Browse

You are looking at 1 - 10 of 17,913 items for :

  • Monthly Weather Review x
  • Refine by Access: All Content x
Clear All
Chong Wang
and
Xiaofeng Li

Abstract

This article developed a deep learning (DL) model for estimating tropical cyclone (TC) 34-, 50-, and 64-kt (1 kt ≈ 0.51 m s−1) wind radii in four quadrants from infrared images in the global ocean. We collected 63 675 TC images from 2004 to 2016 and divided them into three periods (2004–12, 2013–14, and 2015–16) for model training, validation, and testing. First, four DL-based radius estimation models were developed to estimate the TC wind radius for each of the four quadrants. Then, the entire original images and the one-quarter-quadrant subimages were included in the model training for each quadrant. Last, we modified the mean absolute error (MAE) loss function in these DL-based models to reduce the side effect of an unbalanced distribution of wind radii and developed an asymmetric TC wind radius estimation model globally. The comparison of model results with the best-track data of TCs shows that the MAEs of 34-kt wind radius are 18.8, 19.5, 18.6, and 18.8 n mi (1 n mi = 1.852 km) for the northeast, southeast, southwest, and northwest quadrants, respectively. The MAEs of 50-kt wind radius are 11.3, 11.3, 11.1, and 10.8 n mi, respectively, and the MAEs of 64-kt wind radius are 8.9, 9.9, 9.2, and 8.7 n mi, respectively. These results represent a 12.1%–35.5% improvement over existing methods in the literature. In addition, the DL-based models were interpreted with two deep visualization toolboxes. The results indicate that the TC eye, cloud, and TC spiral structure are the main factors that affect the model performance.

Restricted access
Tong Ren
,
Ping Yang
,
Kevin Garrett
,
Yingtao Ma
,
Jiachen Ding
, and
James Coy

Abstract

The satellite observational data assimilation community requires consistent hydrometer descriptions—including mass–size relation and particle size distribution—to be used in both the forecast model and observation operator. We develop a microphysics-scheme-consistent snow and graupel single-scattering property database to meet this requirement. In this database, snowflakes are modeled as a mixture of small column and large aggregated ice particles, the mixing ratios of which may be adjusted to satisfy a given mass–size relation. Snow single-scattering properties are computed for four different mass–size relations. Subsequently, the snow description in the Thompson microphysics scheme is used as an example to demonstrate how microphysics-scheme-consistent snow bulk optical properties are derived. The Thompson-scheme-consistent snow bulk optical properties are added to the Community Radiative Transfer Model (CRTM), version 2.4.0. With CloudSat Cloud Profiling Radar (CPR) snow and liquid precipitation retrievals as the inputs, CRTM simulations are performed over global oceans and compared with four collocated Global Precipitation Measurement (GPM) Microwave Imager (GMI) high-frequency channel observations. The CRTM simulated brightness temperatures show agreement with the GMI observed brightness temperatures in cases of light-to-moderate precipitation over extratropical and polar ice-free oceans, with root-mean-square errors of 4.3, 13.0, 1.8, and 3.3 K in the 166-GHz (vertical polarization), 166-GHz (horizontal polarization), 183 ± 3-GHz (vertical polarization), and 183 ± 7-GHz (vertical polarization) channels, respectively. The result demonstrates the potential of using the newly developed microphysics-scheme-consistent snow optical parameterization in data assimilation applications.

Restricted access
Jaynise M. Pérez Valentín
,
Harindra J. S. Fernando
,
G. S. Bhat
,
Hemantha W. Wijesekera
,
Jayesh Phadtare
, and
Edgar Gonzalez

Abstract

The relationship between eastward-propagating convective equatorial signals (CES) along the equatorial Indian Ocean (EIO) and the northward-propagating monsoon intraseasonal oscillations (MISOs) in the Bay of Bengal (BOB) was studied using observational datasets acquired during the 2018 and 2019 MISO-BOB field campaigns. Convective envelopes of MISOs originating from just south of the BOB were associated with both strong and weak eastward CES (average speed ∼6.4 m s−1). Strong CES contributed to ∼20% of the precipitation budget of BOB, and they spurred northward-propagating convective signals that matched the canonical speed of MISOs (1–2 m s−1). In contrast, weak CES contributed to ∼14% of the BOB precipitation budget, and they dissipated without significant northward propagation. Eastward-propagating intraseasonal oscillations (ISOs; period 30–60 days) and convectively coupled Kelvin waves (CCKWs; period 4–15 days) accounted for most precipitation variability across the EIO during the 2019 boreal summer as compared with that of 2018. An agreement could be noted between high moisture content in the midtroposphere and the active phases of CCKWs and ISOs for two observational locations in the BOB. Basin-scale thermodynamic conditions prior to the arrival of strong or weak CES revealed warmer or cooler sea surface temperatures, respectively. Flux measurements aboard a research vessel suggest that the evolution of MISOs associated with strong CES are signified by local enhanced air–sea interactions, in particular the supply of local moisture and sensible heat, which could enhance deep convection and further moisten the upper troposphere.

Significance Statement

Eastward-propagating convective signals along the equatorial Indian Ocean and their relationship to the northward-propagating spells of rainfall that lead to moisture variability in the Bay of Bengal are studied for the 2018 and 2019 southwest monsoon seasons using observational datasets acquired during field campaigns. Strong convective equatorial signals spurred northward-propagating convection, as compared with weak signals that dissipated without significant northward propagation. Wave spectral analysis showed CCKWs (period 4–15 days), and eastward ISOs (period 30–60 days) accounted for most of the precipitation variability, with the former dominating during the 2018 boreal summer. High moisture periods observed from radiosonde measurements show agreement with the active phases of CCKWs and ISOs.

Restricted access
Andrew Brown
,
Andrew Dowdy
,
Todd P. Lane
, and
Stacey Hitchcock

Abstract

Severe winds associated with thunderstorms and convection are a hazard affecting key aspects of society, including emergency management and infrastructure design. Several studies around the world have shown that severe convective winds (SCWs) can occur due to several different processes, in a range of atmospheric environments, with significant regional and temporal variations. However, in eastern Australia, the types of SCWs and their variability have not been assessed outside of individual case studies. Here, a combination of reanalysis, lightning, radar, and station data are used to characterize a set of 36 SCW events in four locations in eastern Australia. These events are objectively chosen based on the strongest measured wind gusts from station data (greater than 25 m s−1) over a 14-yr period, with 6-hourly lightning data and a 30-dBZ radar reflectivity threshold used to infer moist convective processes. Radar data analysis suggests that these SCW events are produced by several different types of parent thunderstorms, with station observations suggesting a range of temporal characteristics for these different event types. A clustering algorithm applied to environmental data is used to suggest three dominant types of events, based on low-level moisture, low-level temperature lapse rate, and deep-layer mean wind speed and vertical shear. Based on the distribution of synoptic conditions and thunderstorm properties for each environmental cluster, it is suggested that these three event types correspond to the following: 1) shallow vertical transport of strong synoptic-scale winds to the surface, 2) downbursts driven by subcloud evaporation, and 3) intense thunderstorms including supercells.

Significance Statement

The purpose of this study is to better understand the different types of severe wind events in eastern Australia that are produced by convective storms. We looked at 36 historical cases in four locations and find that severe winds can be produced by very different classes of convective storms. We also suggest that there are three key types of atmospheric environment that are associated with events in this region. These environments vary in terms of the vertical structure of temperature, moisture, and wind speed above the surface. Understanding the different types of environments that lead to severe convective winds can help to reduce uncertainties in future climate projections for this region based on environmental changes.

Restricted access
Yue Yang
and
Xuguang Wang

Abstract

The sensitivity of convection-allowing forecasts over the continental United States to radar reflectivity data assimilation (DA) frequency is explored within the Gridpoint Statistical Interpolation (GSI)-based ensemble–variational (EnVar) system. Experiments with reflectivity DA intervals of 60, 20, and 5 min (RAIN60, RAIN20, and RAIN5, respectively) are conducted using 10 diverse cases. Quantitative verification indicates that the degree of sensitivity depends on storm features during the radar DA period. Five developing storms show high sensitivity, whereas five mature or decaying storms do not. The 20-min interval is the most reliable given its best overall performance compared to the 5- and 60-min intervals. Diagnostics suggest that the differences in analyzed cold pools (ACPs) among RAIN60, RAIN20, and RAIN5 vary by storm features during the radar DA period. Such ACP differences result in different forecast skills. In the case where RAIN20 outperforms RAIN60 and the case where RAIN5 outperforms RAIN20, assimilation of reflectivity with a higher frequency commonly produces enhanced and widespread ACPs, promoting broader storms that match better with reality than a lower frequency. In the case where RAIN5 performs worse than RAIN20, the model imbalance of RAIN5 overwhelms information gain associated with frequent assimilation, producing overestimated and spuriously fast-moving ACPs. In the cases where little sensitivity to the reflectivity DA frequency is found, similar ACPs are produced.

Restricted access
Philip Tuckman
,
Vince Agard
, and
Kerry Emanuel

Abstract

We analyze the evolution of convective available potential energy (CAPE) and convective inhibition (CIN) in the days leading up to episodes of high CAPE in North America. The widely accepted theory for CAPE buildup, known as the advection hypothesis, states that high moist static energy (MSE) parcels of air moving north from the Gulf of Mexico become trapped under warm but dry parcels moving east from over elevated dry terrain. If and when the resulting CIN erodes, severe convection can occur due to the large energy difference between the boundary layer parcels and cool air aloft. However, our results, obtained via backward Lagrangian tracking of parcels at locations of peak CAPE, show that large values of CAPE are generated mainly via boundary layer moistening in the days leading up to the time of peak CAPE, and that a large portion of this moisture buildup happens on the day of peak CAPE. On the other hand, the free-tropospheric temperature above these tracked parcels rarely changes significantly over the days leading up to such occurrences. In addition, the CIN that allows for this buildup of CAPE arises mostly from unusually strong boundary layer cooling the night before peak CAPE, and has a contribution from differential advection of unusually warm air above the boundary layer to form a capping inversion. These results have important implications for the climatology of severe convective events, as it emphasizes the role of surface properties and their gradients in the frequency and intensity of high CAPE occurrences.

Significance Statement

Severe convective events, such as thunderstorms, tornadoes, and hail storms, are among the most deadly and destructive weather systems. Although forecasters are quite good at predicting the probability of these events a few days in advance, there is currently no reliable seasonal prediction method of severe convection. We show that the buildup of energy for severe convection relies on both strong surface evaporation during the day of peak energy and anomalous cooling the night before. This progress represents a step toward understanding what controls the frequency of severe convective events on seasonal and longer time scales, including the effect of greenhouse gas–induced climate change.

Open access
Naveen Goutham
,
Riwal Plougonven
,
Hiba Omrani
,
Alexis Tantet
,
Sylvie Parey
,
Peter Tankov
,
Peter Hitchcock
, and
Philippe Drobinski

Abstract

Owing to the increasing share of variable renewable energies in the electricity mix, the European energy sector is becoming more weather sensitive. In this regard, skillful subseasonal predictions of essential climate variables can provide considerable socioeconomic benefits to the energy sector. The aim of this study is therefore to improve the European subseasonal predictions of 100-m wind speed and 2-m temperature, which we achieve through statistical downscaling. We employ redundancy analysis (RDA) to estimate spatial patterns of variability from large-scale fields that allow for the best prediction of surface fields. We compare explanatory powers between the patterns obtained using RDA against those derived using principal component analysis (PCA), when used as predictors in multilinear regression models to predict surface fields, and show that the explanatory power of the former is superior to that of the latter. Subsequently, we employ the estimated relationship between RDA patterns and surface fields to produce statistical probabilistic predictions of gridded surface fields using dynamical ensemble predictions of RDA patterns. We finally demonstrate how a simple combination of dynamical and statistical predictions of surface fields significantly improves the accuracy of subseasonal predictions of both variables over a large part of Europe. We attribute the improved accuracy of these combined predictions to improvements in reliability and resolution.

Open access
Michael S. Fischer
,
Paul D. Reasor
,
Brian H. Tang
,
Kristen L. Corbosiero
,
Ryan D. Torn
, and
Xiaomin Chen

Abstract

The multiscale nature of tropical cyclone (TC) intensity change under moderate vertical wind shear was explored through an ensemble of high-resolution simulations of Hurricane Gonzalo (2014). Ensemble intensity forecasts were characterized by large short-term (36-h) uncertainty, with a forecast intensity spread of over 20 m s−1, due to differences in the timing of rapid intensification (RI) onset. Two subsets of ensemble members were examined, referred to as early-RI and late-RI members. The two ensemble groups displayed significantly different vortex evolutions under the influence of a nearby upper-tropospheric trough and an associated dry-air intrusion. Mid-to-upper-tropospheric ventilation in late-RI members was linked to a disruption of inner-core diabatic heating, a more tilted vortex, and vortex breakdown, as the simulated TCs transitioned from a vorticity annulus toward a monopole structure. A column-integrated moist static energy (MSE) budget revealed the important role of horizontal advection in depleting MSE from the TC core, while mesoscale subsidence beneath the dry-air intrusion acted to dry a deep layer of the troposphere. Eventually, the dry-air intrusion retreated from late-RI members as vertical wind shear weakened, the magnitude of vortex tilt decreased, and late-RI members began to rapidly intensify, ultimately reaching a similar intensity as early-RI members. Conversely, the vortex structures of early-RI members were shown to exhibit greater intrinsic resilience to tilting from vertical wind shear, and early-RI members were able to fend off the dry-air intrusion relatively unscathed. The different TC intensity evolutions can be traced back to differences in the initial TC vortex structure and intensity.

Significance Statement

Despite recent advances, tropical cyclone intensity forecasts struggle to accurately predict episodes of rapid intensification. Such forecasts become increasingly challenging when a storm is embedded within an environment of moderate vertical wind shear. This study uses an ensemble of high-resolution simulations to examine how environmental influences can affect the tropical cyclone vortex and precipitation structure, which, in turn, modulate the intensity of the storm and the onset of rapid intensification. We propose a feedback that exists where slightly weaker and less resilient vortices are more susceptible to ventilation from dry, environmental air, aided in part by differential advection from the tilted circulation, resulting in a degradation of vortex organization and a delayed onset of rapid intensification.

Restricted access
Kuo-Feng Chang
,
Chun-Chieh Wu
, and
Kosuke Ito

Abstract

This work investigates the rapid weakening (RW) processes of Typhoon Trami (2018) by examining sea surface temperature (SST) cooling based on air–sea coupled simulations during typhoon passage. The cold wake and Trami’s RW occurred as the storm was moving at a very slow translation speed. A marked structural change of Trami is found in a three-dimensional ocean-coupled model experiment during the RW stage, in which the convective clouds and convective bursts in the inner core of the simulated TC dramatically decrease, resulting in the loss of diabatic heating and leading to weakening of the TC. In the simulation, the enthalpy flux dramatically decreases in the inner core because of the SST cooling during the RW period, while a stable boundary layer (SBL) is formed in the TC’s inner-core region. The expanding SBL coverage stabilizes the atmosphere and suppresses convection in the inner core, leading to weakening of the storm. A more stable atmosphere in the cold wake is also identified by the inner-core dropsonde data from the field program of Tropical Cyclones-Pacific Asian Research Campaign for Improvement of Intensity Estimations/Forecasts. The strong SST cooling also changes the evolution of Trami’s eyewall replacement cycle (ERC) and limits the eyewall contraction after the ERC.

Restricted access
Takeshi Horinouchi
,
Satoki Tsujino
,
Masahiro Hayashi
,
Udai Shimada
,
Wataru Yanase
,
Akiyoshi Wada
, and
Hiroyuki Yamada

Abstract

Dynamics of low-level flows in the eye of Typhoon Haishen (2020) in its late phase of intensification are investigated with a special rapid-scan observation of the Himawari-8 geosynchronous satellite conducted every 30 s. This is accomplished by deriving storm-relative atmospheric motion vectors at an unprecedentedly high spatiotemporal resolution by tracking clouds across five consecutive visible-light reflectivity. The overall low-level circulation center was situated several kilometers away from the storm center defined in terms of the inner edge of the lower part of eyewall clouds. The shift direction is rearward of the storm translation, consistently with a numerical study of the tropical cyclone (TC) boundary layer. Over the analysis period of 10 h, azimuthal-mean tangential wind around this center was increased at each radius within the eye, and the rotational angular velocity was nearly homogenized. The instantaneous low-level circulation center is found to orbit around the overall circulation center at distances around 5 km. Its orbital angular speed was close to the maximum angular speed of azimuthal-mean tangential winds. This rotating transient disturbance is found to transport angular momentum inward, which explains the tangential wind increase and the angular velocity homogenization in the eye. These features are consistent with an algebraically growing wavenumber-1 barotropic instability, whose impact on TC structures has not been explored. This instability enhances wavenumber-1 asymmetry in ring-shaped vorticity, which can be induced by various processes such as translation, environmental shear, and exponential barotropic instability. Therefore, it may appear broadly in TCs to affect wind distribution in their eyes.

Significance Statement

Axially asymmetric transient features in the inner cores of tropical storms have been suggested to profoundly affect the structures and the time evolutions of tropical storms. However, the scarcity of observations has hindered studying such processes observationally. By using a specially conducted high-frequency satellite imaging of Typhoon Haishen (2020), we derived atmospheric motion vectors nearly homogeneously at an unprecedentedly high spatiotemporal resolution. Various kinds of asymmetric motions in low-level flows in the eye were found. Of particular interest is a special type of wavenumber-1 instability whose role has not drawn much attention; the instability was found to provide angular momentum transport consistent with the measured homogenization of the rotation.

Open access