Persistence Of Initial Conditions Research Articles

Persistence of initial conditions in continental scale air quality simulations

This study investigates the effect of initial conditions (IC) for pollutant concentrations in the atmosphere and soil on simulated air quality for two continental-scale Community Multiscale Air Quality (CMAQ) model applications. One of these applications was performed for springtime and the second for summertime. Results show that a spin-up period of ten days commonly used in regional-scale applications may not be sufficient to reduce the effects of initial conditions to less than 1% of seasonally-averaged surface ozone concentrations everywhere while 20 days were found to be sufficient for the entire domain for the spring case and almost the entire domain for the summer case. For the summer case, differences were found to persist longer aloft due to circulation of air masses and even a spin-up period of 30 days was not sufficient to reduce the effects of ICs to less than 1% of seasonally-averaged layer 34 ozone concentrations over the southwestern portion of the modeling domain. Analysis of the effect of soil initial conditions for the CMAQ bidirectional NH3 exchange model shows that during springtime they can have an important effect on simulated inorganic aerosols concentrations for time periods of one month or longer. The effects are less pronounced during other seasons. The results, while specific to the modeling domain and time periods simulated here, suggest that modeling protocols need to be scrutinized for a given application and that it cannot be assumed that commonly-used spin-up periods are necessarily sufficient to reduce the effects of initial conditions on model results to an acceptable level. What constitutes an acceptable level of difference cannot be generalized and will depend on the particular application, time period and species of interest. Moreover, as the application of air quality models is being expanded to cover larger geographical domains and as these models are increasingly being coupled with other modeling systems to better represent air-surface-water exchanges, the effects of model initialization in such applications needs to be studied in future work.

Spin‐up behavior and effects of initial conditions for an integrated hydrologic model

AbstractInitial conditions have been shown to have a strong effect on outputs of surface water models, but their impact on integrated hydrologic models is not well documented. We investigated the effects of initial conditions on an integrated hydrologic model of a 5632 km2 domain in the northeastern U.S. Simulations were run for the year 1980 using four initial conditions spanning a range of average depth to water table, including 1 m (“wet”), 3m, 5m, and 7 m (“dry”) below land surface. Model outputs showed significant effects of initial conditions on basin‐averaged variables such as subsurface storage, surface storage, and surface runoff, with the greatest impact observed on surface storage and runoff. Effects of initial conditions were related to meteorological conditions, with precipitation reducing the effects of initial conditions on surface storage and runoff. Additionally, feedbacks between soil moisture and land‐energy fluxes affected the impacts of initial conditions: higher temperatures magnified the differences in storage, recharge, and discharge among the four initial‐condition scenarios. Ten year recursive runs were conducted for the wet and dry scenarios. Spin‐up times varied by model components and were considerably smaller for land‐surface states and fluxes. Spin‐up for dry initial conditions was slower than for wet initial conditions, indicating longer system memory for dry initial conditions. These variations in persistence of initial conditions should be taken into consideration when designing model initialization approaches. More broadly, this behavior is indicative of increased persistence of the effects of dry years as opposed to wet years in hydrologic systems.

Conceptual evaluation of continental land-surface model behaviour

Continental land-surface models, such as the landscape component of the Australian Water Resources Assessment System (AWRA-L), aim to simulate the water balance over a wide variety of climates, land forms and land uses. To accommodate this range of hydrological conditions, model conceptualisation has to be flexible, while at the same time robust and parsimonious to allow for calibration using sparse data sets.In this study a Monte Carlo sensitivity analysis of the AWRA-L system is carried out as a step preceding calibration in which the hyperspace formed by parameters and initial conditions is explored using Latin Hypercube Sampling. The main goal is to test whether the model behaviour is in accordance with current understanding of Australian hydrology and to guide calibration. To visualise and analyse the high-dimensionality of the output space and the complex, non-linear interactions between processes and parameters, we used Self Organizing Maps, a non-parametric neural network.The results show that the main cause of non-linear model behaviour can be attributed to the ratio of rainfall over potential evaporation ratio, which determines which processes will dominate the water balance and the persistence of initial conditions. The model behaviour corresponds well to the current understanding of the hydrology of the Australian continent.

Variability and persistence of hillslope initial conditions: A continuous perspective on subsurface flow response to rain events

► HYDRUS simulations examine event response to hillslope-scale initial conditions. ► Hillslope storage exhibits preferred ranges for wet and dry seasons. ► Hillslope field capacity separates wet and dry season preferred storage ranges. ► Subsurface stormflow requires an initial storage threshold near field capacity. ► Total subsurface stormflow is a nonlinear function of initial storage. Runoff response to rain events depends on the initial moisture conditions in the subsurface. This study explores subsurface stormflow response to initial conditions within the context of a continuous hillslope water balance. A hypothetical hillslope with three-dimensional variably saturated subsurface flow is developed using the HYDRUS model forced with a year-long sequence of hourly precipitation and transpiration from Seattle, WA, USA. Using six different soil hydraulic parameter sets, test simulations examine (1) variability of hillslope initial conditions prior to rain events, (2) persistence of initial conditions in a continuous simulation, and (3) effects of initial conditions on subsurface stormflow during rain events. Results show that hillslope initial conditions vary seasonally, producing bimodal distributions of storage values with preferred storage ranges for wet and dry seasons. Preferred storage ranges differ by soil texture and by hydraulic conductivity. Wet season initial conditions are most frequently at storage values above hillslope field capacity, with higher preferred ranges of storage for scenarios with lower saturated hydraulic conductivity. Dry season hillslope storage values converge to minimum values below field capacity, and these minimum values vary with soil texture but not with saturated hydraulic conductivity. Tests of initial condition convergence show that scenarios with different initial storages can eventually converge under either persistent wetting or persistent drying until hillslope storage reaches the wet or dry preferred states. Dry preferred states are unlikely to produce subsurface stormflow, as test rain events generate hillslope outflow only when initial storage is at or above an event and parameter-specific threshold near the hillslope field capacity. Above this flow threshold, all simulations show a nonlinear increase in subsurface stormflow with increasing initial storage, with the steepest rates of increase for scenarios with the highest values of saturated hydraulic conductivity. Simulation experiments present a quantitative approach for deriving functional relationships between event response, initial storage, and hillslope water retention.

Southern hemisphere tropical cyclone intensity forecast methods used at the Joint Typhoon Warning Center, Part I: control forecasts based on climatology and persistence

The development of a simple statistical tropical cyclone (TC) intensity forecast model is described. The primary purpose of this model, called southern hemisphere five-day statistical typhoon intensity forecast scheme (SH ST5D), is to provide a skill/no-skill control forecast for verifying other TC intensity forecasts. However, it also provides useful and always-available forecasts of TC intensity in the southern hemisphere. The model is created by fitting an optimal combination of factors related to climatology and persistence (or CLIPER) using multiple linear regression. These CLIPER factors are determined from the best track tropical cyclone dataset produced by the United States of America’s Joint Typhoon Warning Center (JTWC) in the years 1980-2002. In 2004 the SH ST5D model became part of the operational suite of tropical cyclone intensity guidance run at JTWC. The forecasts from the model since that time have outperformed both climatology (i.e. a constant 65 knots or 33 ms -1 forecast) and the persistence of initial conditions in a statistically significant manner in independent testing during 2004-2007. This documentation is provided to promote the use of this model’s output and provide adequate background for the development of similar models.