Browse Prior Art Database

Method for Predicting the Temperature of Precipitation using On-line Calculations in an Operational Weather Forecast Model

IP.com Disclosure Number: IPCOM000249588D
Publication Date: 2017-Mar-07
Document File: 4 page(s) / 43K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a method to take a known, straightforward, and accurate formula for the wet-bulb temperature and integrate it into an existing computational weather forecasting model to obtain a prediction of the temperature of anticipated precipitation.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 41% of the total text.

1

Method for Predicting the Temperature of Precipitation using On-line Calculations in an Operational Weather Forecast Model

When forecasting the weather using a computer model, the temperature of rainfall landing on the earth's surface is almost always overlooked. However, it can be important for derivative forecasts, like the temperature of an urban environment, the temperature of fast moving runoff driven by a precipitation event, or on the stratification of a water body due to direct precipitation catchment or in combination with precipitation-driven stream inflow.

The novel contribution is a method to take a known, straightforward and accurate formula for the wet-bulb temperature and integrate it into an existing computational weather forecasting model to obtain a prediction of the temperature of anticipated precipitation (principally rainfall, although it can be applied with some accuracy to snow).

The wet-bulb temperature is the temperature a parcel of air would have if it were cooled to saturation (100% relative humidity) by the evaporation of water into it, with the latent heat being supplied by the parcel. Model and laboratory studies of the evaporation and condensation of a freely falling droplet of water (i.e., rainfall) show that its temperature is very close to the ambient wet-bulb temperature (within 0.2 C). In very dry conditions, the wet-bulb temperature can be more than 10 degrees cooler than the sensible, ambient air temperature, hence, it is critical to use the wet-bulb temperature to estimate the temperature of a falling raindrop.

At every model timestep of a computational weather forecasting model forecast, the method calculates the surface wet-bulb temperature (TW) and the total precipitation (P) for the entire model grid. The method is to then multiply these values together to get the rainfall-weighted wet-bulb temperature (PTW ) and 'accumulate' this value over the forecast period to get PTWacc . In other words, at each model timestep, the current rainfall-weighted wet-bulb temperature is added to the previous 'accumulated' rainfall-weighted wet-bulb temperature for the entire model grid.

At the model output time (every 10 minutes, 30 minutes, 1 hour, 6 hours, etc. depending on the forecast purpose), the derived PTWacc field is output with other standard variables (which includes the accumulated precipitation). PTWacc can then be normalized using the accumulated precipitation to obtain the average rainfall-weighted wet-bulb temperature over a given period (PTW-ave) .

PTW-ave is a direct proxy for the average temperature of rainfall over the specified period. Importantly, PTW-ave reflects any significant changes in the temperature of the rainfall during this period, like during the passage of a storm when the temperature of rainfall can change by several degrees in minutes (e.g., see Fig. 3 of Anderson et. al 1998).

2

This method can improve derivative forecasts where the temperature of rainfall is important (e.g., tem...