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David Samuel Williams

Abstract

Participatory modeling is commonly applied in climate change adaptation research to integrate stakeholder knowledge, beliefs, values, and norms into modeling processes. However, participation is not neutral, and current climate change adaptation research is tailored toward those with sufficient resources to adapt, as opposed to those most in need of adaptation. These are commonly marginalized stakeholder groups who remain on the social, economic, and political periphery, driving their vulnerability to climate change impacts. This paper presents the concept of autonomy in the context of multilevel governance for climate change adaptation before examining past participatory modeling approaches, illustrating the lack of application as an emancipatory tool for increasing the autonomy of marginalized stakeholder groups. Therefore, a list of 10 necessary conditions is presented for conducting participatory modeling for increasing the autonomy of marginalized stakeholder groups, strengthening multilevel governance for climate change adaptation. These theoretical foundations are intended to guide public policy and increase the societal impact of participatory modeling.

Significance Statement

Responding to climate change impacts requires the strengthening of multilevel governance. An important aspect is that multilevel governance is dependent on local actors having sufficient autonomy to carry out climate change adaptation actions. Participatory climate change adaptation research can contribute to enhancing autonomy for climate change adaptation in applying participatory modeling. This paper explains why this is important, how participatory modelers need to design their research, and in what way this could contribute to strengthening multilevel governance and the wider societal response to climate change impacts.

If you’re a scholar who studies the social impacts of climate change and you aren’t somehow an activist what are you really?—Professor Kian Goh, University of California, Los Angeles

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David Atlas and Christopher R. Williams

Abstract

This study provides a very clear picture of the microphysics and flow field in a convective storm in the Rondonia region of Brazil through a synthesis of observations from two unique radars, measurements of the surface drop size distribution (DSD), and particle types and sizes from an aircraft penetration. The primary findings are 1) the growth of rain by the collision–coalescence–breakup (CCB) process to equilibrium drop size distributions entirely below the 0°C level; 2) the subsequent growth of larger ice particles (graupel and hail) at subfreezing temperatures; 3) the paucity of lightning activity during the former process, and the increased lightning frequency during the latter; 4) the occurrence of strong downdrafts and a downburst during the latter phase of the storm resulting from cooling by melting and evaporation; 5) the occurrence of turbulence along the main streamlines of the storm; and 6) the confirmation of the large drops reached during the CCB growth by polarimetric radar observations. These interpretations have been made possible by estimating the updraft magnitude using the “lower bound” of the Doppler spectrum at vertical incidence, and identifying the “balance level” at which particles are supported for growth. The combination of these methods shows where raindrops are supported for extended periods to allow their growth to equilibrium drop size distributions, while smaller drops ascend and large ones descend. A hypothesis worthy of pursuit is the control of the storm motion by the winds at the balance level, which is the effective precipitation generating level. Above the 0°C level the balance level separates the small ascending ice crystals from the large descending graupel and hail. Collisions between the two cause electrical charging, while gravity and the updrafts separate the charges to cause lightning. Below the 0°C level, large downward velocities (caused by the above-mentioned cooling) in excess of the terminal fall speeds of raindrops represent the downbursts, which are manifested in the surface winds.

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David P. Marshall, Richard G. Williams, and Mei-Man Lee

Abstract

The dynamical control of the eddy-induced transport is investigated in a series of idealized eddy-resolving experiments. When there is an active eddy field, the eddy-induced transport is found to correlate with isopycnic gradients of potential vorticity, rather than gradients of layer thickness. For any unforced layers, the eddy transfer leads to a homogenization of potential vorticity and a vanishing of the eddy-induced transport in the final steady state.

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David Atlas, Carlton W. Ulbrich, and Christopher R. Williams

Abstract

A unique set of Doppler and polarimetric radar observations were made of a microburst-producing storm in Amazonia during the Tropical Rainfall Measuring Mission (TRMM) Large-Scale Biosphere–Atmosphere (LBA) field experiment. The key features are high reflectivity (50 dBZ) and modest size hail (up to 0.8 mm) in high liquid water concentrations (>4 g m−3) at the 5-km 0°C level, melting near the 3-km level as evidenced by the Doppler spectrum width on the profiler radar (PR), by differential polarization on the S-band dual-polarized radar (S-POL), and a sharp downward acceleration from 2.8 to 1.6 km to a peak downdraft of 11 m s−1, followed by a weak microburst of 15 m s−1 at the surface. The latter features closely match the initial conditions and results of the Srivastava numerical model of a microburst produced by melting hail. It is suggested that only modest size hail in large concentrations that melt aloft can produce wet microbursts. The narrower the distribution of hail particle sizes, the more confined will be the layer of melting and negative buoyancy, and the more intense the microburst. It is hypothesized that the timing of the conditions leading to the microburst is determined by the occurrence of an updraft of proper magnitude in the layer in which supercooled water accounts for the growth of hail or graupel.

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David Ahijevych, James O. Pinto, John K. Williams, and Matthias Steiner

Abstract

A data mining and statistical learning method known as a random forest (RF) is employed to generate 2-h forecasts of the likelihood for initiation of mesoscale convective systems (MCS-I). The RF technique uses an ensemble of decision trees to relate a set of predictors [in this case radar reflectivity, satellite imagery, and numerical weather prediction (NWP) model diagnostics] to a predictand (in this case MCS-I). The RF showed a remarkable ability to detect MCS-I events. Over 99% of the 550 observed MCS-I events were detected to within 50 km. However, this high detection rate came with a tendency to issue false alarms either because of premature warning of an MCS-I event or in the continued elevation of RF forecast likelihoods well after an MCS-I event occurred. The skill of the RF forecasts was found to increase with the number of trees and the fraction of positive events used in the training set. The skill of the RF was also highly dependent on the types of predictor fields included in the training set and was notably better when a more recent training period was used. The RF offers advantages over high-resolution NWP because it can be run in a fraction of the time and can account for nonlinearly varying biases in the model data. In addition, as part of the training process, the RF ranks the importance of each predictor, which can be used to assess the utility of new datasets in the prediction of MCS-I.

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David A. Williams, Kevin J. Horsburgh, David M. Schultz, and Chris W. Hughes

Abstract

On the morning of 23 June 2016, a 0.70-m meteotsunami was observed in the English Channel between the United Kingdom and France. This wave was measured by several tide gauges and coincided with a heavily precipitating convective system producing 10 m s−1 wind speeds at the 10-m level and 1–2.5-hPa surface pressure anomalies. A combination of precipitation rate cross correlations and NCEP–NCAR Reanalysis 1 data showed that the convective system moved northeastward at 19 ± 2 m s−1. To model the meteotsunami, the finite element model Telemac was forced with an ensemble of prescribed pressure forcings, covering observational uncertainty. Ensembles simulated the observed wave period and arrival times within minutes and wave heights within tens of centimeters. A directly forced wave and a secondary coastal wave were simulated, and these amplified as they propagated. Proudman resonance was responsible for the wave amplification, and the coastal wave resulted from strong refraction of the primary wave. The main generating mechanism was the atmospheric pressure anomaly with wind stress playing a secondary role, increasing the first wave peak by 16% on average. Certain tidal conditions reduced modeled wave heights by up to 56%, by shifting the location where Proudman resonance occurred. This shift was mainly from tidal currents rather than tidal elevation directly affecting shallow-water wave speed. An improved understanding of meteotsunami return periods and generation mechanisms would be aided by tide gauge measurements sampled at less than 15-min intervals.

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David R. Easterling, Grant Goodge, Matthew J. Menne, Claude N. Williams Jr., and David Levinson

Abstract

Temperature time series for stations in western North Carolina are used to evaluate the potential for an urban signal in the local temperature trend, and to compare a homogeneous temperature record from a mountain-top station to two versions of the lower-tropospheric, satellite-derived temperatures from the Microwave Sounding Unit (MSU). Results regarding the urban signal are in agreement with the conclusion from previous investigations that after a location is urbanized, the local temperature trend is consistent with trends derived from surrounding, more rural stations. With respect to the mountain top and lower-tropospheric temperature comparison, the magnitudes of the two MSU-derived trends for the western North Carolina area are closer to the average annual minimum temperature trend than to the annual average maximum temperature trend.

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David A. Williams, David M. Schultz, Kevin J. Horsburgh, and Chris W. Hughes

Abstract

Meteotsunamis are shallow-water waves that, despite often being small (~0.3 m), can cause damage, injuries, and fatalities due to relatively strong currents (>1 m s−1). Previous case studies, modeling, and localized climatologies have indicated that dangerous meteotsunamis can occur across northwest Europe. Using 71 tide gauges across northwest Europe between 2010 and 2017, a regional climatology was made to understand the typical sizes, times, and atmospheric systems that generate meteotsunamis. A total of 349 meteotsunamis (54.0 meteotsunamis per year) were identified with 0.27–0.40-m median wave heights. The largest waves (~1 m high) were measured in France and the Republic of Ireland. Most meteotsunamis were identified in winter (43%–59%), and the fewest identified meteotsunamis occurred in either spring or summer (0%–15%). There was a weak diurnal signal, with most meteotsunami identifications between 1200 and 1859 UTC (30%) and the fewest between 0000 and 0659 UTC (23%). Radar-derived precipitation was used to identify and classify the morphologies of mesoscale precipitating weather systems occurring within 6 h of each meteotsunami. Most mesoscale atmospheric systems were quasi-linear systems (46%) or open-cellular convection (33%), with some nonlinear clusters (17%) and a few isolated cells (4%). These systems occurred under westerly geostrophic flow, with Proudman resonance possible in 43 out of 45 selected meteotsunamis. Because most meteotsunamis occur on cold winter days, with precipitation, and in large tides, wintertime meteotsunamis may be missed by eyewitnesses, helping to explain why previous observationally based case studies of meteotsunamis are documented predominantly in summer.

Open access
Ali Tokay, David A. Short, Christopher R. Williams, Warner L. Ecklund, and Kenneth S. Gage

Abstract

The motivation for this research is to move in the direction of improved algorithms for the remote sensing of rainfall, which are crucial for meso- and large-scale circulation studies and climate applications through better determinations of precipitation type and latent heating profiles. Toward this end a comparison between two independent techniques, designed to classify precipitation type from 1) a disdrometer and 2) a 915-MHz wind profiler, is presented, based on simultaneous measurements collected at the same site during the Intensive Observing Period of the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment. Disdrometer-derived quantities such as differences in drop size distribution parameters, particularly the intercept parameter N 0 and rainfall rate, were used to classify rainfall as stratiform or convective. At the same time, profiler-derived quantities, namely, Doppler velocity, equivalent reflectivity, and spectral width, from Doppler spectra were used to classify precipitation type in four categories: shallow convective, deep convective, mixed convective–stratiform, and stratiform.

Overall agreement between the two algorithms is found to be reasonable. Given the disdrometer stratiform classification, the mean profile of reflectivity shows a distinct bright band and associated large vertical gradient in Doppler velocity, both indicators of stratiform rain. For the disdrometer convective classification the mean profile of reflectivity lacks a bright band, while the vertical gradient in Doppler velocity below the melting level is opposite to the stratiform case. Given the profiler classifications, in the order shallow–deep–mixed–stratiform, the composite raindrop spectra for a rainfall rate of 5 mm h−1 show an increase in D 0, the median volume diameter, consistent with the dominant microphysical processes responsible for drop formation. Nevertheless, the intercomparison does reveal some limitations in the classification methodology utilizing the disdrometer or profiler algorithms in isolation. In particular, 1) the disdrometer stratiform classification includes individual cases in which the vertical profiles appear convective, but these usually occur at times when the disdrometer classification is highly variable; 2) the profiler classification scheme also appears to classify precipitation too frequently as stratiform by including cases that have small vertical Doppler velocity gradients at the melting level but no bright band; and 3) the profiler classification scheme includes a category of mixed (stratiform–convective) precipitation that has some features in common with deep convection (e.g., enhanced spectral width above the melting level) but other features in common with stratiform precipitation (e.g., well-developed melting layer signature). Comparison of the profiler-derived vertical structure with disdrometer-determined rain rates reveals that almost all cases of rain rates greater than 10 mm h−1 are convective. For rain rates less than 5 mm h−1 all four profiler-determined precipitation classes are well represented.

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Simon D. P. Williams, Paul S. Bell, David L. McCann, Richard Cooke, and Christine Sams

Abstract

A low-cost [$30 (U.S. dollars)] consumer grade GPS receiver with a sideways-mounted antenna has been applied to measure tidal water levels at a mesotidal coastal site using an interferometric reflectometry approach. The proof-of-concept system was installed approximately 16 m above mean sea level in close proximity to a conventional bubbler tide gauge that provided validation data. The received signal-to-noise ratios (SNR) for the satellites in view were recorded for several months during two successive years and the observed frequencies of the interferometric oscillations used to calculate the difference in elevation between the receiver and the water surface. Comparisons with concurrent and historic in situ tide gauge data at the site initially helped to identify a calibration issue with the in situ gauge. The GPS-based measurements were shown to be in excellent agreement with the corrected in situ gauge, exhibiting a root-mean-square difference of 5.7 cm over a tidal range exceeding 3 m at spring tides and a daily averaged RMS of 1.7 cm. The SNR data from the low-cost GPS receivers are shown to provide significantly higher-quality data for this purpose compared with high-end geodetic grade receivers at similar sites. This low-cost, widely available technology has the potential to be applied globally for monitoring water levels in a wide variety of circumstances and applications that would otherwise be cost or situation prohibitive. It could also be applied as an independent cross check and quality control measure for conventional water-level gauges.

Open access