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.

5 Aug 2022

Simulating Environmental Conditions for Southwest United States Convective Dust Storms Using the Weather Research and Forecasting Model v4.1

Abstract: Dust aerosols can pose a significant detriment to public health, transportation, and tactical operations through reductions in air quality and visibility. Thus, accurate model forecasts of dust emission and transport are essential to decision makers. While a large number of studies have advanced the understanding and predictability of dust storms, the majority of existing literature considers dust production and forcing conditions of the underlying meteorology independently of each other. Our study works towards filling this research gap by inventorying dust-event case studies forced by convective activity in the Desert Southwest United States, simulating select representative case studies using several configurations of the Weather Research and Forecasting (WRF) model, testing the sensitivity of forecasts to essential model parameters, and assessing overall forecast skill using variables essential to dust production and transport. We found our control configuration captured the initiation, evolution, and storm structure of a variety of convective features admirably well. Peak wind speeds were well represented, but we found that simulated events arrived up to 2 hours earlier or later than observed. Our results show that convective storms are highly sensitive to initialization time and initial conditions that can preemptively dry the atmosphere and suppress the growth of convective storms.