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Erika L. Navarro and Gregory J. Hakim

Abstract

A significant challenge for tropical cyclone ensemble data assimilation is that storm-scale observations tend to make analyses that are more asymmetric than the prior forecasts. Compromised structure and intensity, such as an increase of amplitude across the azimuthal Fourier spectrum, are a routine property of ensemble-based analyses, even with accurate position observations and frequent assimilation. Storm dynamics in subsequent forecasts evolve these states toward axisymmetry, creating difficulty in distinguishing between model-induced and actual storm asymmetries for predictability studies and forecasting. To address this issue, a novel algorithm using a storm-centered approach is proposed. The method is designed for use with existing ensemble filters with little or no modification, facilitating its adoption and maintenance. The algorithm consists of 1) an analysis of the environment using conventional coordinates, 2) a storm-centered analysis using storm-relative coordinates, and 3) a merged analysis that combines the large-scale and storm-scale fields together at an updated storm location. This algorithm is evaluated in two sets of observing system simulation experiments (OSSEs): first, no-cycling tests of the update step for idealized three-dimensional storms in radiative–convective equilibrium; second, full cycling tests of data assimilation applied to a shallow-water model for a field of interacting vortices. Results are compared against a control experiment based on a conventional ensemble Kalman filter (EnKF) scheme as well as an alternative EnKF scheme proposed by Lawson and Hansen. The storm-relative method yields vortices that are more symmetric and exhibit finer inner-core structure than either approach, with errors reduced by an order of magnitude over a control case with prior spread consistent with the National Hurricane Center (NHC)’s mean 5-yr forecast track error at 12 h. Azimuthal Fourier error spectra exhibit much-reduced noise associated with data assimilation as compared to both the control and the Lawson and Hansen approach. An assessment of free-surface height tendency of model forecasts after the merge step reveals a balanced trend between the storm-centered and conventional approaches, with storm-centered values more closely resembling the reference state.

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Erika L. Navarro and Gregory J. Hakim

Abstract

A numerical experiment is performed to evaluate the role of the daily cycle of radiation on axisymmetric hurricane structure. Although a diurnal response in high cloudiness has been well documented previously, the link to tropical cyclone (TC) structure and intensity remains unknown. Previous modeling studies attributed differences in results to experimental setup (e.g., initial and boundary conditions) as well as to radiative parameterizations. Here, a numerically simulated TC in a statistically steady state is examined for 300 days to quantify the TC response to the daily cycle of radiation.

Fourier analysis in time reveals a spatially coherent diurnal signal in the temperature, wind, and latent heating tendency fields. This signal is statistically different from random noise and accounts for up to 62% of the variance in the TC outflow and 28% of the variance in the boundary layer. Composite analysis of each hour of the day reveals a cycle in storm intensity: a maximum is found in the morning and a minimum in the evening, with magnitudes near 1 m s−1. Anomalous latent heating forms near the inner core of the storm in the late evening, which persists throughout the early morning. Examination of the radial–vertical wind suggests two distinct circulations: 1) a radiatively driven circulation in the outflow layer due to absorption of solar radiation and 2) a convectively driven circulation in the lower and middle troposphere due to anomalous latent heating. These responses are coupled and are periodic with respect to the diurnal cycle.

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L. A. Aceves-Navarro, K. O. Hubbard, and J. Schmidt

Abstract

Techniques for simultaneously calibrating a number of pyranometers for use with automated weather stations are examined. The pressure involves taking data from an Eppley precision spectral pyranometer and from up to 11 LI-COR pyranometers using a specially built sensor plate. Results of a group calibration of six pyranometers using 10-minute data over a 3-day period are given. Three best-fit lines were determined for full-scale (5–960 W m−2), midscale (300–650 W m−2) and midrank (400–800 W m−2) datasets. The full-scale calibration technique proved most useful, resulting in a standard error of estimate of less than 20 W m−2 in all cases.

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Erika L. Navarro, Gregory J. Hakim, and Hugh E. Willoughby

Abstract

A modified version of the Sawyer–Eliassen equation is applied to determine the impact of periodic diurnal heating on a balanced vortex. The TC diurnal cycle is a coherent signal that arises in the cirrus canopy. However, despite thorough documentation in the literature, the dynamical mechanism remains unknown. Recent work demonstrates that periodic radiative heating in the TC outflow layer is linked with an anomalous upper-level circulation; this heating is also associated with a cycle of latent heating in the lower troposphere that corresponds to a cycle in storm intensity. Using a method that is analogous to the Sawyer–Eliassen equation, but for solutions having the same time scale as time-periodic forcing, these distributions are analyzed to determine the effect of periodic diurnal heating on an axisymmetric vortex.

Results for periodic heating in the lower troposphere show an overturning circulation that resembles the Sawyer–Eliassen solution. The model simulates positive perturbations in the azimuthal wind field of 2.5 m s−1 near the radius of maximum wind. Periodic heating near the top of the vortex produces a local overturning response in the region of heating and an inertia–buoyancy wave response in the storm environment. Comparison of the results from the modified Sawyer–Eliassen equation to those of an idealized axisymmetric solution for both heating distributions shows similarities in the structure of the perturbation wind fields, suggesting that the axisymmetric TC diurnal cycle is primarily a balanced response driven by periodic heating.

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P. A. Jiménez, E. García-Bustamante, J. F. González-Rouco, F. Valero, J. P. Montávez, and J. Navarro

Abstract

Daily wind variability in the Comunidad Foral de Navarra in northern Spain was studied using wind observations at 35 locations to derive subregions with homogeneous temporal variability. Two different methodologies based on principal component analysis were used to regionalize: 1) cluster analysis and 2) the rotation of the selected principal components. Both methodologies produce similar results and lead to regions that are in general agreement with the topographic features of the terrain. The meridional wind variability is similar in all subregions, whereas zonal wind variability is responsible for differences between them. The spectral analysis of wind variability within each subregion reveals a dominant annual cycle and the varying presence of higher-frequency contributions in the subregions. The valley subregions tend to present more variability at high frequencies than do higher-altitude sites. Last, the influence of large-scale dynamics on regional wind variability is explored by studying connections between wind in each subregion and sea level pressure fields. The results of this work contribute to the characterization of wind variability in a complex terrain region and constitute a framework for the validation of mesoscale model wind simulations over the region.

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Etor E. Lucio-Eceiza, J. Fidel González-Rouco, Jorge Navarro, Hugo Beltrami, and Jorge Conte

Abstract

A quality control (QC) process has been developed and applied to an observational database of surface wind speed and wind direction in northeastern North America. The database combines data from three datasets of different initial quality, including a total of 526 land stations and buoys distributed over the provinces of eastern Canada and five adjacent northeastern U.S. states. The data span from 1953 to 2010. The first part of the QC deals with data management issues and is developed in a companion paper. Part II, presented herein, is focused on the detection of measurement errors and deals with low-variability errors, like the occurrence of unrealistically long calms, and high-variability problems, like rapid changes in wind speed; some types of biases in wind speed and wind direction are also considered. About 0.5% (0.16%) of wind speed (wind direction) records have been flagged. Additionally, 15.87% (1.73%) of wind speed (wind direction) data have been corrected. The most pervasive error type in terms of affected sites and erased data corresponds to unrealistic low wind speeds (89% of sites affected with 0.35% records removed). The amount of detected and corrected/removed records in Part II (~9%) is approximately two orders of magnitude higher than that of Part I. Both management and measurement errors are shown to have a discernible impact on the statistics of the database.

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F. J. Tapiador, A. Berne, T. Raupach, A. Navarro, G. Lee, and Z. S. Haddad

Abstract

Improving the atmospheric component of hydrological models is beneficial for applications such as water resources assessment and hydropower operations. Within this goal, precise characterization of rain microphysics is key for climate and weather modeling, and thus for hydrometeorological applications. Such characterization can be achieved by analyzing the evolution in time of the particle size distribution (PSD) of hydrometeors, which can be measured at ground using disdrometers for validation. The estimation, however, depends on the choice of the PSD form (the shape) and on the parameters to define the exact shape. In the case of modeling rain microphysics, two approaches compete: the use of the number concentration of drops decoupled from the shape of the distribution (the [N T, E(D), E(D 2)] and the {N T, E(D), E[log(D)]} models), and the (N 0, Λ, μ) model that embeds in N 0 both the shape of the distribution and the number concentration of drops. Here we use a comprehensive dataset of disdrometer measurements to show that the N T-based approaches allow a more precise characterization of the drop size distribution (DSD) and also a physically based modeling of the microphysical processes of rain since N T is analytically independent of the shape of the DSD {parameterized by E(D), and E(D 2) or E[log(D)]}. The implication is that numerical models would benefit from decoupling the number of drops from the shape of distribution in their modules of precipitation microphysics in order to improve outputs that eventually feed hydrological models.

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Etor E. Lucio-Eceiza, J. Fidel González-Rouco, Jorge Navarro, and Hugo Beltrami

Abstract

A quality control (QC) process has been developed and implemented on an observational database of surface wind speed and direction in northeastern North America. The database combines data from 526 land stations and buoys spread across eastern Canada and five adjacent northeastern U.S. states. It combines the observations of three different institutions spanning from 1953 to 2010. The quality of these initial data varies among source institutions. The current QC process is divided into two parts. Part I, described herein, is focused on issues related to data management: issues stemming from data transcription and collection; differences in measurement units and recording times; detection of sequences of duplicated data; unification of calm and true north criteria for wind direction; and detection of physically unrealistic data measurements. As a result, around ~0.1% of wind speed and wind direction records have been identified as erroneous and deleted. The most widespread error type is related to duplications within the same station, but the error type that entails more erroneous data belongs to duplications among different sites. Additionally, the process of data compilation and standardization has had an impact on more than 90% of the records. A companion paper (Part II) deals with a group of errors that are conceptually different, and is focused on detecting measurement errors that relate to temporal consistency and biases in wind speed and direction.

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Pedro A. Jiménez, J. Fidel González-Rouco, Jorge Navarro, Juan P. Montávez, and Elena García-Bustamante

Abstract

Meteorological data of good quality are important for understanding both global and regional climates. In this respect, great efforts have been made to evaluate temperature- and precipitation-related records. This study summarizes the evaluations made to date of the quality of wind speed and direction records acquired at 41 automated weather stations in the northeast of the Iberian Peninsula. Observations were acquired from 1992 to 2005 at a temporal resolution of 10 and 30 min. A quality assurance system was imposed to screen the records for 1) manipulation errors associated with storage and management of the data, 2) consistency limits to ensure that observations are within their natural limits of variation, and 3) temporal consistency to assess abnormally low/high variations in the individual time series. In addition, the most important biases of the dataset are analyzed and corrected wherever possible. A total of 1.8% wind speed and 3.7% wind direction records was assumed invalid, pointing to specific problems in wind measurement. The study not only tries to contribute to the science with the creation of a wind dataset of improved quality, but it also reports on potential errors that could be present in other wind datasets.

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Pedro A. Jimenez, Jordi Vila-Guerau de Arellano, Jorge Navarro, and J. Fidel Gonzalez-Rouco
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