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Roger M. Wakimoto, Zachary Wienhoff, Dylan Reif, Howard B. Bluestein, and David C. Lewellen

Abstract

Mobile, polarimetric radar data were collected on a series of tornadoes that occurred near Dodge City, Kansas. A poststorm survey revealed a series of tornadic debris swaths in several dirt fields and high-resolution pictures of the tornado documented the visual characteristics of the tornado and the lofted debris cloud. The main rotational couplet associated with the tornado was identified in the single-Doppler velocities; however, no secondary rotational couplets were resolved in the low-level data performed during two consecutive volume scans. Numerical simulations have suggested that cycloidal damage swaths can result when debris is deposited as the low-level inflow turns upward in the corner region of the updraft annulus of the tornado core. This mechanism can dominate even when suction vortices are present in the simulations and can produce these swaths in the absence of these smaller-scale vortices. It is hypothesized that the observed cycloidal damage swaths were a result of the low-level inflow in the corner region of the tornado and not by the existence of suction vortices. Polarimetric data were combined with photographs of the tornado in order to document the lofted debris cloud and its relationship with the funnel. This analysis provided an opportunity to investigate whether recent findings describing the cross-correlation coefficient ρ hv and differential reflectivity Z DR signatures of the lofted debris cloud could be replicated. Regions of low ρ hv at the periphery of the funnel cloud suggesting high debris loading and a column of negative Z DR centered on the tornado believed to be produced by common debris alignment were noted.

Significance Statement

It is well known that some tornadoes produce smaller-scale vortices that rotate around the central axis of the main circulation. In addition, numerous aerial photographs have documented cycloidal debris marks within tornado damage tracks that traverse open fields. The prevailing theory shown in numerous textbooks is that these marks are produced by these vortices. The current study suggests that this widely accepted model for producing these marks may be incorrect. It is suggested that these cycloidal marks are produced by the main tornado circulation and not by the smaller-scale vortices in this case.

Open access
N. C. Privé, R. M. Errico, and Amal El Akkraoui

Abstract

The potential impact of large numbers of Global Navigation Satellite System radio occultation (GNSS-RO) observations on numerical weather prediction is investigated using a global observing system simulation experiment (OSSE). The hybrid four-dimensional ensemble variational Gridpoint Statistical Interpolation (GSI) data assimilation system and Global Earth Observing System (GEOS) model are used to ingest up to 100 000 GNSS-RO soundings per day in addition to the current suite of conventional and radiance data. Analysis quality, forecast skill, and forecast sensitivity to observation impact are examined with differing quantities of additional GNSS-RO profiles. It is found that saturation of information from additional RO soundings has not been reached with 100 000 soundings per day. There are some indications of suboptimal performance of the GSI in handling GNSS-RO observations particularly in the middle- and lower-tropospheric extratropics.

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Brenda Dolan, Steven A. Rutledge, and Kristen L. Rasmussen

Abstract

Orographic precipitation results from complex interactions between terrain, large-scale flow, turbulent motions, and microphysical processes. This study appeals to polarimetric radar data in conjunction with surface-based disdrometer observations, airborne particle probes, and reanalysis data to study these processes and their interactions as observed during the Olympic Mountain Experiment (OLYMPEX). Radar and disdrometer observations from OLYMPEX, which was conducted over the Olympic Peninsula in the winter of 2015, revealed 3 times as much rain fell over elevated sites compared to those along the ocean and coast. Several events were marked by significant water vapor transport and strong onshore flow. Detailed analysis of four cases demonstrated that the warm sector, which previous authors noted to be a period of strong orographic enhancement over the terrain, is associated not only with deeper warm cloud regions, but also deeper cold cloud regions, with the latter supporting the growth of dendritic ice crystals between 4 and 6 km. This dendritic growth promotes enhanced aggregation just above the melting layer, which then seeds the warm cloud layer below, allowing additional drop growth via coalescence. Periods of subsynoptic variability associated with mesoscale boundaries and low-level jets are shown to locally modify both the ice microphysics as well as surface drop-size distributions. This study explores the spatial and temporal variability of precipitation, cloud microphysics, and their relationship over the complex terrain of the Olympic Peninsula.

Significance Statement

This study appeals to polarimetric radar, aircraft particle probes, disdrometer data, and reanalysis to investigate the complex interactions between large frontal systems, terrain, and microphysical processes contributing to precipitation characteristics at the surface over the Olympic Peninsula. The study finds that the precipitation is a complex function of the synoptic regime, distance inland, and terrain height. Ice microphysical processes aloft act to modulate the surface rain drop size distributions, and are more important in contributing to higher rain accumulations inland during the later phases of the warm sector, particularly over the middle terrain heights (100–500 m).

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Clayton R. S. Sasaki, Angela K. Rowe, Lynn A. McMurdie, and Kristen L. Rasmussen

Abstract

The Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) campaign produced unparalleled observations of the South American low-level jet (SALLJ) in central Argentina with high temporal observations located in the path of the jet and upstream of rapidly growing convection. The vertical and temporal structure of the jet is characterized using 3-hourly soundings launched at two fixed sites near the Sierras de Córdoba (SDC), along with high-resolution reanalysis data. Objective SALLJ identification criteria are applied to each sounding to determine the presence, timing, and vertical characteristics of the jet. The observations largely confirm prior results showing that SALLJs most frequently come from the north, occur overnight, and peak in the low levels, though SALLJs notably peaked higher near the end of longer-duration events during RELAMPAGO. This study categorizes SALLJs into shorter-duration events with jet cores peaking overnight in the low levels and longer 5–6-day events with elevated jets near the end of the period that lack a clear diurnal cycle. Evidence of both boundary layer processes and large-scale forcing were observed during shorter-duration events, whereas synoptic forcing dominated the longer 5–6-day events. The highest amounts of moisture and larger convective coverage east of the SDC occurred near the end of the 5–6-day SALLJ events.

Significance Statement

The South American low-level jet (SALLJ) is an area of enhanced northerly winds that likely contributes to long-lived, widespread thunderstorms in Southeastern South America (SESA). This study uses observations from a recent SESA field project to improve understanding of the variability of the SALLJ and the underlying processes. We related jet occurrence to upper-level environmental patterns and differences in the progression speed of those patterns to varying durations of the jet. Longer-duration jets were more elevated, transported moisture southward from the Amazon, and coincided with the most widespread storms. These findings enable future research to study the role of the SALLJ in the life cycle of storms in detail, leading to improved storm prediction in SESA.

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Hristo G. Chipilski, Xuguang Wang, David B. Parsons, Aaron Johnson, and Samuel K. Degelia

Abstract

There is a growing interest in the use of ground-based remote sensors for numerical weather prediction, which is sparked by their potential to address the currently existing observation gap within the planetary boundary layer. Nevertheless, open questions still exist regarding the relative importance of and synergy among various instruments. To shed light on these important questions, the present study examines the forecast benefits associated with several different ground-based profiling networks using 10 diverse cases from the Plains Elevated Convection at Night (PECAN) field campaign. Aggregated verification statistics reveal that a combination of in situ and remote sensing profilers leads to the largest increase in forecast skill, in terms of both the parent mesoscale convective system and the explicitly resolved bore. These statistics also indicate that it is often advantageous to collocate thermodynamic and kinematic remote sensors. By contrast, the impacts of networks consisting of single profilers appear to be flow-dependent, with thermodynamic (kinematic) remote sensors being most useful in cases with relatively low (high) convective predictability. Deficiencies in the data assimilation method as well as inherent complexities in the governing moisture dynamics are two factors that can further limit the forecast value extracted from such networks.

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Carolyn A. Reynolds, William Crawford, Andrew Huang, Neil Barton, Matthew A. Janiga, Justin McLay, Maria Flatau, Sergey Frolov, and Clark Rowley

Abstract

High-fidelity analyses and forecasts of integrated vapor transport (VT) are central to the study of Earth’s hydrological cycle as well as high-impact phenomena such as monsoons and atmospheric rivers. The impact of the in-line analysis correction-based additive inflation (ACAI) on IVT biases and forecast errors is examined within the Navy Earth System Prediction Capability (Navy ESPC) global coupled system. The ACAI technique uses atmospheric analysis corrections from the data assimilation system to approximate model bias and as a representation of stochastic model error to simultaneously reduce systematic and random errors and improve ensemble performance. ACAI reduces the global average magnitude of the 7- and 14-day IVT bias by 16%–17% during Northern Hemisphere summer, reaching 70% reductions in some tropical regions. The global average IVT bias reduction is similar to the bias reduction for low-level wind speed bias and considerably smaller than the bias reduction in total precipitable water. The localized regions where ACAI increases IVT bias occur where the control IVT biases change sign and structure with increasing forecast lead time, such as the South Asian monsoon region. Substituting analyzed wind or moisture fields for the forecast fields when calculating the forecast IVT confirms that, on average, wind errors dominate the IVT error calculation in the tropics, although wind and moisture error contributions are comparable in the extratropics. The existence of regions where using either analyzed winds or analyzed moisture increases IVT bias or mean absolute error reveals areas with compensating errors.

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Phuong-Nghi Do, Kao-Shen Chung, Pay-Liam Lin, Ching-Yin Ke, and Scott M. Ellis

Abstract

This study investigated the effect of the assimilation of the S- and Ka-band dual‐wavelength-retrieved water vapor data with radial wind and reflectivity data. The vertical profile of humidity, which provides environmental information before precipitation occurs, was obtained at low levels and thinned into averaged and four-quadrant profiles. Additionally, the following two strategies were examined: 1) assimilation of water vapor data with radar data for the entire 2 h and 2) assimilation of water vapor data in the first hour, and radial velocity and reflectivity data in the second hour. By using the WRF local ensemble transform Kalman filter data assimilation system, three real cases of the Dynamics of the Madden–Julian Oscillation experiment were examined through a series of experiments. The analysis results revealed that assimilating additional water vapor data more markedly improved the analysis at the convective scale than assimilating radial wind and reflectivity data alone. In addition, the strategy of assimilating only retrieved water vapor data in the first hour and radial wind and reflectivity data in the second hour achieved the optimal analysis and subsequent very short-term forecast. The evaluation of quantitative precipitation forecasting demonstrated that assimilating additional retrieved water vapor data distinctly improved the rain forecast compared with assimilating radar data only. When moisture data were assimilated, improved nowcasting could be extended up to 4 h. Furthermore, assimilating moisture profiles into four quadrants achieved more accurate analysis and forecast. Overall, our study demonstrated that the humidify information in nonprecipitation areas is critical for further improving the analysis and forecast of convective weather systems.

Open access
David I. Duncan, Niels Bormann, Alan J. Geer, and Peter Weston

Abstract

Radiances from microwave temperature sounders have been assimilated operationally at ECMWF for two decades, but observations significantly affected by clouds and precipitation have been screened out. Extending successful assimilation beyond clear-sky scenes is a challenge that has taken several years of development to achieve. In this paper we describe the all-sky treatment of AMSU-A, which enables greater numbers of temperature sounding radiances to be used in meteorologically active parts of the troposphere. Successful all-sky assimilation required combining lessons learned from the clear-sky assimilation of AMSU-A with the approach initially developed for humidity-sensitive microwave radiances. This concerned particularly observation thinning, error modeling, and variational quality control. As a result of the move to all-sky assimilation, the forecast impact of AMSU-A now replicates and exceeds that of the previous clear-sky usage. This is shown via trials in comparison to the current ECMWF assimilation system, judged with respect to forecast scores and background fits to independent observations. Persistently cloudy regions and phenomena such as tropical cyclones are better sampled when assimilating AMSU-A in all-sky conditions, causing an increase of about 13% in used channel-5 radiances globally. These impacts are explored, with an emphasis on tropical cyclones in the 2019 season. Independent observations provide consistent evidence that representation of humidity is improved, for example, while extratropical Z500 forecasts are improved by about 0.5% out to at least day 2. On the strength of these results, assimilation of AMSU-A moved to all-sky conditions with the upgrade to IFS cycle 47R3 in October 2021.

Open access
Mathieu Lachapelle and Julie M. Thériault

Abstract

Freezing rain and ice pellets are particularly difficult to forecast when solid precipitation is completely melted aloft. This study addresses this issue by investigating the processes that led to a long-duration ice pellet event in Montreal, Québec, Canada, on 11–12 January 2020. To do so, a benchmark model initialized with ERA5 data is used to show that solid precipitation was completely melted below the melting layer, which discards partial melting from the possible ice pellet formation processes. Macro photography of precipitation reveals that small columnar crystals (∼200 μm) and ice pellets occurred simultaneously for more than 10 h. The estimation of ice crystal number concentration using macro photographs and laser-optical disdrometer data suggests that all supercooled drops could have refrozen by contact freezing with ice crystals. Rimed ice pellets also indicate ice supersaturation in the subfreezing layer. Given these observations, the formation of ice pellets and ice crystals was probably promoted by secondary ice production and the horizontal advection of ice crystals below the melting layer, as we illustrate using a conceptual model. Overall, these findings demonstrate how ice nucleation processes at temperatures near 0°C can drastically change the precipitation phase and the impact of a storm.

Significance Statement

Ice pellets are generally formed when snow particles partially melt while falling through a warm layer aloft before completely refreezing in a cold layer closer to the surface. Ice pellets can also be formed when snow particles completely melt aloft, but freezing rain is often produced in such conditions. On 11–12 January 2020, ice pellets were produced during more than 10 h in Montreal, Quebec, Canada. Macro photographs of the precipitation particles show that ice pellets occurred simultaneously with small ice crystals. Most of the ice pellets were produced while snow particles were completely melted aloft. The supercooled drops probably refroze due to collisions with the ice crystals that could have been advected by the northeasterly winds near the surface.

Open access
Roland Potthast, Klaus Vobig, Ulrich Blahak, and Clemens Simmer

Abstract

We investigate the assimilation of nowcasted information into a classical data assimilation cycle. As a reference setup, we employ the assimilation of standard observations such as direct observations of particular variables into a forecasting system. The pure advective movement extrapolation of observations as a simple nowcasting (NWC) is usually much better for the first minutes to hours, until outperformed by numerical weather prediction (NWP) based on data assimilation. Can nowcasted information be used in the data assimilation cycle? We study both an oscillator model and the Lorenz 63 model with assimilation based on the localized ensemble transform Kalman filter (LETKF). We investigate and provide a mathematical framework for the assimilation of nowcasted information, approximated as a local tendency, into the LETKF in each assimilation step. In particular, we derive and discuss adequate observation error and background uncertainty covariance matrices and interpret the assimilation of nowcasted information as assimilation with an H 1-type metric in observation space. Further, we show numerical results that prove that nowcasted information in data assimilation has the potential to significantly improve model based forecasting.

Open access