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Yafang Zhong, Zhengyu Liu, and R. Jacob

Abstract

Observations indicate that Pacific multidecadal variability (PMV) is a basinwide phenomenon with robust tropical–extratropical linkage, though its genesis remains the topic of much debate. In this study, the PMV in the Community Climate System Model, version 3 (CCSM3) is investigated with a combined statistical and dynamical approach. In agreement with observations, the modeled North Pacific climate system undergoes coherent multidecadal atmospheric and oceanic variability of a characteristic quasi-50-yr time scale, with apparent connections to the tropical Indo-Pacific.

The statistical assessment based on the CCSM3 control integration cannot exclusively identify the origin of the modeled multidecadal linkage, while confirming the two-way interactions between the tropical and extratropical Pacific. Two sensitivity experiments are performed to further investigate the origin of the PMV. With the atmosphere decoupled from the tropical ocean, multidecadal variability in the North Pacific climate remains outstanding. In contrast, without midlatitude oceanic feedback to atmosphere, an experiment shows much reduced multidecadal power in both extratropical atmosphere and surface ocean; moreover, the tropical multidecadal variability seen in the CCSM3 control run virtually disappears. The combined statistical and dynamical assessment supports a midlatitude coupled origin for the PMV, which can be described as follows: extratropical large-scale air–sea interaction gives rise to multidecadal variability in the North Pacific region; this extratropical signal then imprints itself in the tropical Indo–Pacific climate system, through a robust tropical–extratropical teleconnection. This study highlights a midlatitude origin of multidecadal tropical–extratropical linkage in the Pacific in the CCSM3.

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Stephen R. Okkonen and Gregg A. Jacobs

Abstract

Analytical expressions are presented for calculating alias wavelengths and the direction of propagation resulting from sampling propagating mesoscale wave fields by Geosat and Topex altimeters. Idealized and realistic data are used to illustrate representative examples of spatially aliased propagating wave fields.

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Jacob R. Reed and Jason C. Senkbeil

Abstract

The extended forecast graphic (EFG) is a popular graphic used by meteorologists to convey weather information, but it is poorly understood by the public. Deficiencies in the format, content, and presentation of the EFG contribute to a decrease in the efficacy of this graphic and reduce the comprehension of weather information. The format of the EFG has largely gone unchanged since the graphic first became popular more than four decades ago. The goal of this research was to modify the format of the existing EFG to address current limitations that inhibit understanding and create confusion among the public. Data were gathered from an online survey of the public (n = 885). Four modified versions of the EFG were developed, evaluated, and compared with the existing EFG. Removing probability of precipitation (PoP) information, reducing the number of days shown, and switching to a horizontal layout featuring timing and intensity information resulted in higher percentages for comprehension of weather information and positive comments when compared with the current version. A majority of participants responded that forecasters could accurately predict the weather 3 days out, providing justification for the reduction in number of days shown in the modified EFGs. Results suggest that agencies and members of the meteorological community should continue evaluating and discussing the most effective ways to use graphics to convey weather information to their audiences.

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Jacob R. Reed and Jason C. Senkbeil

Abstract

There have been multiple efforts in recent years to simplify visual weather forecast products, with the goal of more efficient risk communication for the general public. Many meteorological forecast products, such as the cone of uncertainty, storm surge graphics, warning polygons, and Storm Prediction Center (SPC) convective outlooks, have created varying levels of public confusion resulting in revisions, modifications, and improvements. However, the perception and comprehension of private weather graphics produced by television stations has been largely overlooked in peer-reviewed research. The goal of this study is to explore how the extended forecast graphic, more commonly known as the 7, 10 day, etc., is utilized by broadcasters and understood by the public. Data were gathered from surveys with the general public and also from broadcast meteorologists. Results suggest this graphic is a source of confusion and highlights a disconnect between the meteorologists producing the graphic and the content prioritized by their audiences. Specifically, timing and intensity of any precipitation or adverse weather events are the two most important variables to consider from the viewpoint of the public. These variables are generally absent from the extended forecast graphic, thus forcing the public to draw their own conclusions, which may differ from what the meteorologist intends to convey. Other results suggest the placement of forecast high and low temperatures, use of probability of precipitation, icon inconsistency, and length of time the graphic is shown also contribute to public confusion and misunderstanding.

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Zhengyu Liu, Yun Liu, Lixin Wu, and R. Jacob

Abstract

The atmospheric response to a North Pacific subsurface oceanic temperature anomaly is studied in a coupled ocean–atmosphere general circulation model using a combined dynamical and statistical approach, with the focus on the evolution at seasonal and longer time scales. The atmospheric response is first assessed dynamically with an ensemble coupled experiment. The atmospheric response is found to exhibit a distinct seasonal evolution and a significant long-term response. The oceanic temperature anomaly reemerges each winter to force the atmosphere through an upward heat flux, forcing a clear seasonal atmospheric response locally over the Aleutian low and downstream over the North America/North Atlantic Ocean and the Arctic regions. The atmospheric response is dominated by the early winter response with a warm SST-equivalent barotropic ridge and a wave train downstream. Starting in later winter, the atmospheric response weakens significantly and remains weak throughout the summer. The seasonal response of the atmosphere is then assessed statistically from the control simulation. It is found that the major features of the seasonal response, especially the strong warm SST–ridge response in early winter, are crudely consistent between the dynamical and statistical assessments. The statistical assessment is finally applied to the observation, which also suggests a strong seasonal atmospheric response locally over the North Pacific dominated by a warm SST–ridge response in early winter.

One important conclusion is that the atmospheric response becomes more significant at annual and longer time scales, with the signal/noise ratio increasing up to 4 times from the monthly to the 4-yr mean response. This increased signal/noise ratio is caused by a much faster reduction of the atmospheric internal variability toward longer time scales than that of the response signal. The slow decrease of the response signal is due to the long persistence associated with the subsurface ocean. This suggests that the subsurface extratropical oceanic variability could have a much stronger impact on the extratropical atmosphere (and climate variability) at interannual–interdecadal time scales than at monthly–seasonal time scales.

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W. J. Teague, Z. R. Hallock, and G. A. Jacobs

Abstract

An estimate of the geoid across the Kuroshio Extension at its separation point from Japan is calculated through an analysis of coincident sea surface measurements from inverted echo sounders (IESs) and Topex/Poseidon (T/P). The IESs were positioned along a T/P descending ground track in the vicinity of 35°N, 143°E. This geoid section can be used in conjunction with altimeter data to estimate total sea surface height. Thus, Kuroshio position, surface geostrophic velocity, and transport along the section can be continuously monitored.

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Donald E. Lippi, Jacob R. Carley, and Daryl T. Kleist

Abstract

This work describes developments to improve the Doppler radial wind data assimilation scheme used in the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) data assimilation system with a focus on convection-permitting, 0–18-h forecasts of a heavy precipitation single case study. This work focuses on two aspects: 1) the extension of the radial wind observation operator to include vertical velocity and 2) a refinement of the radial wind super-observation processing. The refinement includes reducing the magnitude of observation smoothing and allowing observations from higher scan angles into the analysis with the intent to improve the assimilation of the radar data for operational, convection-permitting models. The results of this study demonstrate that there is sensitivity to the refinement in super-observation settings. The inclusion of vertical velocity in the observation operator is shown to have a neutral to slightly positive impact on the forecast. Results from this study are suggested to be used as a foundation to prioritize future research into the effective assimilation of radial winds in an operational setting.

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H. E. Ngodock, S. R. Smith, and G. A. Jacobs

Abstract

Realistic dynamic systems are often strongly nonlinear, particularly those for the ocean and atmosphere. Applying variational data assimilation to these systems requires a tangent linearization of the nonlinear dynamics about a background state for the cost function minimization. The tangent linearization may be accurate for limited time scales. Here it is proposed that linearized assimilation systems may be accurate if the assimilation time period is less than the tangent linear accuracy time limit. In this paper, the cycling representer method is used to test this assumption with the Lorenz attractor. The outer loops usually required to accommodate the linear assimilation for a nonlinear problem may be dropped beyond the early cycles once the solution (and forecast used as the background in the tangent linearization) is sufficiently accurate. The combination of cycling the representer method and limiting the number of outer loops significantly lowers the cost of the overall assimilation problem. In addition, this study shows that weak constraint assimilation corrects tangent linear model inaccuracies and allows extension of the limited assimilation period. Hence, the weak constraint outperforms the strong constraint method. Assimilated solution accuracy at the first cycle end is computed as a function of the initial condition error, model parameter perturbation magnitude, and outer loops. Results indicate that at least five outer loops are needed to achieve solution accuracy in the first cycle for the selected error range. In addition, this study clearly shows that one outer loop in the first cycle does not preclude accuracy convergence in future cycles.

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Cor M. J. Jacobs and Henk A. R. de Bruin

Abstract

A coupled planetary boundary layer (PBL)–vegetation model is used to study the influence of the PBL–vegetation interaction and the ambient CO2 concentration on surface resistance r s and regional transpiration λE. Vegetation is described using the big-leaf model in which r s is modeled by means of a coupled photosynthesis–resistance model. The PBL part is a one-dimensional, first-order closure model. Nonlocal turbulent transport is accounted for by means of a countergradient correction. The PBL model also describes CO2 fluxes and concentrations, which are driven by photosynthesis of the canopy. A number of sensitivity analyses are presented in which the behavior of r s and λE at an atmospheric CO2 concentration representative for the present-day situation is compared to their behavior under an approximately doubled CO2 concentration. The results reveal a positive atmospheric feedback on r s, by which an initial increase of r s, due to changes in ambient CO2 concentration, is magnified. The stomatal humidity response appears to be the key factor here: if r s increases, the air within the canopy dries out, which causes the stomata to close further. The PBL enlarges the effect of this positive feedback loop. The model suggests plants with a C4 photosynthetic pathway to be less sensitive to the humidity-mediated positive feedback than plants with a C3 photosynthetic pathway. Another important aspect of biosphere–atmosphere interaction is the negative feedback of the PBL on transpiration. It is concluded that the interaction between PBL and the vegetation has to be taken into account if transpiration and its changes, due to changing surface characteristics, are to be predicted at the regional scale. This conclusion applies to modeling studies as well as to extrapolation of results from plant physiological research or from small-scale field plots to the regional scale.

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Jeffrey D. Duda, Xuguang Wang, Yongming Wang, and Jacob R. Carley

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Two methods for assimilating radar reflectivity into deterministic convection-allowing forecasts were compared: an operationally used, computationally less expensive cloud analysis (CA) scheme and a relatively more expensive, but rigorous, ensemble Kalman filter–variational hybrid method (EnVar). These methods were implemented in the Nonhydrostatic Multiscale Model on the B-grid and were tested on 10 cases featuring high-impact deep convective storms and heavy precipitation. A variety of traditional, neighborhood-based, and features-based verification metrics support that the EnVar produced superior free forecasts compared to the CA procedure, with statistically significant differences extending up to 9 h into the forecast. Despite being inferior, the CA scheme was able to provide benefit compared to not assimilating radar reflectivity at all, but limited to the first few forecast hours. While the EnVar is able to partially suppress spurious convection by assimilating 0-dBZ reflectivity observations directly, the CA is not designed to reduce or remove hydrometeors. As a result, the CA struggles more with suppression of spurious convection in the first-guess field, which resulted in high-frequency biases and poor forecast evolution, as illustrated in a few case studies. Additionally, while the EnVar uses flow-dependent ensemble covariances to update hydrometers, thermodynamic, and dynamic variables simultaneously when the reflectivity is assimilated, the CA relies on a radar reflectivity-derived latent heating rate that is applied during a separate digital filter initialization (DFI) procedure to introduce deep convective storms into the model, and the results of CA are shown to be sensitive to the window length used in the DFI.

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