Next Article in Journal
Convolutional Neural Networks for Automated ULF Wave Classification in Swarm Time Series
Next Article in Special Issue
A Holistic Approach Based on Biomonitoring Techniques and Satellite Observations for Air Pollution Assessment and Health Risk Impact of Atmospheric Trace Elements in a Semi-Rural Area of Southern Italy (High Sauro Valley)
Previous Article in Journal
Lag Effect of Temperature and Humidity on COVID-19 Cases in 11 Chinese Cities
Previous Article in Special Issue
Using Daylight Saving Time Clock Changes to Study the Impact of Meteorology on Air Pollution
 
 
Article

How Should a Numerical Weather Prediction Be Used: Full Field or Anomaly? A Conceptual Demonstration with a Lorenz Model

by 1,* and 2
1
Environmental Modeling Center, National Centers for Environmental Prediction/NOAA, 5830 University Research Court, College Park, MD 20740, USA
2
Earth System Modeling and Prediction Center, China Meteorological Administration, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Academic Editor: Jason C. Knievel
Atmosphere 2022, 13(9), 1487; https://doi.org/10.3390/atmos13091487
Received: 25 June 2022 / Revised: 3 September 2022 / Accepted: 9 September 2022 / Published: 13 September 2022
(This article belongs to the Special Issue Feature Papers in Atmosphere Science)
A forecast from a numerical weather prediction (NWP) model can be decomposed into model climate and anomaly. Each part contributes to forecast error. To avoid errors from model climate, an anomaly, rather than a full field, should be used in a model. Model climate is replaced by the observed climate to reconstruct a new forecast for application. Using a Lorenz model, which has similar error characteristics to an NWP model, the following results were obtained. (a) The new anomaly-based method can significantly and steadily increase forecast accuracy throughout the entire forecast period (28 model days). On average, the total forecast error was reduced ~25%, and the correlation was increased by ~100–200%. The correlation improvement increases with the increasing of forecast length. (b) The method has different impacts on different types of error. Bias error was almost eliminated (over 90% in reduction). However, the change in flow-dependent error was mixed: a slight reduction (~5%) for model day 1–14 forecasts and increase (~15%) for model day 15–28 forecasts on average. The larger anomaly forecast error leads to the worsening of flow-dependent error. (c) Bias error stems mainly from model climate prediction, while flow-dependent error is largely associated with anomaly forecast. The method works more effectively for a forecast that has larger bias and smaller flow-dependent error. (d) A more accurate anomaly forecast needs to be constructed relative to model climate rather than observed climate by taking advantage of cancelling model systematic error (i.e., perfect-model assumption). In principle, this approach can be applicable to any model-based prediction. View Full-Text
Keywords: model climate; observed climate; anomaly forecast; bias; flow-dependent error; Lorenz model model climate; observed climate; anomaly forecast; bias; flow-dependent error; Lorenz model
Show Figures

Figure 1

MDPI and ACS Style

Du, J.; Deng, G. How Should a Numerical Weather Prediction Be Used: Full Field or Anomaly? A Conceptual Demonstration with a Lorenz Model. Atmosphere 2022, 13, 1487. https://doi.org/10.3390/atmos13091487

AMA Style

Du J, Deng G. How Should a Numerical Weather Prediction Be Used: Full Field or Anomaly? A Conceptual Demonstration with a Lorenz Model. Atmosphere. 2022; 13(9):1487. https://doi.org/10.3390/atmos13091487

Chicago/Turabian Style

Du, Jun, and Guo Deng. 2022. "How Should a Numerical Weather Prediction Be Used: Full Field or Anomaly? A Conceptual Demonstration with a Lorenz Model" Atmosphere 13, no. 9: 1487. https://doi.org/10.3390/atmos13091487

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop