maximum noted during November 1990 failed to appear the following year, while the February 2-day amplitude maximum declined somewhat in 1992.

Fritts, David C.↗

NASA NTRS2013

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data: 1. an EOF Approach to the Spatial-Temporal Variability of Aerosol Optical Depth Using Multiple Remote Sensing Data Sets

Many remote sensing techniques and passive sensors have been developed to measure global aerosol properties. While instantaneous comparisons between pixel-level data often reveal quantitative differences, here we use Empirical Orthogonal Function (EOF) analysis, also known as Principal Component Analysis, to demonstrate that satellite-derived aerosol optical depth (AOD) data sets exhibit essentially the same spatial and temporal variability and are thus suitable for large-scale studies. Analysis results show that the first four EOF modes of AOD account for the bulk of the variance and agree well across the four data sets used in this study (i.e., Aqua MODIS, Terra MODIS, MISR, and SeaWiFS). Only SeaWiFS data over land have slightly different EOF patterns. Globally, the first two EOF modes show annual cycles and are mainly related to Sahara dust in the northern hemisphere and biomass burning in the southern hemisphere, respectively. After removing the mean seasonal cycle from the data, major aerosol sources, including biomass burning in South America and dust in West Africa, are revealed in the dominant modes due to the different interannual variability of aerosol emissions. The enhancement of biomass burning associated with El Niño over Indonesia and central South America is also captured with the EOF technique.

variability↗

NASA NTRS2004

The Remarkable 2003-2004 Winter and Other Recent Warm Winters in the Arctic Stratosphere Since the Late 1990s

The 2003-2004 Arctic winter was remarkable in the 40-year record of meteorological analyses. A major warming beginning in early January 2004 led to nearly two months of vortex disruption with high-latitude easterlies in the middle to lower stratosphere. The upper stratospheric vortex broke up in late December, but began to recover by early January, and in February and March was the strongest since regular observations began in 1979. The lower stratospheric vortex broke up in late January. Comparison with two previous years, 1984-1985 and 1986-1987, with prolonged mid-winter warming periods shows unique characteristics of the 2003-2004 warming period: The length of the vortex disruption, the strong and rapid recovery in the upper stratosphere, and the slow progression of the warming from upper to lower stratosphere. January 2004 zonal mean winds in the middle and lower stratosphere were over two standard deviations below average. Examination of past variability shows that the recent frequency of major stratospheric warmings (seven in the past six years) is unprecedented. Lower stratospheric temperatures were unusually high during six of the past seven years, with five having much lower than usual potential for PSC formation and ozone loss (nearly none in 1998-1999, 2001-2002 and 2003-2004, and very little in 1997-1998 and 2000-2001). Middle and upper stratospheric temperatures, however, were unusually low during and after February. The pattern of five of the last seven years with very low PSC potential would be expected to occur randomly once every approximately 850 years. This cluster of warm winters, immediately following a period of unusually cold winters, may have important implications for possible changes in interannual variability and for determination and attribution of trends in stratospheric temperatures and ozone.

Manney, Gloria L.↗

DOE OSTI2022

Tropical extreme droughts drive long-term increase in atmospheric CO 2 growth rate variability

The terrestrial carbon sink slows the accumulation of carbon dioxide (CO 2 ) in the atmosphere by absorbing roughly 30% of anthropogenic CO 2 emissions, but varies greatly from year to year. The resulting variations in the atmospheric CO 2 growth rate (CGR) have been related to tropical temperature and water availability. The apparent sensitivity of CGR to tropical temperature ( ${{{{{{\rm{\gamma }}}}}}}_{{{{{{\rm{CGR}}}}}}}^{{{{{{\rm{T}}}}}}}$ ) has changed markedly over the past six decades, however, the drivers of the observation to date remains unidentified. Here, we use atmospheric observations, multiple global vegetation models and machine learning products to analyze the cause of the sensitivity change. We found that a threefold increase in ${{{{{{\rm{\gamma }}}}}}}_{{{{{{\rm{CGR}}}}}}}^{{{{{{\rm{T}}}}}}}$ emerged due to the long-term changes in the magnitude of CGR variability (i.e., indicated by one standard deviation of CGR; STD CGR ), which increased 34.7% from 1960-1979 to 1985-2004 and subsequently decreased 14.4% in 1997-2016. We found a close relationship (r 2 = 0.75, p < 0.01) between STD CGR and the tropical vegetated area (23°S – 23°N) affected by extreme droughts, which influenced 6-9% of the tropical vegetated surface. A 1% increase in the tropical area affected by extreme droughts led to about 0.14 Pg C yr -1 increase in STD CGR . The historical changes in STD CGR were dominated by extreme drought-affected areas in tropical Africa and Asia, and semi-arid ecosystems. The outsized influence of extreme droughts over a small fraction of vegetated surface amplified the interannual variability in CGR and explained the observed long-term dynamics of ${{{{{{\rm{\gamma }}}}}}}_{{{{{{\rm{CGR}}}}}}}^{{{{{{\rm{T}}}}}}}$ .

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2023

Aura/MLS Observes and SD-WACCM-X Simulates the Seasonality, Quasi-Biennial Oscillation and El Niño-Southern Oscillation of the Migrating Diurnal Tide Driving Upper Mesospheric CO Primarily Through Vertical Advection

This work uses 17 years of upper mesospheric carbon monoxide (CO) and temperature observations by the Microwave Limb Sounder (MLS) on-board the Aura satellite to present and explain the seasonal and interannual variability of the migrating diurnal tide (DW1) component of upper mesospheric CO. This work then compares these observations to simulations by the Specified Dynamics – Whole Atmosphere Community Climate Model with Ionosphere/Thermosphere eXtension (SD-WACCM-X). Results show that, for all seasons, MLS CO local-time perturbations peaks above 85 km and has a latitude structure resembling the (1,1) mode in temperature. On the other hand, SD-WACCM-X DW1 also peaks above 85 km and has a latitude structure resembling the (1,1) mode but it simulates 2 local maximum of the (1,1) mode between 85 km and 92 km. Despite the differences in altitude structure, a tendency analysis and the adiabatic displacement method revealed that, on seasonal and interannual timescales, observed and modelled CO’s (1,1) component can be reproduced solely using vertical advection. It was also found that both observed and modelled CO’s (1,1) component contains interannual oscillations with periodicities close to that of the Quasi-biennial Oscillation and the El Niño–Southern Oscillation. From these results, this work concludes that on seasonal and interannual timescales, the observed and modelled (1,1) mode affects the global structure of upper mesospheric CO primarily through vertical advection.

Cornelius Csar Jude H Salinas↗

NASA NTRS2023

Aura/MLS Observes, and SD-WACCM-X Simulates the Seasonality, Quasi-Biennial Oscillation and El Nino Southern Oscillation of the Migrating Diurnal Tide Driving Upper Mesospheric Co Primarily Through Vertical Advection

This work uses 17 years of upper mesospheric carbon monoxide (CO) and temperature observations by the Microwave Limb Sounder (MLS) on-board the Aura satellite to present and explain the seasonal and interannual variability of the migrating diurnal tide (DW1) component of upper mesospheric CO. This work then compares these observations to simulations by the Specified Dynamics – Whole Atmosphere Community Climate Model with Ionosphere/Thermosphere eXtension (SD-WACCM-X). Results show that, for all seasons, MLS CO local-time perturbations peaks above 85 km and has a latitude structure resembling the (1,1) mode in temperature. On the other hand, SD-WACCM-X DW1 also peaks above 85 km and has a latitude structure resembling the (1,1) mode but it simulates 2 local maximum of the (1,1) mode between 85 km and 92 km. Despite the differences in altitude structure, a tendency analysis and the adiabatic displacement method revealed that, on seasonal and interannual timescales, observed and modelled CO’s (1,1) component can be reproduced solely using vertical advection. It was also found that both observed and modelled CO’s (1,1) component contains interannual oscillations with periodicities close to that of the Quasi-biennial Oscillation and the El Nino Southern Oscillation. From these results, this work concludes that on seasonal and interannual timescales, the observed and modelled (1,1) mode affects the global structure of upper mesospheric CO primarily through vertical advection.

Cornelius Csar Jude H. Salinas↗

NASA NTRS2005

The Remarkable 2003--2004 Winter and Other Recent Warm Winters in the Arctic Stratosphere Since the Late 1990s

The 2003-2004 Arctic winter was remarkable in the approximately 50-year record of meteorological analyses. A major warming beginning in early January 2004 led to nearly 2 months of vortex disruption with high-latitude easterlies in the middle to lower stratosphere. The upper stratospheric vortex broke up in late December, but began to recover by early January, and in February and March was the strongest since regular observations began in 1979. The lower stratospheric vortex broke up in late January. Comparison with 2 previous years, 1984-1985 and 1986-1987, with prolonged midwinter warming periods shows unique characteristics of the 2003-2004 warming period: The length of the vortex disruption, the strong and rapid recovery in the upper stratosphere, and the slow progression of the warming from upper to lower stratosphere. January 2004 zonal mean winds in the middle and lower stratosphere were over 2 standard deviations below average. Examination of past variability shows that the recent frequency of major stratospheric warmings (7 in the past 6 years) is unprecedented. Lower stratospheric temperatures were unusually high during 6 of the past 7 years, with 5 having much lower than usual potential for polar stratospheric cloud (PSC) formation and ozone loss (nearly none in 1998-1999, 2001-2002, and 2003-2004, and very little in 1997-1998 and 2000-2001). Middle and upper stratospheric temperatures, however, were unusually low during and after February. The pattern of 5 of the last 7 years with very low PSC potential would be expected to occur randomly once every 850 years. This cluster of warm winters, immediately following a period of unusually cold winters, may have important implications for possible changes in interannual variability and for determination and attribution of trends in stratospheric temperatures and ozone.

ozone↗

NASA NTRS2003

Martian Atmospheric Circulation and Climate

This proposal is focused on using Mars Global Surveyor (MGS) data and numerical models to address issues of atmospheric mixing of volatiles and aerosols, on defining the mean state of the atmosphere and the degree of variability, and on the processes which exchange volatiles and aerosols between the surface and atmosphere. Specifically, five areas of research were defined: In the first, we proposed to use TES data to examine the general circulation of the atmosphere both through retrieval of the residual circulation, and by comparison of the TES data with a Mars General Circulation Model (GCM). In the second, we proposed to look at synoptic and mesoscale atmospheric mixing processes (baroclinic storms, etc.) by combining TES and MOC Wide Angle data, and by employing a Mars Mesoscale Model. In the third section, we proposed to examine the record of the Martian atmospheric state provided by MGS, Viking, and Mariner 9 - as well as published ground-based observations - in order to assess the nature of interannual variability. In the forth section, we proposed to compare numerical models of the Martian water and dust cycles with TES and MOC data, specifically looking at water ice cloud distributions, dust distribution, etc. In the fifth section, we propose to use the mesoscale model to study the Mars Pathfinder Lander data. This work has now concluded its final of three years.

Ingersoll, Andrew P.↗

DOE OSTI2023

Climate-driven changes in the predictability of seasonal precipitation

Climate-driven changes in precipitation amounts and their seasonal variability are expected in many continental-scale regions during the remainder of the 21st century. However, much less is known about future changes in the predictability of seasonal precipitation, an important earth system property relevant for climate adaptation. Here, on the basis of CMIP6 models that capture the present-day teleconnections between seasonal precipitation and previous-season sea surface temperature (SST), we show that climate change is expected to alter the SST-precipitation relationships and thus our ability to predict seasonal precipitation by 2100. Specifically, in the tropics, seasonal precipitation predictability from SSTs is projected to increase throughout the year, except the northern Amazonia during boreal winter. Concurrently, in the extra-tropics predictability is likely to increase in central Asia during boreal spring and winter. The altered predictability, together with enhanced interannual variability of seasonal precipitation, poses new opportunities and challenges for regional water management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Fusion of Multiple Models for Improving Gross Primary Production Estimation With Eddy Covariance Data Based on Machine Learning

Abstract Terrestrial gross primary production (GPP) represents the magnitude of CO 2 uptake through vegetation photosynthesis, and is a key variable for carbon cycles between the biosphere and atmosphere. Light use efficiency (LUE) models have been widely used to estimate GPP for its physiological mechanisms and availability of data acquisition and implementation, yet each individual GPP model has exhibited large uncertainties due to input errors and model structure, and further studies of systematic validation, comparison, and fusion of those models with eddy covariance (EC) site data across diverse ecosystem types are still needed in order to further improve GPP estimation. We here compared and fused five GPP models (VPM, EC‐LUE, GOL‐PEM, CHJ, and C‐Fix) across eight ecosystems based on FLUXNET2015 data set using the ensemble methods of Bayesian Model Averaging (BMA), Support Vector Machine (SVM), and Random Forest (RF) separately. Our results showed that for individual models, EC‐LUE gave a better performance to capture interannual variability of GPP than other models, followed by VPM and GLO‐PEM, while CHJ and C‐Fix were more limited in their estimation performance. We found RF and SVM were superior to BMA on merging individual models at various plant functional types (PFTs) and at the scale of individual sites. On the basis of individual models, the fusion methods of BMA, SVM, and RF were examined by a five‐fold cross validation for each ecosystem type, and each method successfully improved the average accuracy of estimation by 8%, 18%, and 19%, respectively.

Environmental Sciences & Ecology↗