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Detecting forest structure and biomass with C-band multipolarization radar - Physical model and field tests

The ability of C-band radar (4.75 GHz) to discriminate features of forest structure, including biomass, is tested using a truck-mounted scatterometer for field tests on a 1.5-3.0 m pygmy forest of cypress (Cupressus pygmaea) and pine (Pinus contorta ssp, Bolanderi) near Mendocino, CA. In all, 31 structural variables of the forest are quantified at seven sites. Also measured was the backscatter from a life-sized physical model of the pygmy forest, composed of nine wooden trees with 'leafy branches' of sponge-wrapped dowels. This model enabled independent testing of the effects of stem, branch, and leafy branch biomass, branch angle, and moisture content on radar backscatter. Field results suggested that surface area of leaves played a greater role in leaf scattering properties than leaf biomass per se. Tree leaf area index was strongly correlated with vertically polarized power backscatter (r = 0.94; P less than 0.01). Field results suggested that the scattering role of leaf water is enhanced as leaf surface area per unit leaf mass increases; i.e., as the moist scattering surfaces become more dispersed. Fog condensate caused a measurable rise in forest backscatter, both from surface and internal rises in water content. Tree branch mass per unit area was highly correlated with cross-polarized backscatter in the field (r = 0.93; P less than 0.01), a result also seen in the physical model.

Westman, Walter E.↗

Comparison of cloud microphysical parameters derived from surface and satellite measurements during FIRE phase 2

Cloud microphysical properties are an important component in climate model parameterizations of water transport, cloud radiative exchange, and latent heat processes. Estimation of effective cloud particle size, liquid or ice water content, and optical depth from satellite-based instrumentation is needed to develop a climatology of cloud microphysical properties and to better understand and model cloud processes in atmospheric circulation. These parameters are estimated from two different surface data sets taken at Coffeyville, Kansas, during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (November 13 - December 7, 1991). Satellite data can also provide information about optical depth and effective particle size. This paper explores the combination of the FIRE-2 surface and satellite data to determine each of the cloud microphysical properties.

Young, David F.↗

Calbindins decreased after space flight

Exposure of the body to microgravity during space flight causes a series of well-documented changes in Ca2+ metabolism, yet the cellular and molecular mechanisms leading to these changes are poorly understood. Calbindins, vitamin D-dependent Ca2+ binding proteins, are believed to have a significant role in maintaining cellular Ca2+ homeostasis. In this study, we used biochemical and immunocytochemical approaches to analyze the expression of calbindin-D28k and calbindin-D9k in kidneys, small intestine, and pancreas of rats flown for 9 d aboard the space shuttle. The effects of microgravity on calbindins in rats from space were compared with synchronous Animal Enclosure Module controls, modeled weightlessness animals (tail suspension), and their controls. Exposure to microgravity resulted in a significant and sustained decrease in calbindin-D28k content in the kidney and calbindin-D9k in the small intestine of flight animals, as measured by enzyme-linked immunosorbent assay (ELISA). Modeled weightlessness animals exhibited a similar decrease in calbindins by ELISA. Immunocytochemistry (ICC) in combination with quantitative computer image analysis was used to measure in situ the expression of calbindins in the kidney and the small intestine, and the expression of insulin in pancreas. There was a large decrease of immunoreactivity in renal distal tubular cell-associated calbindin-D28k and in intestinal absorptive cell-associated calbindin-D9k of space flight and modeled weightlessness animals compared with matched controls. No consistent difference in pancreatic insulin immunoreactivity between space flight, modeled weightlessness, and controls was observed. Regression analysis of results obtained by quantitative ICC and ELISA for space flight, modeled weightlessness animals, and their controls demonstrated a significant correlation. These findings after a short-term exposure to microgravity or modeled weightlessness suggest that a decreased expression of calbindins may contribute to the disorders of Ca2+ metabolism induced by space flight.

Non-NASA Center↗

Buckets: Smart Objects for Digital Libraries

Current discussion of digital libraries (DLs) is often dominated by the merits of the respective storage, search and retrieval functionality of archives, repositories, search engines, search interfaces and database systems. While these technologies are necessary for information management, the information content is more important than the systems used for its storage and retrieval. Digital information should have the same long-term survivability prospects as traditional hardcopy information and should be protected to the extent possible from evolving search engine technologies and vendor vagaries in database management systems. Information content and information retrieval systems should progress on independent paths and make limited assumptions about the status or capabilities of the other. Digital information can achieve independence from archives and DL systems through the use of buckets. Buckets are an aggregative, intelligent construct for publishing in DLs. Buckets allow the decoupling of information content from information storage and retrieval. Buckets exist within the Smart Objects and Dumb Archives model for DLs in that many of the functionalities and responsibilities traditionally associated with archives are pushed down (making the archives dumber) into the buckets (making them smarter). Some of the responsibilities imbued to buckets are the enforcement of their terms and conditions, and maintenance and display of their contents.

Nelson, Michael L.↗

Microwave backscattering and emission model for grass canopies

A two-layer model is developed that treats the grass canopy as a collection of randomly oriented elliptical dielectric discs over a layer of thatch with underlying soil surface. The distorted Born approximation in conjunction with the Peake formulation is used to calculate the backscattering coefficient and the emissivity from the canopy. Two particular features of this model which are unique for grass canopies are the variation of the canopy structure and the presence of the thatch layer. The basic parameters in the model such as the size and orientation of grass blades, dielectric constant of soil and vegetation, and thickness and water content of the thatch layer have been obtained from ground truth data. To interpret the available experimental observations of grasslands, numerical results from both passive and active models at L-band (1.4 GHz) are generated and various scattering and emission properties of the grass canopies are discussed.

Saatchi, Sasan S.↗

Connecting Paleo and Modern Oceanographic Data to Understand Atlantic Meridional Overturning Circulation Over Decades to Centuries

Modeling is an important tool for understanding AMOC on all timescales. Mechanistic studies of modern AMOC variability have been hampered by a lack of consistency between free-running models and the sensitivity of AMOC to resolution and parameterization. Recent work within the framework of the phase two Coordinated Ocean- Reference Experiments (CORE-II) addresses this issue head on, looking at model differences of AMOC mean state and interannual variability. One consistent feature across the models is that AMOC mean transport is related to mixed layer depths and Labrador Sea salt content, whereas interannual variability is primarily associated with Labrador Sea temperature anomalies. This is consistent with the hypothesized importance of salt balance for AMOC variability on geological timescales. The simulated relationships between AMOC and subsurface temperature anomalies in fully coupled climate models reveal subsurface AMOC fingerprints that could be used to reconstruct historical AMOC variations at low frequency.With the lack of long-term AMOC observations, models of ocean state that assimilate observational data have been explored as a way to reconstruct AMOC, but comparisons between models indicate they are quite variable in their AMOC representations. Karspeck et al. (2015) found that historical reconstructions of AMOC in such models are sensitive to the details of the data assimilation procedure. The ocean data assimilation community continues to address these issues through improved models and methods for estimating and representing error information.Two objectives of paleoclimate modeling are 1) to provide mechanistic information for interpretation of paleoclimate observations, and 2) to test the ability of predictive models to simulate Earth's climate under different background forcing states. In a good example of the first objective, Schmittner and Lund (2015) and Menviel et al. (2014) provided key information about the proxy signals expected under freshwater disturbance of AMOC, which were used to support the paleoclimate observations made by Henry et al. (2016). In an example of the second objective, Muglia and Schmittner (2015) analyzed Third Paleoclimate Modeling Intercomparison Project (PMIP3) models of the Last Glacial Maximum (LGM) and found consistently more intense and deeper AMOC transports relative to preindustrial simulations, counter to the paleoclimate consensus of LGM conditions, indicating that some processes are not well represented in the PMIP3 models. One challenge is to find adequate paleo observations against which to test these models. PMIP is now in phase 4 (part of CMIP6), which includes experiments covering five periods in Earth's history: the last millennium, last glacial maximum, last interglacial, and the mid-Pliocene. Newly compiled paleoclimate datasets from the PAGES2k project, more transient simulations, and participation of isotope enabled models planned for CMIP6PMIP4 will enable richer paleo data-model comparisons in the near future.

Kilbourne, Hali↗

Reionization in a cold dark matter universe: The feedback of galaxy formation on the intergalactic medium

We study the coupled evolution of the intergalactic medium (IGM) and the emerging structure in the universe in the context of the cold dark matter (CDM) model, with a special focus on the consequences of imposing reionization and the Gunn-Peterson constraint as a boundary condition on the model. We have calculated the time-varying density of the IGM by coupling our detailed, numerical calculations of the thermal and ionization balance and radiative transfer in a uniform, spatially averaged IGM of H and He, including the mean opacity of an evolving distribution of gas clumps which correspond to quasar absorption line clouds, to the linearized equations for the growth of density fluctuations in both the gaseous and dark matter components in a CDM universe. We use the linear growth equations to identify the fraction of the gas which must have collapsed out at each epoch, an approach similar in spirit to the so-called Press-Schechter formalism. We identify the IGM density with the uncollapsed baryon fraction. The collapsed fraction is postulated to be a source of energy injection into the IGM, by radiation or bulk hydrodynamical heating (e.g., via shocks) or both, at a rate which is marginally enough to satisfy the Gunn-Peterson constraint at z less than 5. Our results include the following: (1) We find that the IGM in a CDM model must have contained a substantial fraction of the total baryon density of the universe both during and after its reionization epoch. (2) As a result, our previous conclusion that the observed Quasi-Stellar Objects (QSOs) at high redshift are not sufficient to ionize the IGM enough to satisfy the Gunn-Peterson constraint is confirmed. (3) We predict a detectable He II Gunn-Peterson effect at 304(1 + z) A in the spectra of quasars at a range of redshift z greater than or approx. 3, depending on the nature of the sources of IGM reionization. (4) We find, moreover, that a CDM model with high bias parameter b (i.e., b greater than or approx. 2) cannot account for the baryon content of the universe at z approximately 3 observed in quasar absorption line gas unless Omega (sub B) significantly exceeds the maximum value allowed by big bang nucleocynthesis. (5) For a CDM model with bias parameter within the allowed range of (lower) values, the lower limit to Omega(sub B) imposed by big bang nucleosynthesis (Omega(sub B) h(sup 2) greater than or equal to 0.01) combines with our results to yield the minimum IGM density for the CDM fodel. For CDM with b = 1 (Cosmic Background Explorer (COBE) normalization), we find Omega(sub IGM)(sup min) (z approximately 4) approx. equal 0.02-0.03, and Omega(sub IGM)(sup min)(z approximately 0) approx. equal 0.005-0.03, depending upon the nature of the sources of IGM reionization. (6) In general, we find that self-consistent reionization of the IGM by the collapsed baryon fraction has a strong effect on the rate of collapse. (7) As a further example, we show that the feedback effect on the IGM of energy release by the collapsed baryon fraction may explain the slow evolution of the observed comoving QSO number density between z = 5 and z = 2, followed by the sharp decline after z = 2.

Shapiro, Paul R.↗

Data Science for Weather Impacts on Crop Yield

Private businesses in sectors, such as food, energy, and retail, as well as public sector and federal agencies are interested in the predictive understanding of weather impacts on crop yield, which is an important aspect of food security. Scientific literature has mainly examined how crop yield is impacted by growing season-averaged weather indices. Although a few studies did consider weather extremes in their analysis, their scope was either restricted to measuring their conditional relationship with yield or the extreme event types considered were limited. Selection of regression models, whether the more commonly used linear approaches or nonlinear methods, have not been appropriately justified in this context. Here, we develop data-driven methods to examine two inter-related hypotheses for improved scientific understanding and enhanced predictive modeling. The first hypothesis, that extreme weather indices have a statistically significant information content in them is found to be valid based on linear and nonlinear methods for pairwise dependence. The second hypothesis, examines the value addition of nonlinear regression methods, and suggests that linear approaches may not alone be adequate. The results of this study can inform scientific understanding, generation and relevance of indices and end-to-end risk assessment systems in the context of climate impacts on crop yield. An immediate application may be in the context of NASA Earth Exchange (NEX) which facilitates the generation and dissemination of impacts relevant weather data and indices using a multitude of satellite-derived data sets and model outputs.

Data mining, food security, weather impacts↗

Electrical Resistance of SiC/SiC Ceramic Matrix Composites for Damage Detection and Life-Prediction

Ceramic matrix composites (CMC) are suitable for high temperature structural applications such as turbine airfoils and hypersonic thermal protection systems due to their low density high thermal conductivity. The employment of these materials in such applications is limited by the ability to accurately monitor and predict damage evolution. Current nondestructive methods such as ultrasound, x-ray, and thermal imaging are limited in their ability to quantify small scale, transverse, in-plane, matrix cracks developed over long-time creep and fatigue conditions. CMC is a multifunctional material in which the damage is coupled with the material s electrical resistance, providing the possibility of real-time information about the damage state through monitoring of resistance. Here, resistance measurement of SiC/SiC composites under mechanical load at both room temperature monotonic and high temperature creep conditions, coupled with a modal acoustic emission technique, can relate the effects of temperature, strain, matrix cracks, fiber breaks, and oxidation to the change in electrical resistance. A multiscale model can in turn be developed for life prediction of in-service composites, based on electrical resistance methods. Results of tensile mechanical testing of SiC/SiC composites at room and high temperatures will be discussed. Data relating electrical resistivity to composite constituent content, fiber architecture, temperature, matrix crack formation, and oxidation will be explained, along with progress in modeling such properties.

Smith, Craig↗

VESIcal: A Critical Approach to Volatile Solubility Modelling Using the Open-Source Engine Vesical

Accurate models of H(2)O and CO(2) solubility in silicate melts are vital for understanding volcanic plumbing systems. These models are used to estimate the depths of magma storage regions from melt inclusion volatile contents, investigate the role of volatile exsolution as a driver of volcanic eruptions, and track the degassing path followed by a magma ascending to the surface. However, despite the large increase in the number of experimental constraints over the last two decades, many recent studies still utilize an earlier generation of models which were calibrated on experimental datasets with restricted compositional ranges. This may be because many of the available tools for more recent models require large numbers of input parameters to be hand-typed (e.g., temperature, concentrations of H(2)O, CO(2), and 8–14 oxides), making them difficult to implement on large datasets. Here, we use a new open-source Python3 tool, VESIcal, to critically evaluate the behaviors and sensitivities of different solubility models for a range of melt compositions. Using literature datasets of andesitic-dacitic experimental products and melt inclusions as case studies, we illustrate the importance of evaluating the calibration dataset of each model. Finally, we highlight the limitations of particular data presentation methods, such as isobar diagrams, and provide suggestions for alternatives, and best practices regarding the presentation and archiving of data. This review will aid the selection of the most applicable solubility model for different melt compositions, and identifies areas where additional experimental constraints on volatile solubility are required.

magma↗

Ionospheric electron content prediction from SERIES/GPS data

Total electron contents along arbitrary lines-of-sight are derived from dual band SERIES P-code data. At present, in a normal observing session, five Global Positioning Satellites (GPS) can be observed for a time interval of 5 h. A SERIES observing session consists of about 300 line-of-sight measurements. Transmitter offsets are different for each satellite and no reliable a priori data can be obtained at present. The electron content and the satellite offsets are estimated simultaneously by a least squares procedure using a simple empirical model. The present accuracy of this technique is estimated to be 6 x 10 to the 16th el/sq m. The results are compared with Faraday rotation measurements. The method may be used for local or global ionospheric content monitoring.

Lanyi, Gabor↗

In Situ Trace Element Measurements on Roda and the Origin of Diogenites

The origin of diogenites remains poorly understood. A recent model interprets many diogenites to have been formed from melts that were derived by remelting initial magma ocean cumulates, and these penultimate parent melts were then contaminated by melts derived from remelting of the basaltic (eucritic) crust to form the ultimate diogenite parent melts [1] (hereafter the remelting model). This is a very complicated petrogenesis that has profound implications for the geological evolution of 4 Vesta if correct. This model was developed based on trace element analyses of bulk rock samples that had been leached in acids to remove phosphates; the compositions of the residues were interpreted to be close to those of cumulus orthopyroxenes plagioclase, chromite and olivine [1]. In situ measurements of phases in diogenites can be used to test this model. We have begun a campaign of laser ablation ICP-MS of orthopyroxene grains in diogenites for this purpose. Here we report our first results on one diogenite, Roda. We have determined a suite of trace lithophile elements on nine, mm-sized pyroxene grains separated from Roda that have previously been studied [2, 3]. A key observation supporting the remelting model is the very low Eu/Eu* of leached residues; values too low to represent orthopyroxene that crystallized from melts with chondritic Sm/Eu and Gd/Eu [1]. (Eu* = Eu interpolated from REE diagrams.) Crustal remelts have low Sm/Eu and Gd/Eu, and orthopyroxenes that crystallized from parent melts contaminated by them would have very low Eu/Eu* [1]. Roda grains have Eu/Eu* of 0.243 to 0.026; the latter a value lower than any measured on bulk diogenite leached residues (0.041) [1]. There is a general negative correlation between Eu/Eu* and some incompatible elements (Zr, Nb, Hf), but not others (LREE). This appears inconsistent with the remelting model as it would suggest an evolving parent melt with La de-creasing as Zr increased and Eu/Eu* decreased. Grain R-15 includes trace-element-rich trapped melt phases [2, 3]. This grain has the highest Eu/Eu* and LREE contents, indicating that the trapped melt had a high Eu/Eu*. Thus, our first data on one diogenite do not provide support for the remelting model [1]. Roda is unusual in that its orthopyroxene grains show wide ranges in trace element contents [4]. Previous in situ REE analyses of grain R-15 did not reveal evidence for subsolidus equilibration with trace-element-rich trapped melt phases, and led to the suggestion that Roda may be polymict, with different grains representing different lithologies of diverse compositions [3]. Thus, based on our results on Roda, it is perhaps premature to abandon the remelting model. In situ measurements on a suite of diogenites is planned to further address this issue.

Mittlefehldt, David W.↗

The viscosity of magmatic silicate liquids: A model for calculation

A simple model has been designed to allow reasonably accurate calculations of viscosity as a function of temperature and composition. The problem of predicting viscosities of anhydrous silicate liquids has been investigated since such viscosity numbers are applicable to many extrusive melts and to nearly dry magmatic liquids in general. The fluidizing action of water dissolved in silicate melts is well recognized and it is now possible to predict the effect of water content on viscosity in a semiquantitative way. Water was not incorporated directly into the model. Viscosities of anhydrous compositions were calculated, and, where necessary, the effect of added water and estimated. The model can be easily modified to incorporate the effect of water whenever sufficient additional data are accumulated.

Bottinga, Y.↗

Evidence for Harmonic Content and Frequency Evolution of Oscillations During the Rising Phase of X-ray Bursts From 4U 1636-536

We report on a study of the evolution of burst oscillation properties during the rising phase of X-ray bursts from 4U 1636-536 observed with the proportional counter array (PCA) on board the Rossi X-Ray Timing Explorer (RXTE) . We present evidence for significant harmonic structure of burst oscillation pulses during the early rising phases of bursts. This is the first such detection in burst rise oscillations, and is very important for constraining neutron star structure parameters and the equation of state models of matter at the core of a neutron star. The detection of harmonic content only during the initial portions of the burst rise is consistent with the theoretical expectation that with time the thermonuclear burning region becomes larger, and hence the fundamental and harmonic amplitudes both diminish. We also find, for the first time from this source, strong evidence of oscillation frequency increase during the burst rise. The timing behavior of harmonic content, amplitude, and frequency of burst rise oscillations may be important in understanding the spreading of thermonuclear flames under the extreme physical conditions on neutron star surfaces.

Bgattacharyya, Sudip↗

An Investigation into the Effect of Liquid Accumulation on Thermo-Physiologic State using an Advanced Moisture Model Coupled with a High Resolution Human Thermal Model

A physics-based mathematical model for simulating heat and moisture transport on the skin and within clothing was developed to improve the accuracy of human thermal modeling predictions. In a previous study, a set of sweating hotplate experiments was specifically created to obtain test data for model validation. The clothing moisture model was subsequently coupled with a human thermal model and tested by simulating human experiments described in the open literature, which served to verify the model’s ability to predict whole body thermo-physiologic state in work-rest cycles during which sweating was known to occur. In this study, a human subject test was specifically designed to validate the model’s ability to predict local and whole body sweat evaporation and accumulation on the surface of the body. The human subject test incorporated twelve clothed male subjects of moderate physical fitness, ages 18-30, which were prescribed a work-rest cycle in a climate-controlled chamber (25 °C, 50% RH). Two activity levels were considered during the active stage (4 MET vs. 6.5 MET), and two sets of ending ambient conditions were considered for the final rest stage (25 °C vs. 15 °C, 50% RH). Model predictions were compared to the measured local skin temperatures, core temperatures, and whole body sweat losses. In general, the model was able to reproduce the trends observed in the human subject trial, but more importantly, provided insight into how dynamic changes in liquid content can impact the evolution of local and whole body thermo-physiologic state. This study demonstrates the ability of an advanced moisture model to capture distinct physics attributable to moisture accumulation, allowing for increased accuracy in predicting human thermal state and for interpreting the results of measurements derived from human subject tests.

human thermal model↗

Magma Ocean Evolution of the TRAPPIST-1 Planets

Recent observations of the potentially habitable planets TRAPPIST-1 e, f, and g suggest that they possess large water mass fractions of possibly several tens of wt% of water, even though the host star’s activity should drive rapid atmospheric escape. These processes can photolyze water, generating free oxygen and possibly desiccating the planet. After the planets formed, their mantles were likely completely molten with volatiles dissolving and exsolving from the melt. In order to understand these planets and prepare for future observations, the magma ocean phase of these worlds must be understood. To simulate these planets, we have combined existing models of stellar evolution, atmospheric escape, tidal heating, radiogenic heating, magma ocean cooling, planetary radiation, and water-oxygen-iron geochemistry. We present Magm Oc, a versatile magma ocean evolution model, validated against the rocky Super-Earth GJ 1132b and early Earth. We simulate the coupled magma ocean-atmospheric evolution of TRAPPIST-1 e, f, and g for a range of tidal and radiogenic heating rates, as well as initial water contents between 1 and 100 Earth oceans. We also reanalyze the structures of these planets and find they have water mass fractions of 0–0.23, 0.01–0.21, and 0.11–0.24 for planets e, f, and g, respectively. Our model does not make a strong prediction about the water and oxygen content of the atmosphere of TRAPPIST-1 e at the time of mantle solidification. In contrast, the model predicts that TRAPPIST-1 f and g would have a thick steam atmosphere with a small amount of oxygen at that stage. For all planets that we investigated, we find that only 3 ́5% of the initial water will be locked in the mantle after the magma ocean solidified.

Exoplanets↗

Analyzing Contents of a Computer Cache

The Cache Contents Estimator (CCE) is a computer program that provides information on the contents of level-1 cache of a PowerPC computer. The CCE is configurable to enable simulation of any processor in the PowerPC family. The need for CCE arises because the contents of level-1 caches are not available to either hardware or software readout mechanisms, yet information on the contents is crucial in the development of fault-tolerant or highly available computing systems and for realistic modeling and prediction of computing- system performance. The CCE comprises two independent subprograms: (1) the Dynamic Application Address eXtractor (DAAX), which extracts the stream of address references from an application program undergoing execution and (2) the Cache Simulator (CacheSim), which models the level-1 cache of the processor to be analyzed, by mimicking what the cache controller would do, in response to the address stream from DAAX. CacheSim generates a running estimate of the contents of the data and the instruction subcaches of the level-1 cache, hit/miss ratios, the percentage of cache that contains valid or active data, and time-stamped histograms of the cache content.

Beahan, John↗

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.

Crop simulation model↗