10 Nov 2025

Spatial Analyses of Atmospheric Rivers in the Willamette River Basin of Oregon: Literature Review and Atmospheric River

Abstract: This technical note summarizes the literature review and atmospheric river (AR) detection technique data collection and initial processing activities that were performed in preparation to spatially storm type (i.e., categorize) AR extreme storm events in Oregon’s Willamette River Basin (WRB). Storm typing is performed to develop a homogeneous extreme event dataset for precipitation-frequency analyses, whose products are used to support business line (e.g., Dam and Levee Safety and Flood Risk Management) activities of the US Army Corps of Engineers (USACE). Twenty-three Atmospheric River Tracking Method Intercomparison Project (ARTMIP) Tier 1 data catalogs were collected from the US National Science Foundation’s National Center for Atmospheric Research Climate Data Gateway (Rutz et al. 2019). Each catalog models the binary presence or absence of an AR on a gridded basis, globally, at a three-hour time step from 1980 to 2016. Any ARTMIP Tier 1 catalog could effectively be selected and applied to segment AR extreme storm events for a given area by intersecting it with a prescribed precipitation dataset. However, each catalog characterizes the presence or absence of ARs differently. Hence, there exists uncertainty regarding which ARTMIP Tier 1 catalogs to select for a given practical application. This technical note addresses the uncertainty associated with ARTMIP Tier 1 catalog choice by generalizing model selection (i.e., which ARTMIP Tier 1 methods to use). Monthly climatological AR frequency was calculated throughout the WRB for each of the 23 ARTMIP Tier 1 data catalogs. Thirteen of the AR identification and tracking methods that together consistently calculated climatological AR frequency throughout the WRB were selected to form an ensemble subset. The 13-member ensemble could be used to develop AR storm type (Ralph et al. 2019) annual and seasonal maxima datasets to compute areal-precipitation-frequency estimates for the contributing drainage areas of dams in the WRB that are operated and maintained by USACE.

10 Oct 2025

Development and Management of Arctic Zonal Characterization Products: Geospatial Database

Abstract: Environmental parameters for operational planning in extreme conditions require accurate knowledge of prevailing meteorological conditions. However, the Arctic region presents unique challenges due to limited observational data and unique geographical conditions. To address the need for such knowledge, this study presents an analysis of Arctic prevailing-conditions using European Center for Medium-Range Weather Forecasting (ECMWF) Reanalysis v5 (ERA5) Data from 1991 to 2020. A custom Python-based framework was developed to process and analyze hourly datasets, identifying zones of extreme events and their frequency across multiple temporal scales. The framework uses ArcPy to automate the generation of nearly 40,000 mapped classifications for land masses 60°N and above. This automated pipeline enables both static and dynamic map generation capabilities for operational planning now and in the future. The resulting dataset provides critical spatial and temporal resolution of Arctic prevailing-conditions, enabling more refined characterization of extreme prevailing-conditions across the circumpolar region.

24 Sep 2025

Simulating Environmental Conditions for a Severe Dust Storm in Southwest Asia Using the Weather Research and Forecasting Model: A Model Configuration Sensitivity Study

Abstract: Dust aerosols create hazardous air quality conditions that affect human health, visibility, and military operations. Numerical weather prediction models are important tools for predicting atmospheric dust by simulating dust emission, transport, and chemical evolution. We assessed the Weather Research and Forecasting (WRF) model’s ability to simulate the atmospheric conditions that drove a major dust event in Southwest Asia during July–August 2018. We evaluated five WRF configurations against satellite observations and Reanalysis Version 5 (ERA5) reanalysis data, focusing on the event’s synoptic evolution, storm progression, vertical structure, and surface wind fields. Results revealed substantial differences between configurations using Noah and Noah Multiparameterization (Noah-MP) land surface models (LSMs), with Noah providing a superior representation of meteorological conditions despite theoretical expectations of similar performance in arid environments. The best-performing configuration (Noah LSM, Mellor–Yamada–Nakanishi–Niino planetary boundary layer scheme, and spectral nudging) of the five considered accurately simulated the progression of a low-level jet streak and the associated surface winds responsible for dust mobilization throughout the event. This study supports the US Army Engineer Research and Development Center’s efforts to improve dust forecasting and establishes a foundation for evaluating dust emission parameterizations by isolating meteorological forcing errors from dust model physics.

9 Sep 2025

Projecting the Longevity of Coastal Foredunes Under Stochastic Meteorological and Oceanographic Forcing

Abstract: Coastal foredunes serve as critical buffers between the ocean and beach-adjacent infrastructure, yet these features are at increasing risk of destruction from future storms and changes in sea level. Quantifying potential future hazards to dunes is complicated by an inability to forecast the exact sequencing and magnitude of future oceanographic and meteorological forcings. We used a stochastic weather emulator capable of generating time series of wind and wave properties to force a reduced complexity morphologic model to assess potential accretional and erosional dune volume changes over the next century. Inclusion of background beach erosion rates and sea level changes instead drives more frequent net volumetric dune erosion. At decadal scales, volume changes of the dune are shown to be dominated by the magnitude of shoreline change rate in locations rapidly retreating. For stable and mildly eroding shorelines, shoreline changes and changes in the still water level influence timescales of dune destruction. Sets of probabilistic simulations are used to show gradual wind-driven sediment gains can compensate for episodic wave-driven losses over the long term. However, in the case of higher sea levels, more frequent dune collision results in less time for dune recovery between major storms.

11 Jul 2024

Sharing Ships’ Weather Data via AIS: Concept and Results from Multiyear Observations

Abstract: The purpose of this Coastal and Hydraulics Engineering technical note (CHETN) is to discuss the concept, demonstrations, and the initial results of multiyear proof-of-concept testing of the capability to share weather data from ships via the Automatic Identification System (AIS). Technical foundations of this process were described by Tetreault and Johnson (2020) with partial results described in Johnston et al. 2021. The updated results in this CHETN include evaluation of the efficacy of the various application-specific message (ASM) formats use to communicate the weather observations and data reception results for selected vessels that have been participating in the proof-of-concept field deployment since 2019 or later.

2 Feb 2024

The Influence of Mesoscale Atmospheric Convection on Local Infrasound Propagation

Abstract: Infrasound—that is, acoustic waves with frequencies below the threshold of human hearing—has historically been used to detect and locate distant explosive events over global ranges (≥1,000 km). Simulations over these ranges have traditionally relied on large-scale, synoptic meteorological information. However, infrasound propagation over shorter, local ranges (0–100 km) may be affected by smaller, mesoscale meteorological features. To identify the effects of these mesoscale meteorological features on local infrasound propagation, simulations were conducted using the Weather Research and Forecasting (WRF) meteorological model to approximate the meteorological conditions associated with a series of historical, small-scale explosive test events that occurred at the Big Black Test Site in Bovina, Mississippi. These meteorological conditions were then incorporated into a full-wave acoustic model to generate meteorology-informed predictions of infrasound propagation. A series of WRF simulations was conducted with varying degrees of horizontal resolution—1, 3, and 15 km—to investigate the spatial sensitivity of these infrasound predictions. The results illustrate that convective precipitation events demonstrate potentially observable effects on local infrasound propagation due to strong, heterogeneous gradients in temperature and wind associated with the convective events themselves. Therefore, to accurately predict infrasound propagation on local scales, it may be necessary to use convection-permitting meteorological models with a horizontal resolution ≤4 km at locations and times that support mesoscale convective activity.

28 Sep 2023

Incorporating Advanced Snow Microphysics and Lateral Transport into the Noah-Multiparameterization (Noah-MP) Land Surface Model

Abstract: The dynamic state of the land surface presents challenges and opportunities for military and civil operations in extreme cold environments. In particular, the effects of snow and frozen ground on Soldier and vehicle mobility are hard to overstate. Current authoritative weather and land models are run at global scales (i.e., dx > 10 km) and are of limited use at the Soldier scale (dx < 100 m). Here, we describe several snow physics upgrades made to the Noah-Multiparameterization (Noah-MP) community land surface model (LSM). These upgrades include a blowing snow overlay to simulate the lateral redistribution of snow by the wind and the addition of new prognostic snow microstructure variables, namely grain size and bond radius. These additions represent major upgrades to the snow component of the Noah-MP LSM because they incorporate processes and methods used in more specialized snow modeling frameworks. These upgrades are demonstrated in idealized and real-world applications. The test simulations were promising and show that the newly added snow physics replicate observed behavior with reasonable accuracy. We hope these upgrades facilitate ongoing and future research on characterizing the effects of the integrated snow and soil land surface in extreme cold environments at the tactical scale.

9 Nov 2022

Meteorological Influences of a Major Dust Storm in Southwest Asia during July–August 2018

Abstract: Dust storms can be hazardous for aviation, military activities, and respiratory health and can occur on a wide variety of spatiotemporal scales with little to no warning. To properly forecast these storms, a comprehensive understanding of the meteorological dynamics that control their evolution is a prerequisite. To that end, we chose a major dust storm that occurred in Southwest Asia during July–August 2018 and conducted an observation-based analysis of the meteorological conditions that influenced the storm’s evolution. We found that the main impetus behind the dust storm was a large-scale meteorological system (i.e., a cyclone) that affected Southwest Asia. It seems that cascading effects from this system produced a smaller, near-surface warm anomaly in Mesopotamia that may have triggered the dust storm, guided its trajectory over the Arabian Peninsula, and potentially catalyzed the development of a small low-pressure system over the southeastern end of the peninsula. This low-pressure system may have contributed to some convective activity over the same region. This type of analysis may provide important information about large-scale meteorological forcings for not only this particular dust storm but also for future dust storms in Southwest Asia and other regions of the world.

15 Aug 2022

Understanding and Improving Snow Processes in Noah-MP over the Northeast United States via the New York State Mesonet

Abstract: Snow is a critical component of the global hydrologic cycle and is a key input to river and stream flow forecasts. In 2016, the National Oceanic and Atmospheric Administration launched the National Water Model (NWM) to provide a high-fidelity numerical forecast of streamflow integrated with the broader atmospheric prediction modeling framework. The NWM is coupled to the atmospheric model using the Noah-MP land surface modeling framework. While snow in Noah-MP has been consistently evaluated in the western United States, less attention has been paid to understanding and optimizing its performance in the Northeast US (NEUS). The newly installed New York State Mesonet (NYSM), a network of high-quality surface meteorological stations distributed across New York State, provides a unique opportunity to evaluate Noah-MP performance in the NEUS. In this report, we document the methodology used to perform single-column simulations using meteorological inputs from the NYSM and compare the point evaluations against baseline NWM performance. We further discuss how enhanced surface energy balance measurements at a selection of NYSM sites can be used to evaluate specific components of Noah-MP and present initial results.

2 Sep 2021

Spatial and Temporal Variance of Soil and Meteorological Properties Affecting Sensor Performance—Phase 2

ABSTRACT: An approach to increasing sensor performance and detection reliability for buried objects is to better understand which physical processes are dominant under certain environmental conditions. The present effort (Phase 2) builds on our previously published prior effort (Phase 1), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried-object detection. The study utilized a 3.05 × 3.05 m test plot in Hanover, New Hampshire. Unlike Phase 1, the current effort involved removing the soil from the test plot area, homogenizing the material, then reapplying it into eight discrete layers along with buried sensors and objects representing targets of interest. Each layer was compacted to a uniform density consistent with the background undisturbed density. Homogenization greatly reduced the microscale soil temperature variability, simplifying data analysis. The Phase 2 study spanned May–November 2018. Simultaneous measurements of soil temperature and moisture (as well as air temperature and humidity, cloud cover, and incoming solar radiation) were obtained daily and recorded at 15-minute intervals and coupled with thermal infrared and electro-optical image collection at 5-minute intervals.