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Ralph D. Reynolds

Abstract

Synchronous radar, temperature and pressure data of suitable quality, gathered from three balloon flights of the Mountain Wave Project, were analyzed in detail to show the relationships between balloon-depicted waves and isentropic and isopycnic waves. Results show that in wave conditions, superpressure balloons: 1) follow the undulations of density surfaces but overestimate crests and troughs of waves by an average error of 6%; and 2) follow isentropic surfaces, but underestimate true wave crests by.an average error of 5%, and true wave troughs by errors averaging 30%.

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Ralph D. Reynolds

A procedure for using the 700-mb dew point temperature as an objective aid for forecasting the occurrence or nonoccurrence of cumuloform showers in southern Arizona is presented with verification data.

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Ralph D. Reynolds
and
Roy L. Lamberth

Abstract

A cause of erroneous temperatures obtained in the earlier phases of a study using standard radiosondes flown on constant-level balloons at White Sands Missile Range is discussed. A simple and inexpensive modification of the radiosondes which produces more accurate ambient temperatures on daylight flights is described.

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Ralph D. Reynolds
,
Roy L. Lamberth
, and
M. G. Wurtele

Abstract

A complex mountain lee wave was recorded by radar-tracked superpressure balloons at White Sands Missile Range on 6 May 1965 at a mean altitude of 3.5 km MSL; simultaneously, a very weak wave was recorded at 7 km. The lower complex wave showed variable wavelengths, amplitudes, and increasing vertical velocities with time.

Several of the better existing mountain wave theories were tested against the data to determine which theory or theories, if any, could explain the physical cause of the particular features of the complex wave.

It was found that existing theoretical models are too simplified to apply to the condition in the observed wave and explain only its grosser features. If our understanding of gravity waves is to be adequate to explain quantitatively what we are capable of observing quantitatively, we must begin the analysis of more realistic models or turn to numerical integration of the relevant equations.

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Roy I. Glass
,
Ralph D. Reynolds
, and
Roy L. Lamberth

Abstract

This paper describes how continuous pressure measurements may be obtained by making a relatively simple modification to any standard or clock-switched radiosonde which can be flown on a rising or floating balloon. The continuous pressure device is composed of an aneroid sensor which controls the frequency of a subcarrier oscillator. Frequency modulation of the radiosonde transmitting tube is used instead of amplitude modulation. The receiver for this system utilizes the standard GMD-1B ground tracker with a special demodulator, the standard TMQ-5 recorder, and a frequency counter with printer. Each pressure sensor is calibrated for frequency vs. pressure; precision of reading the pressure is to 1 mb as currently used, but readings to 0.1 mb are easily obtainable.

Pressure data from three superpressure balloon flights are presented to show the detail obtained by the instrument with this modification. This modified instrument provides the research meteorologist with a new inexpensive research tool.

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Carolyn A. Reynolds
,
James D. Doyle
,
F. Martin Ralph
, and
Reuben Demirdjian

Abstract

The initial-state sensitivity and optimal perturbation growth for 24- and 36-h forecasts of low-level kinetic energy and precipitation over California during a series of atmospheric river (AR) events that took place in early 2017 are explored using adjoint-based tools from the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). This time period was part of the record-breaking winter of 2016–17 in which several high-impact ARs made landfall in California. The adjoint sensitivity indicates that both low-level winds and precipitation are most sensitive to mid- to lower-tropospheric perturbations in the initial state in and near the ARs. A case study indicates that the optimal moist perturbations occur most typically along the subsaturated edges of the ARs, in a warm conveyor belt region. The sensitivity to moisture is largest, followed by temperature and winds. A 1 g kg−1 perturbation to moisture may elicit twice as large a response in kinetic energy and precipitation as a 1 m s−1 perturbation to the zonal or meridional wind. In an average sense, the sensitivity and related optimal perturbations are very similar for the kinetic energy and precipitation response functions. However, on a case-by-case basis, differences in the sensitivity magnitude and optimal perturbation structures result in substantially different forecast perturbations, suggesting that optimal adaptive observing strategies should be metric dependent. While the nonlinear evolved perturbations are usually smaller (by about 20%, on average) than the expected linear perturbations, the optimal perturbations are still capable of producing rapid nonlinear perturbation growth. The positive correlation between sensitivity magnitude and wind speed forecast error or precipitation forecast differences supports the relevance of adjoint-based calculations for predictability studies.

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F. M. Ralph
,
E. Sukovich
,
D. Reynolds
,
M. Dettinger
,
S. Weagle
,
W. Clark
, and
P. J. Neiman

Abstract

Extreme precipitation events, and the quantitative precipitation forecasts (QPFs) associated with them, are examined. The study uses data from the Hydrometeorology Testbed (HMT), which conducted its first field study in California during the 2005/06 cool season. National Weather Service River Forecast Center (NWS RFC) gridded QPFs for 24-h periods at 24-h (day 1), 48-h (day 2), and 72-h (day 3) forecast lead times plus 24-h quantitative precipitation estimates (QPEs) from sites in California (CA) and Oregon–Washington (OR–WA) are used. During the 172-day period studied, some sites received more than 254 cm (100 in.) of precipitation. The winter season produced many extreme precipitation events, including 90 instances when a site received more than 7.6 cm (3.0 in.) of precipitation in 24 h (i.e., an “event”) and 17 events that exceeded 12.7 cm (24 h)−1 [5.0 in. (24 h)−1]. For the 90 extreme events {>7.6 cm (24 h)−1 [3.0 in. (24 h)−1]}, almost 90% of all the 270 QPFs (days 1–3) were biased low, increasingly so with greater lead time. Of the 17 observed events exceeding 12.7 cm (24 h)−1 [5.0 in. (24 h)−1], only 1 of those events was predicted to be that extreme. Almost all of the extreme events correlated with the presence of atmospheric river conditions. Total seasonal QPF biases for all events {i.e., ≥0.025 cm (24 h)−1 [0.01 in. (24 h)−1]} were sensitive to local geography and were generally biased low in the California–Nevada River Forecast Center (CNRFC) region and high in the Northwest River Forecast Center (NWRFC) domain. The low bias in CA QPFs improved with shorter forecast lead time and worsened for extreme events. Differences were also noted between the CNRFC and NWRFC in terms of QPF and the frequency of extreme events. A key finding from this study is that there were more precipitation events >7.6 cm (24 h)−1 [3.0 in. (24 h)−1] in CA than in OR–WA. Examination of 422 Cooperative Observer Program (COOP) sites in the NWRFC domain and 400 in the CNRFC domain found that the thresholds for the top 1% and top 0.1% of precipitation events were 7.6 cm (24 h)−1 [3.0 in. (24 h)−1] and 14.2 cm (24 h)−1 [5.6 in. (24 h)−1] or greater for the CNRFC and only 5.1 cm (24 h)−1 [2.0 in. (24 h)−1] and 9.4 cm (24 h)−1 [3.7 in. (24 h)−1] for the NWRFC, respectively. Similar analyses for all NWS RFCs showed that the threshold for the top 1% of events varies from ∼3.8 cm (24 h)−1 [1.5 in. (24 h)−1] in the Colorado Basin River Forecast Center (CBRFC) to ∼5.1 cm (24 h)−1 [3.0 in. (24 h)−1] in the northern tier of RFCs and ∼7.6 cm (24 h)−1 [3.0 in. (24 h)−1] in both the southern tier and the CNRFC. It is recommended that NWS QPF performance in the future be assessed for extreme events using these thresholds.

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Reuben Demirdjian
,
James D. Doyle
,
Carolyn A. Reynolds
,
Joel R. Norris
,
Allison C. Michaelis
, and
F. Martin Ralph

Abstract

Analysis of a strong landfalling atmospheric river is presented that compares the evolution of a control simulation with that of an adjoint-derived perturbed simulation using the Coupled Ocean–Atmosphere Mesoscale Prediction System. The initial-condition sensitivities are optimized for all state variables to maximize the accumulated precipitation within the majority of California. The water vapor transport is found to be substantially enhanced at the California coast in the perturbed simulation during the time of peak precipitation, demonstrating a strengthened role of the orographic precipitation forcing. Similarly, moisture convergence and vertical velocities derived from the transverse circulation are found to be substantially enhanced during the time of peak precipitation, also demonstrating a strengthened role of the dynamic component of the precipitation.

Importantly, both components of precipitation are associated with enhanced latent heating by which (i) a stronger diabatically driven low-level potential vorticity anomaly strengthens the low-level wind (and thereby the orographic precipitation forcing), and (ii) greater moist diabatic forcing enhances the Sawyer–Eliassen transverse circulation and thereby increases ascent and dynamic precipitation. A Lagrangian parcel trajectory analysis demonstrates that a positive moisture perturbation within the atmospheric river increases the moisture transport into the warm conveyor belt offshore, which enhances latent heating in the perturbed simulation. These results suggest that the precipitation forecast in this case is particularly sensitive to the initial moisture content within the atmospheric river due to its role in enhancing both the orographic precipitation forcing and the dynamic component of precipitation.

Open access
Rebecca E. Stone
,
Carolyn A. Reynolds
,
James D. Doyle
,
Rolf H. Langland
,
Nancy L. Baker
,
David A. Lavers
, and
F. Martin Ralph

Abstract

Atmospheric rivers, often associated with impactful weather along the west coast of North America, can be a challenge to forecast even on short time scales. This is attributed, at least in part, to the scarcity of eastern Pacific in situ observations. We examine the impact of assimilating dropsonde observations collected during the Atmospheric River (AR) Reconnaissance 2018 field program on the Navy Global Environmental Model (NAVGEM) analyses and forecasts. We compare NAVGEM’s representation of the ARs to the observations, and examine whether the observation–background difference statistics are similar to the observation error variance specified in the data assimilation system. Forecast sensitivity observation impact is determined for each dropsonde variable, and compared to the impacts of the North American radiosonde network. We find that the reconnaissance soundings have significant beneficial impact, with per observation impact more than double that of the North American radiosonde network. Temperature and wind observations have larger total and per observation impact than moisture observations. In our experiment, the 24-h global forecast error reduction from the reconnaissance soundings can be comparable to the reduction from the North American radiosonde network for the field program dates that include at least two flights.

Free access
Carolyn A. Reynolds
,
Rebecca E. Stone
,
James D. Doyle
,
Nancy L. Baker
,
Anna M. Wilson
,
F. Martin Ralph
,
David A. Lavers
,
Aneesh C. Subramanian
, and
Luca Centurioni

Abstract

Under the Atmospheric River Reconnaissance (AR Recon) Program, ocean drifting buoys (drifters) that provide surface pressure observations were deployed in the northeastern Pacific Ocean to improve forecasts of U.S. West Coast high-impact weather. We examine the impacts of both AR Recon and non-AR Recon drifter observations in the U.S. Navy’s global atmospheric data assimilation (DA) and forecast system using data-denial experiments and forecast sensitivity observation impact (FSOI) analysis, which estimates the impact of each observation on the 24-h global forecast error total energy. Considering all drifters in the eastern North Pacific for the 2020 AR Recon season, FSOI indicates that most of the beneficial impacts come from observations in the lowest quartile of observed surface pressure values, particularly those taken late in the DA window. Observations in the upper quartile have near-neutral impacts on average and are slightly nonbeneficial when taken late in the DA window. This may occur because the DA configuration used here does not account for model biases, and innovation statistics show that the forecast model has a low pressure bias at high pressures. Case studies and other analyses indicate large beneficial impacts coming from observations in regions with large surface pressure gradients and integrated vapor transport, such as fronts and ARs. Data-denial experiments indicate that the assimilation of AR Recon drifter observations results in a better-constrained analysis at nearby non-AR Recon drifter locations and counteracts the NAVGEM pressure bias. Assimilating the AR Recon drifter observations improves 72- and 96-h Northern Hemisphere forecasts of winds in the lower and middle troposphere, and geopotential height in the lower, middle, and upper troposphere.

Significance Statement

The purpose of this study is to understand how observations of atmospheric pressure at the ocean surface provided by drifting buoys impact weather forecasts. Some of these drifting buoys were deployed under a program to study atmospheric rivers (ARs) to improve forecasts of high-impact weather on the West Coast. We find that these observations are most effective at reducing forecast errors when taken in regions near fronts and cyclones. The additional drifting buoys deployed under the AR Reconnaissance project reduce forecast errors at 72 and 96 h over North America and the Northern Hemisphere. These results are important because they illustrate the potential for improving forecasts by increasing the number of drifting buoy surface pressure observations over the world oceans.

Free access