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Olivier Champagne
,
Olga Zolina
,
Jean-Pierre Dedieu
,
Mareile Wolff
, and
Hans-Werner Jacobi

Abstract

The Svalbard archipelago, in the Atlantic–Arctic region, has been affected by a strong increase in precipitation in the last decades, with major potential impacts for the cryosphere, biogeochemical cycles, and the ecosystems. Ny-Ålesund (79°N), in the northwest part of Svalbard, hosts invaluable meteorological records widely used by many researchers. Among the observed parameters, the amount of precipitation is subject to large biases, mainly due to the well-known precipitation gauges undercatch during windy conditions. The purpose of this study is to investigate if the observed trend of precipitation in Ny-Ålesund in the 1975–2022 period was real and how it was impacted by the gauge undercatch. We applied several correction factors developed in the last decades, based on local wind speed and temperature. We forced these corrections with 12-hourly precipitation data from the Ny-Ålesund weather station. Taking the period 1975–2022, the trend of precipitation increased from 3.8 mm yr−1 in the observations to 4.5 mm yr−1 (±0.2) after the corrections, mainly due to enhanced snowfall in November–January months. Taking the most recent 40-yr period (1983–2022), the amount of precipitation still increased by 3.8 mm yr−1 in the observations, but only by 2.6 mm yr−1 (±0.5) after the corrections. The recent observed trend of precipitation stays large due to an increase of wet snowfall and rainfall that are measured more efficiently by the precipitation gauge. This result shows the need of applying correction factors when using precipitation gauge data, especially in regions exhibiting large interannual changes of weather conditions.

Significance Statement

The purpose of this study is to investigate if the observed trend of precipitation in Ny-Ålesund in the 1975–2022 period was real and how it was impacted by the gauge undercatch. The results show that the observed trend of precipitation was overestimated when calculated in the most recent 40-yr period (1983–2022). This overestimation was large due to an increase with time of wet snowfall and rainfall that were measured more efficiently by the precipitation gauge. This result shows the need of applying corrections factors when using precipitation gauge data, especially in regions exhibiting large interannual changes of weather conditions.

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Clifford Mass
and
David Ovens

Abstract

On 8 August 2023, a wind-driven wildfire pushed across the city of Lahaina, located in West Maui, Hawaii, resulting in at least 100 deaths and an estimated economic loss of 4-6 billion dollars. The Lahaina wildfire was associated with strong, dry downslope winds gusting to 31-41 ms−1 (60-80 kt) that initiated the fire by damaging power infrastructure. The fire spread rapidly in invasive grasses growing in abandoned agricultural land upslope from Lahaina. This paper describes the synoptic and mesoscale meteorology associated with this event, as well as its predictability. Stronger than normal northeast trade winds, accompanied by a stable layer near the crest level of the West Maui Mountains, resulted in a high-amplitude mountain wave response and a strong downslope windstorm. Mesoscale model predictions were highly accurate regarding the location, strength, and timing of the strong winds. Hurricane Dora, which passed approximately 1300 km to the south of Maui, does not appear to have had a significant impact on the occurrence and intensity of the winds associated with the wildfire event. The Maui wildfire was preceded by a wetter-than-normal winter and near-normal summer conditions.

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Timothy B. Higgins
,
Aneesh C. Subramanian
,
Will E. Chapman
,
David A. Lavers
, and
Andrew C. Winters

Abstract

Accurate forecasts of weather conditions have the potential to mitigate the social and economic damages they cause. To make informed decisions based on forecasts, it is important to determine the extent to which they could be skillful. This study focuses on subseasonal forecasts out to a lead time of four weeks. We examine the differences between the potential predictability, which is computed under the assumption of a “perfect model,” of integrated vapor transport (IVT) and precipitation under extreme conditions in subseasonal forecasts across the northeast Pacific. Our results demonstrate significant forecast skill of extreme IVT and precipitation events (exceeding the 90th percentile) into week 4 for specific areas, particularly when anomalously wet conditions are observed in the true model state. This forecast skill during weeks 3 and 4 is closely associated with a zonal extension of the North Pacific jet. These findings of the source of skillful subseasonal forecasts over the U.S. West Coast could have implications for water management in these regions susceptible to drought and flooding extremes. Additionally, they may offer valuable insights for governments and industries on the U.S. West Coast seeking to make informed decisions based on extended weather prediction.

Significance Statement

The purpose of this study is to understand the differences between the ability to predict high amounts of the transport of water vapor and precipitation over the North Pacific 3 and 4 weeks into the future. The results indicate that differences do exist in a region that is relevant to precipitation on the U.S. West Coast. To physically explain why differences in predictability exist, the relationship between weekly extremes of the extension of the jet stream, IVT, and precipitation over the North Pacific is explored. These findings may impact decisions relevant to water management on the U.S. West Coast susceptible to drought and flooding extremes.

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Chandra M. Pasillas
,
Christian Kummerow
,
Michael Bell
, and
Steven D. Miller

Abstract

Meteorological satellite imagery is a critical asset for observing and forecasting weather phenomena. The Joint Polar Satellite System (JPSS) Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) sensor collects measurements from moonlight, airglow, and artificial lights. DNB radiances are then manipulated and scaled with a focus on digital display. DNB imagery performance is tied to the lunar cycle, with best performance during the full moon and worst with the new moon. We propose using feed-forward neural networks models to transform brightness temperatures and wavelength differences in the infrared spectrum to a pseudo lunar reflectance value based on lunar reflectance values derived from observed DNB radiances. JPSS NOAA-20 and Suomi National Polar-orbiting Partnership (SNPP) satellite data over the North Pacific Ocean at night for full moon periods from December 2018 - November 2020 were used to design the models. The pseudo lunar reflectance values are quantitatively compared to DNB lunar reflectance, providing the first-ever lunar reflectance baseline metrics. The resulting imagery product, Machine Learning Night-time Visible Imagery (ML-NVI), is qualitatively compared to DNB lunar reflectance and infrared imagery across the lunar cycle. The imagery goal is not only to improve upon the consistency performance of DNB imagery products across the lunar cycle, but ultimately lay the foundation for transitioning the algorithm to geostationary sensors, making global continuous nighttime imagery possible. ML-NVI demonstrates its ability to provide DNB derived imagery with consistent contrast and representation of clouds across the full lunar cycle for night-time cloud detection.

Open access
Sipra Biswas
,
Kallol Sarkar
, and
Tapan Kumar Das

Abstract

Being situated in the estuary of the flood-dominated Hooghly River system, the macrotidal Indian Sundarban Delta (ISD) has become one of the most complex, dynamic and rapidly changing landforms on the earth’s surface. To study horizontal areal shifting of shoreline and its impact on mangrove-cover in the region, United State Geological Survey (USGS)-satellite data of 1980, 1990, 2000, 2010 and 2021 were used. Remote sensing and GIS techniques were employed in the investigation. Simultaneous prograding and retrograding shoreline shifting was distinguished almost in all the parts, though sediment-starved eastern and macrotidally more active southern lobes experienced dominantly retreating shift, and sediment-engorged western lobe demonstrated to be more dynamic. Net areal change over north-south tracks followed the trend of decreasing accretion to increasing erosion while going from west to east, whereas that over west-east tracks followed the trend of exponentially increasing erosion while going from north to south. Overall accretion of ∼91 sq. km in the ISD accounted for augmentation of sparse vegetation of ∼13 sq. km, whereas, ∼243 sq. km erosion called for depletion of sparse & moderate vegetation of ∼18 & ∼174 sq. km respectively over the 41-year period. Various oceanographic and riparian forces and actions, episodic natural events etc. vis-a-vis several anthropogenic interventions— all together contributed to such changes. The findings may help the coastal environmentalists, professionals, planners, decision-makers and implementers in formulating and taking up of suitable strategic measures for integrated and effective coastal zone management in this estuarine wetland-forest.

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Chong-Chi Tong
,
Ming Xue
,
Chengsi Liu
,
Jingyao Luo
, and
Youngsun Jung

Abstract

To improve the representation of all relevant scales in initial conditions for large-domain convection-allowing models, a new multi-scale ensemble Kalman filter (MEnKF) algorithm is developed and implemented within the GSI data assimilation framework coupled with the FV3 limited area model. The algorithm utilizes ensemble background error covariances filtered to match the observations assimilated. This is realized in a sequential manner: 1) When assimilating coarse-resolution observations such as radiosondes, ensemble background perturbations are filtered to remove scales smaller than those the observations can represent, along with relatively large horizontal localization radii to ensure low-noise and balanced analysis increments. 2) The resulting ensemble analyses from the first step then serve as the background to assimilate denser observations such as radar data with smaller localization radii. Several passes can be taken to assimilate all observations. In this paper, vertically increasing horizontal filter scales are used when assimilating rawinsonde and surface observations together while radar data are assimilated in the second step.

The algorithm is evaluated through six convective storm cases during May 2021, with cycled assimilation of either conventional data only or with additional radar reflectivity followed by 24-h ensemble forecasts. Overall, positive impacts of the MEnKF on forecasts are obtained regardless of reflectivity data; its advantage over the single-scale EnKF is most significant in surface humidity and temperature forecasts up to at least 12 hours. More accurate hourly precipitation forecasts with MEnKF can last up to 24 hours for light rain. Furthermore, MEnKF forecasts higher ensemble probabilities for the observed hazardous events.

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Falk Feddersen
,
Olavo B. Marques
,
James H. MacMahan
, and
Robert L. Grenzeback

Abstract

Wave spectra and directional moment measurements are of scientific and engineering interest and are routinely estimated with wave buoys. Recently, both fixed-location and uncrewed aircraft system (UAS)-mounted lidar have estimated surfzone wave spectra. However, nearshore wave statistics seaward of the surfzone have not been measured with lidar due to low return number, and nearshore directional moments have not been measured at all. We use a multibeam scanning lidar mounted on a gasoline-powered UAS to estimate wave spectra, wave slope spectra, and directional moments on the inner shelf in ≈10-m water depth from an 11-min hover and compare to a collocated wave buoy. Lidar returns within circular sampling regions with varying radius R are fit to a plane and a 2D parabola, providing sea surface and slope time series. Wave spectra across the sea–swell (0.04–0.4 Hz) band are robustly estimated for R ≥ 0.8 m. Estimating slope spectra is more challenging. Large R works well in the swell band, and smaller R works well at higher frequencies, in good agreement with a wave buoy inferred slope spectrum. Directional Fourier coefficients, estimated from wave and slope spectra and cross-spectra, are compared to a wave buoy in the sea–swell band. Larger R and the 2D parabola-fit yield better comparison to the wave buoy. Mean wave angles and directional spreads, functions of the directional Fourier coefficients, are well reproduced at R = 2.4 m and the 2D parabola-fit, within the uncertainties of the wave buoy. The internal consistency of the UAS-lidar-derived results and their good comparison to the Spotter wave buoy demonstrate the effectiveness of this tool for estimating wave statistics.

Significance Statement

Previously fixed-location or hovering lidar has been used to estimate wave spectra in the surf and swash zone where lidar returns are high due to the reflectance of foam. We present a methodology to accurately estimate wave spectra and directional properties on the inner shelf where waves are not breaking using a hovering uncrewed aircraft system with a mounted lidar. The estimated wave spectra and directional statistics are compared well with a Spotter wave buoy, demonstrating the method’s robustness.

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Andrew L. Stewart
,
Yan Wang
,
Aviv Solodoch
,
Ru Chen
, and
James C. McWilliams

Abstract

Eastern Boundary Upwelling Systems (EBUSs) host equatorward wind-driven near-surface currents overlying poleward subsurface undercurrents. Various previous theories for these undercurrents have emphasized the role of poleward alongshore pressure gradient forces (APF). Energetic mesoscale variability may also serve to accelerate undercurrents via mesoscale stirring of the potential vorticity gradient imposed by the continental slope. However, it remains unclear whether this eddy rectification mechanism contributes substantially to driving poleward undercurrents in EBUS. This study isolates the influence of eddy rectification on undercurrents via a suite of idealized simulations forced either by alongshore winds, with or without an APF, or by randomly-generated mesoscale eddies. It is found that the simulations develop undercurrents with strengths comparable to those found in nature in both wind-forced and randomly forced experiments. Analysis of the momentum budget reveals that the along-isobath undercurrent flow is accelerated by isopycnal advective eddy momentum fluxes and the APF, and retarded by frictional drag. The undercurrent acceleration may manifest as eddy momentum fluxes or as topographic form stress depending on the coordinate system used to compute the momentum budget, which reconciles these findings with previous work that linked eddy acceleration of the undercurrent to topographic form stress. The leading-order momentum balance motivates a scaling for the strength of the undercurrent that explains most of the variance across the simulations. These findings indicate that eddy rectification is of comparable importance to the APF in driving poleward undercurrents in EBUSs, and motivate further work to diagnose this effect in high-resolution models and observations, and to parameterize it in coarse-resolution ocean/climate models.

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