Stochastic atmospheric perturbations in the EC-Earth3 global coupled model: impact of SPPT on seasonal forecast quality

2015 ◽  
Vol 45 (11-12) ◽  
pp. 3419-3439 ◽  
Author(s):  
Lauriane Batté ◽  
Francisco J. Doblas-Reyes
Keyword(s):  
Coupled Model ◽  
Seasonal Forecast ◽  
Atmospheric Perturbations ◽  
Forecast Quality ◽  
Global Coupled Model

scholarly journals The Met Office Global Coupled model 2.0 (GC2) configuration

2015 ◽  
Vol 8 (1) ◽  
pp. 521-565 ◽  
Author(s):  
K. D. Williams ◽  
C. M. Harris ◽  
A. Bodas-Salcedo ◽  
J. Camp ◽  
R. E. Comer ◽  
...  
Keyword(s):  
Coupled Model ◽  
Systematic Errors ◽  
Diagnostic Techniques ◽  
Seasonal Forecast ◽  
Unified Model ◽  
Climate Projection ◽  
Forecast System ◽  
Projection System ◽  
Model Components ◽  
Global Coupled Model

Abstract. The latest coupled configuration of the Met Office Unified Model (Global Coupled configuration 2, GC2) is presented. This paper documents the model components which make up the configuration (although the scientific description of these components is detailed elsewhere) and provides a description of the coupling between the components. The performance of GC2 in terms of its systematic errors is assessed using a variety of diagnostic techniques. The configuration is intended to be used by the Met Office and collaborating institutes across a range of timescales, with the seasonal forecast system (GloSea5) and climate projection system (HadGEM) being the initial users. In this paper GC2 is compared against the model currently used operationally in those two systems.

scholarly journals Dynamics of the Indian monsoon and ENSO relationships in the SINTEX global coupled model

2004 ◽  
Vol 24 (2-3) ◽  
pp. 145-168 ◽  
Author(s):  
P. Terray ◽  
E. Guilyardi ◽  
A. S. Fischer ◽  
P. Delecluse
Keyword(s):  
Indian Monsoon ◽  
Coupled Model ◽  
Global Coupled Model

scholarly journals IPCC global coupled model simulations of the South America monsoon system

2008 ◽  
Vol 33 (7-8) ◽  
pp. 893-916 ◽  
Author(s):  
Rodrigo J. Bombardi ◽  
Leila M. V. Carvalho
Keyword(s):  
South America ◽  
Coupled Model ◽  
The South ◽  
Model Simulations ◽  
Monsoon System ◽  
Global Coupled Model

A forecast quality assessment of an end-to-end probabilistic multi-model seasonal forecast system using a malaria model

2005 ◽  
Vol 57 (3) ◽  
pp. 464-475 ◽  
Author(s):  
ANDREW P. MORSE ◽  
FRANCISCO J. DOBLAS-REYES ◽  
MOSHE B. HOSHEN ◽  
RENATE HAGEDORN ◽  
TIM N. PALMER
Keyword(s):  
Quality Assessment ◽  
Seasonal Forecast ◽  
Forecast System ◽  
End To End ◽  
Malaria Model ◽  
Forecast Quality

scholarly journals The Canadian Seasonal to Interannual Prediction System Version 2 (CanSIPSv2)

2020 ◽  
Vol 35 (4) ◽  
pp. 1317-1343 ◽  
Author(s):  
Hai Lin ◽  
William J. Merryfield ◽  
Ryan Muncaster ◽  
Gregory C. Smith ◽  
Marko Markovic ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Southern Oscillation ◽  
Weather Prediction ◽  
Coupled Model ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Boreal Winter ◽  
Prediction System ◽  
Sea Ice Concentration

AbstractThe second version of the Canadian Seasonal to Interannual Prediction System (CanSIPSv2) was implemented operationally at Environment and Climate Change Canada (ECCC) in July 2019. Like its predecessors, CanSIPSv2 applies a multimodel ensemble approach with two coupled atmosphere–ocean models, CanCM4i and GEM-NEMO. While CanCM4i is a climate model, which is upgraded from CanCM4 of the previous CanSIPSv1 with improved sea ice initialization, GEM-NEMO is a newly developed numerical weather prediction (NWP)-based global atmosphere–ocean coupled model. In this paper, CanSIPSv2 is introduced, and its performance is assessed based on the reforecast of 30 years from 1981 to 2010, with 10 ensemble members of 12-month integrations for each model. Ensemble seasonal forecast skill of 2-m air temperature, 500-hPa geopotential height, precipitation rate, sea surface temperature, and sea ice concentration is assessed. Verification is also performed for the Niño-3.4, the Pacific–North American pattern (PNA), the North Atlantic Oscillation (NAO), and the Madden–Julian oscillation (MJO) indices. It is found that CanSIPSv2 outperforms the previous CanSIPSv1 system in many aspects. Atmospheric teleconnections associated with the El Niño–Southern Oscillation (ENSO) are reasonably well captured by the two CanSIPSv2 models, and a large part of the seasonal forecast skill in boreal winter can be attributed to the ENSO impact. The two models are also able to simulate the Northern Hemisphere teleconnection associated with the tropical MJO, which likely provides another source of skill on the subseasonal to seasonal time scale.

scholarly journals A forecast quality assessment of an end-to-end probabilistic multi-model seasonal forecast system using a malaria model

2005 ◽  
Vol 57 (3) ◽  
pp. 464-475 ◽  
Author(s):  
Andrew P. Morse ◽  
Francisco J. Doblas-Reyes ◽  
Moshe B. Hoshen ◽  
Renate Hagedorn ◽  
Tim N. Palmer
Keyword(s):  
Quality Assessment ◽  
Seasonal Forecast ◽  
Forecast System ◽  
End To End ◽  
Malaria Model ◽  
Forecast Quality

Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

2013 ◽  
Vol 42 (1-2) ◽  
pp. 271-290 ◽  
Author(s):  
Chloé Prodhomme ◽  
Pascal Terray ◽  
Sébastien Masson ◽  
Takeshi Izumo ◽  
Tomoki Tozuka ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Indian Monsoon ◽  
Coupled Model ◽  
Global Coupled Model

scholarly journals Monsoon intra-seasonal variability in a high-resolution version of Met Office Global Coupled model

2017 ◽  
Vol 69 (1) ◽  
pp. 1354661 ◽  
Author(s):  
Yongjie Fang ◽  
Peili Wu ◽  
M.S. Mizielinski ◽  
M.J. Roberts ◽  
Bo Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Seasonal Variability ◽  
Coupled Model ◽  
Global Coupled Model

On the reliability of decadal climate prediction

2020 ◽  
Author(s):  
Deborah Verfaillie ◽  
Francisco J. Doblas-Reyes ◽  
Markus G. Donat ◽  
Nuria Pérez-Zanón ◽  
Balakrishnan Solaraju-Murali ◽  
...  
Keyword(s):  
Coupled Model ◽  
Skill Assessment ◽  
Added Value ◽  
Climate Projections ◽  
Negative Consequences ◽  
Climate Information ◽  
The North ◽  
Decadal Climate ◽  
The Impact ◽  
Forecast Quality

<p>Decadal climate predictions and forced climate projections both provide potentially useful information to users for the next ten years. They only differ in the former being initialised with observations, while the latter is not. Bringing together initialised decadal climate predictions and non-initialised climate projections in order to provide seamless climate information for users over the next decades is a new challenging area of research. This can be achieved by comparing the forecast quality of global initialised and non-initialised simulations in their common prediction time horizons (up to 10 years ahead), and quantify in how far initialisation improves the forecast quality. Forecast quality has been usually explored through skill assessment. However, the impact of initialisation on the reliability, which quantifies the agreement between the predicted probabilities and observed relative frequencies of a given event, of decadal predictions has not yet been investigated sufficiently. Hence, users of probabilistic predictions are particularly sensitive to the potential lack of reliability which would imply that the probabilities are not trustworthy and this can have negative consequences for decision-making. In this communication, initialised decadal hindcasts (or retrospective forecasts) from 12 forecasting systems of the Coupled Model Intercomparison Project Phase 5 are compared to the corresponding non-initialised historical simulations in terms of reliability over their common period 1961-2005. We show that reliability varies greatly depending on the region or model ensemble analysed and on the correction applied. In particular, the North Atlantic and Europe stand out as regions where there is some added-value of initialised decadal hindcasts over non-initialised historical simulations in terms of reliability, mainly because of smaller biases and/or a better representation of the trend. Furthermore, we show that post-processed data display more reliable results, indicating that bias correction and calibration are fundamental to obtain reliable climate information.</p>

The value of skill in seasonal climate forecasting to wheat crop management in a region with high climatic variability

1996 ◽  
Vol 47 (5) ◽  
pp. 717 ◽  
Author(s):  
GL Hammer ◽  
DP Holzworth ◽  
R Stone
Keyword(s):  
Crop Management ◽  
Seasonal Forecast ◽  
Seasonal Forecasting ◽  
Wheat Crop ◽  
Phase System ◽  
Management Decisions ◽  
Seasonal Climate ◽  
Climate Forecasting ◽  
Daily Weather Data ◽  
Forecast Quality

In Australia, and particularly in the northern part of the grain belt, wheat is grown in an extremely variable climate. The wheat crop manager in this region is faced with complex decisions on choice of planting time, varietal development pattern, and fertiliser strategy. A skilful seasonal forecast would provide an opportunity for the manager to tailor crop management decisions more appropriately to the season. Recent developments in climate research have led to the development of a number of seasonal climate forecasting systems. The objectives of this study were to determine the value of the capability in seasonal forecasting to wheat crop management, to compare the value of the existing forecast methodologies, and to consider the potential value of improved forecast quality. We examined decisions on nitrogen (N) fertiliser and cultivar maturity using simulation analyses of specific production scenarios at a representative location (Goondiwindi) using long-term daily weather data (1894-1989). The average profit and risk of making a loss were calculated for the possible range of fixed (i.e. the same every year) and tactical (i.e. varying depending on seasonal forecast) strategies. Significant increase in profit (up to 20%) and/or reduction in risk (up to 35%) were associated with tactical adjustment of crop management of N fertiliser or cultivar maturity. The forecasting system giving greatest value was the Southern Oscillation Index (SOI) phase system of Stone and Auliciems (1992), which classifies seasons into 5 phases depending on the value and rate of change in the SOI. The significant skill in this system for forecasting both seasonal rainfall and frost timing generated the value found in tactical management of N fertiliser and cultivar maturity. Possible impediments to adoption of tactical management, associated with uncertainties in forecasting individual years, are discussed. The scope for improving forecast quality and the means to achieve it are considered by comparing the value of tactical management based on SO1 phases with the outcome given perfect prior knowledge of the season. While the analyses presented considered only one decision at a time, used specific scenarios, and made a number of simplifying assumptions, they have demonstrated that the current skill in seasonal forecasting is sufficient to justify use in tactical management of crops. More comprehensive studies to examine sensitivities to location, antecedent conditions, and price structure, and to assumptions made in this analysis, are now warranted. We have examined decisions related only to management of wheat. It would be appropriate to pursue similar analyses in relation to management decisions for other crops, cropping sequences, and the whole farm enterprise mix.

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