scholarly journals Validation of a Tropical Cyclone Steering Response Function with a Barotropic Adjoint Model

2010 ◽  
Vol 67 (6) ◽  
pp. 1806-1816 ◽  
Author(s):  
Brett T. Hoover ◽  
Michael C. Morgan
Keyword(s):  
Tropical Cyclone ◽  
Response Function ◽  
Initial Conditions ◽  
Model Verification ◽  
Response Functions ◽  
Adjoint Sensitivity ◽  
Final Time ◽  
Steering Vector ◽  
Sensitivity Studies ◽  
Forecast State

Abstract The steering of a tropical cyclone (TC) vortex is commonly understood as the advection of the TC vortex by an “environmental wind.” In past studies, the environmental steering wind vector has been defined by the horizontal and vertical averaging of the horizontal winds in a box centered on the TC. The components of this environmental steering have been proposed as response functions to derive adjoint-derived sensitivities of TC zonal and meridional steering. The appropriateness of these response functions in adjoint sensitivity studies of TC steering is tested using a two-dimensional barotropic model and its adjoint for a 24-h forecast. It is found that these response functions do not produce sensitivities to TC steering because perturbations to the model initial conditions that change the final-time location of the TC also change the response functions in ways that have nothing to do with the steering of the TC at model verification. An alternate response function is proposed wherein the environmental steering vector is defined as the wind averaged over the response function box attributed to vorticity outside of that box. By redefining the response functions for the zonal and meridional steering as components of this environmental steering vector, the effect of small changes to the final-time location of the TC is removed, and the resultant sensitivity gradients can be shown to truly represent the sensitivity of TC steering to perturbations of the model forecast state.

scholarly journals Application of Adjoint-Derived Forecast Sensitivities to the 24–25 January 2000 U.S. East Coast Snowstorm

2005 ◽  
Vol 133 (11) ◽  
pp. 3148-3175 ◽  
Author(s):  
Daryl T. Kleist ◽  
Michael C. Morgan
Keyword(s):  
Response Function ◽  
Initial Conditions ◽  
Forecast Error ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Vertical Motion ◽  
Initial Condition ◽  
Response Functions ◽  
Eastern United States ◽  
Surface Cyclone

Abstract The 24–25 January 2000 eastern United States snowstorm was noteworthy as operational numerical weather prediction (NWP) guidance was poor for lead times as short as 36 h. Despite improvements in the forecast of the surface cyclone position and intensity at 1200 UTC 25 January 2000 with decreasing lead time, NWP guidance placed the westward extent of the midtropospheric, frontogenetically forced precipitation shield too far to the east. To assess the influence of initial condition uncertainties on the forecast of this event, an adjoint model is used to evaluate forecast sensitivities for 36- and 48-h forecasts valid at 1200 UTC 25 January 2000 using as response functions the energy-weighted forecast error, lower-tropospheric circulation about a box surrounding the surface cyclone, 750-hPa frontogenesis, and vertical motion. The sensitivities with respect to the initial conditions for these response functions are in general very similar: geographically isolated, maximized in the middle and lower troposphere, and possessing an upshear vertical tilt. The sensitivities are maximized in a region of enhanced low-level baroclinicity in the vicinity of the surface cyclone’s precursor upper trough. However, differences in the phase and structure of the gradients for the four response functions are evident, which suggests that perturbations could be constructed to alter one response function but not necessarily the others. Gradients of the forecast error response function with respect to the initial conditions are used in an iterative procedure to construct initial condition perturbations that reduce the forecast error. These initial condition perturbations were small in terms of both spatial scale and magnitude. Those initial condition perturbations that were confined primarily to the midtroposphere grew rapidly into much larger amplitude upper-and-lower tropospheric perturbations. The perturbed forecasts were not only characterized by reduced final time forecast error, but also had a synoptic evolution that more closely followed analyses and observations.

scholarly journals Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization

2011 ◽  
Vol 24 (12) ◽  
pp. 2963-2982 ◽  
Author(s):  
Andrea Alessandri ◽  
Andrea Borrelli ◽  
Silvio Gualdi ◽  
Enrico Scoccimarro ◽  
Simona Masina
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Wind Shear ◽  
Large Scale ◽  
Initial Conditions ◽  
North Pacific Ocean ◽  
Convective Available Potential Energy ◽  
Seasonal Prediction ◽  
Boreal Summer ◽  
Prediction System

Abstract This study investigates the predictability of tropical cyclone (TC) seasonal count anomalies using the Centro Euro-Mediterraneo per i Cambiamenti Climatici–Istituto Nazionale di Geofisica e Vulcanologia (CMCC-INGV) Seasonal Prediction System (SPS). To this aim, nine-member ensemble forecasts for the period 1992–2001 for two starting dates per year were performed. The skill in reproducing the observed TC counts has been evaluated after the application of a TC location and tracking detection method to the retrospective forecasts. The SPS displays good skill in predicting the observed TC count anomalies, particularly over the tropical Pacific and Atlantic Oceans. The simulated TC activity exhibits realistic geographical distribution and interannual variability, thus indicating that the model is able to reproduce the major basic mechanisms that link the TCs’ occurrence with the large-scale circulation. TC count anomalies prediction has been found to be sensitive to the subsurface assimilation in the ocean for initialization. Comparing the results with control simulations performed without assimilated initial conditions, the results indicate that the assimilation significantly improves the prediction of the TC count anomalies over the eastern North Pacific Ocean (ENP) and northern Indian Ocean (NI) during boreal summer. During the austral counterpart, significant progresses over the area surrounding Australia (AUS) and in terms of the probabilistic quality of the predictions also over the southern Indian Ocean (SI) were evidenced. The analysis shows that the improvement in the prediction of anomalous TC counts follows the enhancement in forecasting daily anomalies in sea surface temperature due to subsurface ocean initialization. Furthermore, the skill changes appear to be in part related to forecast differences in convective available potential energy (CAPE) over the ENP and the North Atlantic Ocean (ATL), in wind shear over the NI, and in both CAPE and wind shear over the SI.

IMPROVING EXTRACTION OF IMPULSE RESPONSE FUNCTIONS USING STATIONARY WAVELET SHRINKAGE IN TERAHERTZ REFLECTION IMAGING

2010 ◽  
Vol 09 (04) ◽  
pp. 387-394 ◽  
Author(s):  
YANG CHEN ◽  
YIWEN SUN ◽  
EMMA PICKWELL-MACPHERSON
Keyword(s):  
Experimental Data ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Terahertz Imaging ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Inverse Filtering ◽  
Wavelet Shrinkage ◽  
Gaussian Filtering

In terahertz imaging, deconvolution is often performed to extract the impulse response function of the sample of interest. The inverse filtering process amplifies the noise and in this paper we investigate how we can suppress the noise without over-smoothing and losing useful information. We propose a robust deconvolution process utilizing stationary wavelet shrinkage theory which shows significant improvement over other popular methods such as double Gaussian filtering. We demonstrate the success of our approach on experimental data of water and isopropanol.

scholarly journals Using adjoint sensitivity as a local structure function in variational data assimilation

2001 ◽  
Vol 8 (6) ◽  
pp. 347-355 ◽  
Author(s):  
G. Hello ◽  
F. Bouttier
Keyword(s):  
Data Assimilation ◽  
Structure Function ◽  
Local Structure ◽  
Initial Conditions ◽  
Storm Track ◽  
Variational Data Assimilation ◽  
Sensitive Area ◽  
Adjoint Sensitivity ◽  
Weather Events ◽  
Gradient Fields

Abstract. One approach recently proposed in order to improve the forecast of weather events, such as cyclogenesis, is to increase the number of observations in areas depending on the flow configuration. These areas are obtained using, for example, the sensitivity to initial conditions of a selected predicted cyclone. An alternative or complementary way is proposed here. The idea is to employ such an adjoint sensitivity field as a local structure function within variational data assimilation, 3D-Var in this instance. Away from the sensitive area, observation increments project on the initial fields with the usual climatological (or weakly flow-dependent, in the case of 4D-Var) structure functions. Within the sensitive area, the gradient fields are projected using all the available data in the zone, conventional or extra, if any. The formulation of the technique is given and the approach is further explained by using a simple 1D scheme. The technique is implemented in the ARPEGE/IFS code and applied to 11 FASTEX (Fronts and Atlantic Storm-Track Experiment) cyclone cases, together with the targeted observations performed at the time of the campaign. The new approach is shown to allow for the desired stronger impact of the available observations and to systematically improve the forecasts of the FASTEX cyclones, unlike the standard 3D-Var.

Identification of Rotating Asymmetry in Rotating Machines by Using Reverse dFRF

1999 ◽  
Author(s):  
Chong-Won Lee ◽  
Kye-Si Kwon
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Modal Testing ◽  
Vibration Sensor ◽  
Response Functions ◽  
Physical Realization ◽  
Simple Method ◽  
Testing Method ◽  
Asymmetric Rotor

Abstract A quick and easy but comprehensive identification method for asymmetry in an asymmetric rotor is proposed based on complex modal testing method. In this work, it is shown that the reverse directional frequency response function (reverse dFRF), which indicates the degree of asymmetry, can be identified with a simple method requiring only one vibration sensor and one exciter. To clarify physical realization associated with estimation of the reverse dFRF, its relation to the conventional frequency response functions, which are defined by the real input (exciter) and output (vibration sensor), are extensively discussed.

scholarly journals Impact of Gulfstream-IV Dropsondes on Tropical Cyclone Prediction in a Regional OSSE System

2019 ◽  
Vol 147 (8) ◽  
pp. 2961-2977 ◽  
Author(s):  
Kelly Ryan ◽  
Lisa Bucci ◽  
Javier Delgado ◽  
Robert Atlas ◽  
Shirley Murillo
Keyword(s):  
Tropical Cyclone ◽  
Real Time ◽  
Environmental Conditions ◽  
The United States ◽  
Track Forecast ◽  
Deterministic Models ◽  
Research Division ◽  
Sensitivity Studies ◽  
Potential Impact ◽  
The Impact

Abstract Aircraft reconnaissance missions remain the primary means of collecting direct measurements of marine atmospheric conditions affecting tropical cyclone formation and evolution. The National Hurricane Center tasks the NOAA G-IV aircraft to sample environmental conditions that may impact the development of a tropical cyclone threatening to make landfall in the United States or its territories. These aircraft data are assimilated into deterministic models and used to produce real-time analyses and forecasts for a given tropical cyclone. Existing targeting techniques aim to optimize the use of reconnaissance observations and partially rely on regions of highest uncertainty in the Global Ensemble Forecast System. Evaluating the potential impact of various trade-offs in the targeting process is valuable for determining the ideal aircraft flight track for a prospective mission. AOML’s Hurricane Research Division has developed a system for performing regional observing system simulation experiments (OSSEs) to assess the potential impact of proposed observing systems on hurricane track and intensity forecasting. This study focuses on improving existing targeting methods by investigating the impact of proposed aircraft observing system designs through various sensitivity studies. G-IV dropsonde retrievals were simulated from a regional nature run, covering the life cycle of a rapidly intensifying Atlantic hurricane. Results from sensitivity studies provide insight into improvements for real-time operational synoptic surveillance targeting for hurricanes and tropical storms, where dropsondes released closer to the vortex–environment interface provide the largest impact on the track forecast. All dropsonde configurations provide a positive 2-day impact on intensity forecasts by improving the environmental conditions known to impact tropical cyclone intensity.

scholarly journals Power spectrum response of large-scale structure in 1D and in 3D: tests of prescriptions for post-collapse dynamics

2020 ◽  
Vol 499 (2) ◽  
pp. 1769-1787
Author(s):  
Anaëlle Halle ◽  
Takahiro Nishimichi ◽  
Atsushi Taruya ◽  
Stéphane Colombi ◽  
Francis Bernardeau
Keyword(s):  
Power Spectrum ◽  
Response Function ◽  
Large Scale ◽  
Initial Conditions ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Adaptive Smoothing ◽  
Single Stream ◽  
Non Linear ◽  
Spectrum Response

ABSTRACT The power spectrum response function of the large-scale structure of the Universe describes how the evolved power spectrum is modified by a small change in initial power through non-linear mode coupling of gravitational evolution. It was previously found that the response function for the coupling from small to large scales is strongly suppressed in amplitude, especially at late times, compared to predictions from perturbation theory (PT) based on the single-stream approximation. One obvious explanation for this is that PT fails to describe the dynamics beyond shell crossing. We test this idea by comparing measurements in N-body simulations to prescriptions based on PT but augmented with adaptive smoothing to account for the formation of non-linear structures of various sizes in the multistream regime. We first start with one-dimensional (1D) cosmology, where the Zel’dovich approximation provides the exact solution in the single-stream regime. Similarly to the three-dimensional (3D) case, the response function of the large-scale modes exhibits a strong suppression in amplitude at small scales that cannot be explained by the Zel’dovich solution alone. However, by performing adaptive smoothing of initial conditions to identify haloes of different sizes and solving approximately post-collapse dynamics in the three-stream regime, agreement between theory and simulations drastically improves. We extend our analyses to the 3D case using the pinocchio algorithm, in which similar adaptive smoothing is implemented on the Lagrangian PT fields to identify haloes and is combined with a spherical halo prescription to account for post-collapse dynamics. Again, a suppression is found in the coupling between small- and large-scale modes and the agreement with simulations is improved.

Comparing the Vertical Structures of Weighting Functions and Adjoint Sensitivity of Radiance and Verifying Mesoscale Forecasts Using AIRS Radiance Observations

2008 ◽  
Vol 136 (4) ◽  
pp. 1327-1348 ◽  
Author(s):  
Matthew J. Carrier ◽  
Xiaolei Zou ◽  
William M. Lapenta
Keyword(s):  
Sensitivity Analysis ◽  
Weighting Function ◽  
Model Space ◽  
Forecast Model ◽  
Model Atmosphere ◽  
Model Verification ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Adjoint Sensitivity Analysis ◽  
Adjoint Sensitivity

Abstract An adjoint sensitivity analysis is conducted using the adjoint of the hyperspectral radiative transfer model (RTM) that simulates the radiance spectrum from the Advanced Infrared Sounder (AIRS). It is shown, both theoretically and numerically, that the height of the maximum sensitivity of radiance in a channel could be higher or lower than the height of the maximum weighting function of that channel. It is shown that the discrepancy between the two heights is determined by the vertical structures of the atmospheric thermodynamic state. The sensitivity finds the level at which changes in temperature and/or moisture will have the largest influence on the simulated brightness temperature (BT), and the maximum weighting function (WF) height indicates the level where the model atmosphere contributes most significantly to the emission at the top of the atmosphere. Based on the above findings, an adjoint method for forecast verification using AIRS radiances is presented. In this method, model forecasts are first mapped into radiance space by an RTM so that they can be compared directly with the observed radiance values. The adjoint sensitivity analysis results are then used to connect the deviations of the model forecasts from observed radiances to the changes of temperature and moisture variables in model space. This adjoint sensitivity based model verification provides useful information on forecast model performances based on indirect observations from satellites.

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