Wet spring and active weather all month long

It has been a very wet spring. I measure rain in my rain gauge just about every morning. Since the beginning of April, I have measured 4.81 inches in Provo. There is actually a little little more because I accidentally spilled the water out of the gauge before I got a measurement.

At my Davis weather station in Spanish Fork, I have measured 4.44 inches since June 1st. (Had to get this info from Weather Underground because WeatherLink doesn't let me see this anymore without paying for my own data I send to them; just a little upset).

https://www.wunderground.com/dashboard/pws/KUTSPANI8/table/2019-04-23/2019-04-23/monthly

Why so much rain this year? I remember in my synoptic meteorology learning that the more wave numbers you have the more active and progressive systems are. We definitely have a high wave number in the northern hemisphere, 6+, and that means storms roll through quickly. Maybe I should dust off my synoptic meteorology notes and get a refresher on this. I'm very rusty.

Impacts of high-frequency radar-derived wind observations on COAMPS® forecasts

I recently submitted a proposal for the National Research Council Research Associateship Program (http://sites.nationalacademies.org/pga/rap/). The proposal is to work at the Naval Research Laboratory in Monterey, California as a post-doctorate researcher on a data assimilation project.

The full application can be found here: https://1drv.ms/b/s!AtJL0JL_rT9judo3fc85wl5SkgOIiQ

Abstract

Shore-based high-frequency (HF) radars are routinely used to observe ocean currents and surface wave characteristics remotely. Because surface waves are closely related to near-surface winds, many investigators have explored methods in deriving winds from HF radars, with limited success until now. Most recently, a technique has been developed that uses HF radar Doppler spectra data with the adjoints of a HF radar model and a wave prediction model to derive winds. This technique has been applied to HF radar data collected along the Santa Barbara, California coast during October 2017. These remotely sensed near-surface wind observations are likely to be valuable in initializing mesoscale analyses and forecasts in the littoral zone, as satellite-derived surface winds are generally not available near the coast. Since ocean wave models are dependent on atmospheric winds, better forecasts of near-surface winds impact almost all Naval operations near shore—especially transits in and out of ports. This work proposes to investigate the impact HF radar-derived winds have on the quality of Coupled Ocean/Atmosphere Mesoscale Prediction System® (COAMPS) analyses and forecasts using the new COAMPS-4D Variational data assimilation system. An observing system experiment is proposed to evaluate impacts from real HF radar observations on COAMPS followed by a historical observing system simulation experiment to determine potential impacts from simulated wind retrievals.

FIG. 1 Southern California coast surface wind observation network available 14 October 2017. Locations of the HF radar network are denoted by green triangles and automated weather stations and buoys are denoted by red dots.

FIG. 2 Observed near-surface vector wind at 17:25 UTC 14 October 2017 from MetOp-B ASCAT scatterometer (black) and automatic weather stations and buoys (red). Half and full barbs denote 2.5 and 5 m s^-1, respectively.

Kelvin-Helmholtz Cloud (Wave Cloud)

This Kelvin-Helmholtz cloud phenomenon was spotted from the University of Utah campus MesoWest cameras (looking south). Wikipedia: Kelvin-Helmholtz Instability.

Polar Vortex and Extreamly Cold Temperatures

A wave of cold, artic air moved into the United States late in January 2019. Many record cold temperatures were broken. You can search on the news for that.

3-years of HRRR model analyses were used to compute empirical cumulative distributions of conditions for every hour of the year (Blaylock et al. 2018). This image show how much the temperatures at 0700 UTC on 31 January 2019 are less than the 5th percentile for the same time of year. This shows that temperatures are much more than 10 degrees colder than the 5th percentile temperature.

Punch Cloud -- Salt Lake City 29 January 2019

Several punch clouds occurred over Salt Lake City on January 29, 2019. The altocumulus cloud layer is made of supercooled liquid cloud droplets. When an ice particle is introduced, probably by an aircraft, ice crystals grow rapidly at the expense of the liquid droplets. This results in ice fall streaks that fall out of the cloud and leaving a hole behind. More info at Wikipedia: Fallstreak Cloud.

Time lapse from the MesoWest cameras. 

The hole was visible from the GOES16 satellite.

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