ACCURACY OF MONTHLY AND SEASONAL FORECASTS GENERATED FOR THE TERRITORY OF LITHUANIA USING NOAA’S CLIMATE FORECAST SYSTEM VERSION 2

Arūnas Bukantis,Gytis Valaika

doi:10.3846/jeelm.2021.15580

Abstract

The objective of this paper is to assess the accuracy of air temperature and precipitation monthly and seasonal forecasts generated for the territory of Lithuania using the NOAA’s Climate Forecast System, version 2 (CFSv2) and to determine the atmospheric circulation conditions present at the time of initialization of the respective forecasts. The air temperature and precipitation data are obtained from three-month mean and monthly mean spatial anomalies during the period between 2012 and 2019. The accuracy of forecasts was performed in accordance with three criteria: range, state and the absolute error of the respective predicted anomaly. The study has shown that forecasts initialized 0–20 days in advance of the target month or season tend to be the most skilful. The accuracy of CFSv2 forecasts may be significantly impacted by the initial atmospheric circulation conditions present during the generation thereof. The study determined which phases of Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) and which circulation types according to the Hess-Brezowsky classification are favourable/unfavourable for the monthly and seasonal forecasting of air temperature and precipitation.

Highlights

The need for skilful monthly and seasonal forecasts of air temperature and precipitation anomalies have grown around the world
The present section analyses the accuracy of forecasts of monthly-mean air temperature and monthly precipitation amount spatial anomalies generated using CFSv2 for the territory of Lithuania between 2012 and 2019
The smallest absolute error, i.e., the difference between the actual and the forecasted air temperature values of temperature forecasts generated using CFSv2 was seen in forecasts initialized right before the forecasted month, in which case the mean error was

Summary

Introduction

The need for skilful monthly and seasonal forecasts of air temperature and precipitation anomalies have grown around the world. Weather and climate forecast centers such as the National Centers for Environmental Prediction (NCEP), the European Centre for MediumRange Weather Forecasts (ECMWF), Met Office’s seasonal forecast system GloSea and other make dynamical. Accuracy of monthly and seasonal forecasts generated for the territory of Lithuania using

Objectives

Methods

Results

Conclusion