Impact Of Interannual Variability Research Articles

Exploring backup requirements to complement wind, solar and hydro generation in a highly renewable Spanish power system

A weather-driven model is used to investigate the requirements for the backup generation (annual energy, power capacity and flexibility) in a power system with different penetrations of wind, solar photovoltaics, and hydroelectricity. The impact of interannual variability is assessed by using 26 years of weather data. The flexibility needed for the backup generation is found to be higher as the solar penetration increases since ramps caused by sunrises and sunsets are more significant than those caused by hour-to-hour wind fluctuations. The model is applied to the Spanish power system and two dispatch strategies for reservoir hydro and pumped hydro storage are evaluated. The currently installed gas power capacity is found to be sufficient to secure hourly demand for high renewable penetration.

Robust design of a future 100% renewable european energy supply system with hydrogen infrastructure

Variable renewable energy sources (VRES) will be the cornerstones of future energy supply systems. Nevertheless, their inherent intermittency remains an obstacle to their widespread deployment. Renewably-produced or ‘green’ hydrogen has been suggested as an energy carrier that could account for this in a sustainable manner. In this study, a fully VRES-based European energy system in the year 2050 is designed using an iterative minimal cost-optimization approach that ensures robust supply security across 38 weather-year scenarios (1980–2017). The impact of different power generation locations is factored in by defining exclusive VRES groups within each optimization region. From this, it can be seen that higher numbers of groups in each region offer cheaper electricity generation locations to the optimizer and thus decrease the system's total annual costs. Furthermore, the robust system design and impact of inter-annual variability is identified by iteratively combining the installed capacities of different system designs derived through the application of the 38 historical weather years. The system design outlined here has significantly lower capacities in comparison to the maximum regional capacities obtained in the first round of optimization.

Climatic constraints for the maize-soybean system in the humid subtropical region of Argentina

The implementation of two summer crops in the same growing season is a possible alternative for land intensification in areas with a long frost-free period. The aim of this study was to analyse the strategy of land intensification through the implementation of the maize-soybean succession at two locations (Reconquista, 29°09′S 59°40′W and Las Brenas, 27°05′S 61°5′W) of the humid subtropical region of Argentina. CERES-Maize and CROPGRO-Soybean models were used to evaluate the impact of inter-annual variability of climate (36 years) of both locations on rain-fed grain yields of the following productive alternatives: (i) monoculture of maize, (ii) monoculture of soybean and (iii) the succession of a short-cycle maize followed by soybean as the second summer crop (maize-soybean system). The maize-soybean system was evaluated by the method of land equivalent ratio (LER), based on the sum of the relative grain yields of its components. The impact of the inter-annual variability of climate and of “El Nino” or “La Nina” episodes (El Nino Southern Oscillation phenomenon (ENSO)) on LER values was analysed. Simulated yields of maize monoculture (5687 kg ha−1; CV = 49.7% and 5637 kg ha−1; CV = 57.6% at Reconquista and Las Brenas, respectively) were higher than those of the short-cycle maize, especially at Las Brenas (5448 kg ha−1; CV = 49.3% and 2322 kg ha−1; CV = 33.9% at Reconquista and Las Brenas, respectively). Simulated yields of the soybean monoculture were higher (3588 kg ha−1; CV = 26.1% and 2883 kg ha−1; CV = 20.7% at Reconquista and Las Brenas, respectively) that those of the soybean as the second crop (2634 kg ha−1; CV = 38.1% and 2456 kg ha−1; CV = 32.9% at Reconquista and Las Brenas, respectively) at both locations. Average LERs were 1.69 (CV = 11.4%) at Reconquista and 1.41 (CV = 26.1%) at Las Brenas, and the inter-annual variability of LER was mainly determined by grain yields of (i) soybean as the second crop at Reconquista and (ii) maize monoculture at Las Brenas. Soil water content after maize harvest and rainfalls during reproductive period of soybean as the second crop conditioned LER values, but they were generally greater than 1. At Reconquista, LER values were not affected by the different episodes of ENSO phenomenon. By contrast, at Las Brenas, LER values were higher during La Nina episodes (1.48; CV = 26.6%) than during El Nino episodes (1.32; CV = 23.7%) mainly by their effects on grain yields of maize monoculture. Therefore, crop simulation models demonstrate the possibility to intensify land use (40–70%) at two locations of the humid subtropical region of Argentina, by the implementation of the maize-soybean system.

A Comparative Analysis of Change in the First and Second Moment of the PDF of Seasonal Mean 200-mb Heights with ENSO SSTs

Abstract Based on simulations from nine different atmospheric general circulation models (AGCMs), a comparative assessment of the influence of ENSO SST variability on the first and second moment of the probability density function (PDF) of 200-mb seasonal mean height is made. This comparison is quantified by regressing the interannual variability in the mean and the spread of the seasonal means against the Niño-3.4 SSTs. Based on the analysis of simulations from multiple AGCMs, it is concluded that the relative impact of interannual variability of SSTs is larger, and more systematic, on the mean of the PDF of 200-mb heights than on its spread. This result implies that seasonal predictability due to SSTs is predominantly a function of its influence on the seasonal mean. Further, for the practice of seasonal predictions, it might be pragmatic to assume that spread of seasonal means stays constant and that the seasonal forecast information resides entirely in the shift of the seasonal mean PDF.

Interannual Atmospheric Variability Affects Continental Ice Sheet Simulations on Millennial Time Scales

Abstract To inform the ongoing development of earth system models that aim to incorporate interactive ice, the potential impact of interannual variability associated with synoptic variability and El Niño–Southern Oscillation (ENSO) at the Last Glacial Maximum (LGM) on the evolution of a large continental ice sheet is explored through a series of targeted numerical modeling experiments. Global and North American signatures of ENSO at the LGM are described based on a multidecadal paleoclimate simulation using an atmosphere–ocean general circulation model (AOGCM). Experiments in which a thermomechanical North American ice sheet model (ISM) was forced with persistent LGM ENSO composite anomaly maps derived from the AOGCM showed only modest ice sheet thickness sensitivity to ENSO teleconnections. In contrast, very high model sensitivity was found when North American climate variations were incorporated directly in the ISM as a looping interannual time series. Under this configuration, localized transient cold anomalies in the atmospheric record instigated substantial new ice formation through a dynamically mediated feedback at the ice sheet margin, altering the equilibrium geometry and resulting in a bulk 10% growth of the Laurentide ice sheet volume over 5 kyr.

Response of the mean global vegetation distribution to interannual climate variability

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’ ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes.

The impact of interannual variability on multidecadal total ozone simulations

We have used a two‐dimensional chemistry and transport model to study the effects of interannual dynamical variability on global total ozone for 1979–2004. Long‐term meteorological data from the National Centers for Environmental Prediction‐National Center for Atmospheric Research (NCEP‐NCAR) reanalysis‐2 project and the European Center for Medium Range Weather Forecasts (ECMWF) updated reanalysis (ERA‐40) are used to construct yearly dynamical fields for use in the model. The simulations qualitatively resolve much of the seasonal and interannual variability observed in long‐term global total ozone data, including fluctuations related to the quasi‐biennial oscillation (QBO). We performed a series of model experiments to examine the relative roles of the interannual variability, changes in halogen and volcanic aerosol loading, and the 11‐year solar cycle in controlling the multidecadal ozone changes. Statistical regression is used to isolate these signals in the observed and simulated time series. At Northern midlatitudes, the simulated interannual dynamical variability acts to reinforce the chemical ozone depletion caused by the enhanced aerosol loading following the eruption of Mt. Pinatubo in 1991. However, at Southern midlatitudes, the interannual variability masks the aerosol‐induced chemical effect. The simulated solar cycle response in total ozone is generally consistent with observations and is primarily due to the direct photochemical effect. The halogen‐induced total ozone trend for 1979–1996 derived from the model is in good agreement with that derived from observations in the tropics and the Northern Hemisphere (NH). However, at Southern midlatitudes, the trend derived from the model is more sensitive to halogen loading than that derived from observations.

Inversion of the surface properties of ice sheets from satellite microwave data

Electromagnetic models are used as the basis for a least squares inversion technique to estimate the dry snow zone surface properties of the terrestrial ice sheets from active and passive microwave satellite data. Retrieved parameters include grain size, density, layer thickness, and accumulation rate. The prime motivation is to provide information of direct value to the Cryosat altimeter mission. The derived parameters can be used to convert from elevation change to snow mass change. They can also be used to predict geophysical retracking errors in altimeter data and to estimate the resulting uncertainty in the altimeter elevation measurement. With this technique, snow accumulation rate can also be estimated using passive microwave data. These data can then be compared to historical European Remote Sensing (ERS) satellite altimeter data in order to assess the impact of interannual variability in accumulation rate on the significance of rates of elevation change. The technique is in the preliminary stages of assessment, but is demonstrated using ERS-2 altimeter data in conjunction with spatio-temporally colocated Special Sensor Microwave/Imager (SSM/I) and QuikSCAT data. It is planned to apply the technique ultimately to Cryosat.

AVHRR channel selection for land cover classification

Mapping land cover of large regions often requires processing of satellite images collected from several time periods at many spectral wavelength channels. However, manipulating and processing large amounts of image data increases the complexity and time, and hence the cost, that it takes to produce a land cover map. Very few studies have evaluated the importance of individual Advanced Very High Resolution Radiometer (AVHRR) channels for discriminating cover types, especially the thermal channels (channels 3, 4 and 5). Studies rarely perform a multi-year analysis to determine the impact of inter-annual variability on the classification results. We evaluated 5 years of AVHRR data using combinations of the original AVHRR spectral channels (1-5) to determine which channels are most important for cover type discrimination, yet stabilize inter-annual variability. Particular attention was placed on the channels in the thermal portion of the spectrum. Fourteen cover types over the entire state of Colorado were evaluated using a supervised classification approach on all two-, three-, four- and five-channel combinations for seven AVHRR biweekly composite datasets covering the entire growing season for each of 5 years. Results show that all three of the major portions of the electromagnetic spectrum represented by the AVHRR sensor are required to discriminate cover types effectively and stabilize inter-annual variability. Of the two-channel combinations, channels 1 (red visible) and 2 (near-infrared) had, by far, the highest average overall accuracy (72.2%), yet the inter-annual classification accuracies were highly variable. Including a thermal channel (channel 4) significantly increased the average overall classification accuracy by 5.5% and stabilized interannual variability. Each of the thermal channels gave similar classification accuracies; however, because of the problems in consistently interpreting channel 3 data, either channel 4 or 5 was found to be a more appropriate choice. Substituting the thermal channel with a single elevation layer resulted in equivalent classification accuracies and inter-annual variability.

Impact of interannual variability in hydrodynamic circulation on egg and larval transport of plaice Pleuronectes platessa L. in the southern North Sea

A realistic 2D circulation model of the southern North Sea was applied to simulate the interannual variability in dispersal (advection and diffusion) of plaice Pleuronectes platessa L. eggs and larvae from the spawning area in the Southern Bight of the North Sea towards the Dutch coastal nursery areas. The model is driven with daily varying current fields, which are the result of driving a general hydrodynamical model with realistic tidal and meteorological (wind) forcing for the period 1974–1981. Model simulations of plaice egg and larval transport are compared with observed larval concentrations near coastal nursery areas (Delta area and Wadden Sea). The model simulations show that: (1) the interannual variability in transport is large and of the same order as the year-to-year variations observed in larval concentrations near the nursery areas; (2) the interannual variability increases with increasing distance from the spawning area; (3) for the years in which larval estimates were available, the model predictions were positively correlated with observed estimates for the Marsdiep tidal inlet. This suggests that the variability in circulation patterns during the early pelagic stages in the open sea might be a key factor in determining year-class strength of plaice.

Impact of clouds on the surface radiation balance of the Arctic Ocean

The relationship between clouds and the surface radiative fluxes over the Arctic Ocean are explored by conducting a series of modelling experiments using a one-dimensional thermodynamic sea ice model. The sensitivity of radiative flux to perturbations in cloud fraction and cloud optical depth are determined. These experiments illustrate the substantial effect that clouds have on the state of the sea ice and on the surface radiative fluxes. The effect of clouds on the net flux of radiation at the surface is very complex over the Arctic Ocean particularly due to the presence of the underlying sea ice. Owing to changes in surface albedo and temperature associated with changing cloud properties, there is a strong non-linearity between cloud properties and surface radiative fluxes. The model results are evaluated in three different contexts: 1) the sensitivity of the arctic surface radiation balance to uncertainties in cloud properties; 2) the impact of interannual variability in cloud characteristics on surface radiation fluxes and sea ice surface characteristics; and 3) the impact of climate change and the resulting changes in cloud properties on the surface radiation fluxes and sea ice characteristics.

Impact of interannual variability (1979–1986) of transport and temperature on ozone as computed using a two‐dimensional photochemical model

Eight years of NMC (National Meteorological Center) temperature and SBUV (solar backscattered ultraviolet) ozone data were used to calculate the monthly mean heating rates and residual circulation for use in a two‐dimensional photochemical model in order to examine the interannual variability of modeled ozone. Fairly good correlations were found in the interannual behavior of modeled and measured SBUV ozone in the upper stratosphere at middle to low latitudes, where temperature dependent photochemistry is thought to dominate ozone behavior. The calculated total ozone is found to be more sensitive to the interannual residual circulation changes than to the interannual temperature changes. The magnitude of the modeled ozone variability is similar to the observed variability, but the observed and modeled year to year deviations are mostly uncorrelated. The large component of the observed total ozone variability at low latitudes due to the quasi‐biennial oscillation (QBO) is not seen in the modeled total ozone, as only a small QBO signal is present in the heating rates, temperatures, and monthly mean residual circulation. Large interannual changes in tropospheric dynamics are believed to influence the interannual variability in the total ozone, especially at middle and high latitudes. Since these tropospheric changes and most of the QBO forcing are not included in our model formulation, it is not surprising that the interannual variability in total ozone is not well represented in our model computations.