Vortex Initialization in the NCEP Operational Hurricane Models

This paper describes the vortex initialization (VI) currently used in NCEP operational hurricane models (HWRF and HMON, and possibly HAFS in the future). The VI corrects the background fields for hurricane models: it consists of vortex relocation, and size and intensity corrections. The VI creates an improved background field for the data assimilation and thereby produces an improved analysis for the operational hurricane forecast. The background field after VI can be used as an initial field (as in the HMON model, without data assimilation) or a background field for data assimilation (as in HWRF model). Keywords: vortex initialization; bogus storm; hurricane initialization</p

Multi-Scale Analysis of Observations of Tropical Cyclones with Applications to High-Resolution Hurricane Modeling

Tropical cyclone numerical models, a critical tool to forecasters, have been run at resolutions of around 9-30 km in operational centers until recently. It is currently possible to run in the range of 1-4 km resolution, which may allow a model to resolve small-scale dynamical processes critical to tropical cyclone intensity. A 3km version of the NCEP HWRF model is developed for that purpose and its competitive track and intensity forecasting abilities are demonstrated. To determine if the small scales are resolved correctly, a statistical framework for comparison to observations of small-scales is developed. The standard definition of a model's forecast intensity is examined, and found to have a systematic, resolution-dependent bias. A database of TRMM overpasses of over eight hundred tropical cyclones is produced and used to show a relationship between storm-scale cloud top temperature and storm wind intensity. However, all storms, regardless of strength, produce near-tropopause cloud tops, and storms undergoing rapid intensification (RI) tend to have higher cloud tops than non-RI storms. In an analysis of in-situ wind data, vertical wind is shown to be scale-invariant, with no correlation beyond, nominally, 2 km scales. This new framework for comparison is used to show that model's cloud tops have the right relationships with intensity and intensification, but that downdrafts are weak and rare. Model ""spin-up"" issues are seen: in the first six hours, some storms rapidly gain fine-scale 3 km resolution wind maxima that hurt the forecast and others weaken uniformly at all resolutions. In addition, a model bug is found in this and operational HWRF: all microphysics type fractions are discarded when the nest moves. Overall, the research presented in this demonstrates the value of statistical diagnostics for high-resolution models. In addition, this research presents a framework for a deeper investigation of tropical cyclone small-scale dynamics

Multi-Scale Analysis of Observations of Tropical Cyclones with Applications to High-Resolution Hurricane Modeling

Tropical cyclone numerical models, a critical tool to forecasters, have been run at resolutions of around 9-30 km in operational centers until recently. It is currently possible to run in the range of 1-4 km resolution, which may allow a model to resolve small-scale dynamical processes critical to tropical cyclone intensity. A 3km version of the NCEP HWRF model is developed for that purpose and its competitive track and intensity forecasting abilities are demonstrated. To determine if the small scales are resolved correctly, a statistical framework for comparison to observations of small-scales is developed. The standard definition of a model's forecast intensity is examined, and found to have a systematic, resolution-dependent bias. A database of TRMM overpasses of over eight hundred tropical cyclones is produced and used to show a relationship between storm-scale cloud top temperature and storm wind intensity. However, all storms, regardless of strength, produce near-tropopause cloud tops, and storms undergoing rapid intensification (RI) tend to have higher cloud tops than non-RI storms. In an analysis of in-situ wind data, vertical wind is shown to be scale-invariant, with no correlation beyond, nominally, 2 km scales. This new framework for comparison is used to show that model's cloud tops have the right relationships with intensity and intensification, but that downdrafts are weak and rare. Model ""spin-up"" issues are seen: in the first six hours, some storms rapidly gain fine-scale 3 km resolution wind maxima that hurt the forecast and others weaken uniformly at all resolutions. In addition, a model bug is found in this and operational HWRF: all microphysics type fractions are discarded when the nest moves. Overall, the research presented in this demonstrates the value of statistical diagnostics for high-resolution models. In addition, this research presents a framework for a deeper investigation of tropical cyclone small-scale dynamics

On the growth of intensity forecast errors in the operational hurricane weather research and forecasting (HWRF) model

This study examines the growth of tropical cyclone (TC) intensity forecast errors and related intensity predictability for the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model. Using operational intensity forecasts during the 2012 to 2016 seasons, two conditions for a limited range of TC intensity predictability are demonstrated, which include (a) the existence of an intensity error saturation limit, and (b) the dependence of the intensity error growth rate on storm intensity during TC development. By stratifying intensity errors based on different initial intensity bins, it is shown that TC intensity error growth rate is relatively small (∼0.3 kt h−1) at the early stage of TC development, but it quickly increases to ∼1 kt h−1 during TC intensification. Of further importance is that the intensity error saturation varies in the range of 14–18 kt in different ocean basins, thus suggesting the potential dependence of the intensity predictability on large‐scale environment. Additional idealized experiments with the HWRF model confirm the saturation of intensity errors, even under a perfect model scenario. The existence of the intensity error saturation together with the finding of a faster error growth rate for higher intensity suggests that the TC dynamics possesses an inherent limited predictability, which prevents us from reducing the intensity errors in TC dynamical models below a certain threshold

On the Growth of Intensity Forecast Errors in the Operational Hurricane Weather Research and Forecasting (HWRF) Model

This study examines the growth of tropical cyclone (TC) intensity forecast errors and related intensity predictability for the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model. Using operational intensity forecasts during the 2012 to 2016 seasons, two conditions for a limited range of TC intensity predictability are demonstrated, which include (a) the existence of an intensity error saturation limit, and (b) the dependence of the intensity error growth rate on storm intensity during TC development. By stratifying intensity errors based on different initial intensity bins, it is shown that TC intensity error growth rate is relatively small (∼0.3 kt h−1) at the early stage of TC development, but it quickly increases to ∼1 kt h−1 during TC intensification. Of further importance is that the intensity error saturation varies in the range of 14–18 kt in different ocean basins, thus suggesting the potential dependence of the intensity predictability on large‐scale environment. Additional idealized experiments with the HWRF model confirm the saturation of intensity errors, even under a perfect model scenario. The existence of the intensity error saturation together with the finding of a faster error growth rate for higher intensity suggests that the TC dynamics possesses an inherent limited predictability, which prevents us from reducing the intensity errors in TC dynamical models below a certain threshold

Direct Retrieval of Sulfur Dioxide Amount and Altitude from Spaceborne Hyperspectral UV Measurements: Theory and Application

We describe the physical processes by which a vertically localized absorber perturbs the top-of-atmosphere solar backscattered ultraviolet (UV) radiance. The distinct spectral responses to perturbations of an absorber in its column amount and layer altitude provide the basis for a practical satellite retrieval technique, the Extended Iterative Spectral Fitting (EISF) algorithm, for the simultaneous retrieval of these quantities of a SO2 plume. In addition, the EISF retrieval provides an improved UV aerosol index for quantifying the spectral contrast of apparent scene reflectance at the bottom of atmosphere bounded by the surface and/or cloud; hence it can be used for detection of the presence or absence of UV absorbing aerosols. We study the performance and characterize the uncertainties of the EISF algorithm using synthetic backscattered UV radiances, retrievals from which can be compared with those used in the simulation. Our findings indicate that the presence of aerosols (both absorbing and nonabsorbing) does not cause large errors in EISF retrievals under most observing conditions when they are located below the SO2 plume. The EISF retrievals assuming a homogeneous field of view can provide accurate column amounts for inhomogeneous scenes, but they always underestimate the plume altitudes. The EISF algorithm reduces systematic errors present in existing linear retrieval algorithms that use prescribed SO2 plume heights. Applying the EISF algorithm to Ozone Monitoring Instrument satellite observations of the recent Kasatochi volcanic eruption, we demonstrate the successful retrieval of effective plume altitude of volcanic SO2, and we also show the improvement in accuracy in the corresponding SO2 columns

Vitality of Gorse-seed

The EXtreme PREcision Spectrograph (EXPRES) is a new Doppler spectrograph designed to reach a radial-velocity measurement precision sufficient to detect Earth-like exoplanets orbiting nearby, bright stars. We report on extensive laboratory testing and on-sky observations to quantitatively assess the instrumental radial-velocity measurement precision of EXPRES, with a focused discussion of individual terms in the instrument error budget. We find that EXPRES can reach a single-measurement instrument calibration precision better than 10 cm s-1, not including photon noise from stellar observations. We also report on the performance of the various environmental, mechanical, and optical subsystems of EXPRES, assessing any contributions to radial-velocity error. For atmospheric and telescope related effects, this includes the fast tip-tilt guiding system, atmospheric dispersion compensation, and the chromatic exposure meter. For instrument calibration, this includes the laser fRequency comb (LFC), flat-field light source, CCD detector, and effects in the optical fibers. Modal noise is mitigated to a negligible level via a chaotic fiber agitator, which is especially important for wavelength calibration with the LFC. Regarding detector effects, we empirically assess the impact on the radial-velocity precision due to pixel-position nonuniformities and charge transfer inefficiency (CTI). EXPRES has begun its science survey to discover exoplanets orbiting G-dwarf and K-dwarf stars, in addition to transit spectroscopy and measurements of the Rossiter-McLaughlin effect. © 2020. The American Astronomical Society. All rights reserved.Immediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]