There is an informative news article that illustrates why multi-decadal regional predictions of changes in climate statistics are of no value, The news article is on SciDev.net by Christine Ottery is titled
“The organization which is reported on is described as
The CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) is a 10-year research initiative launched by the Consultative Group on International Agricultural Research (CGIAR) and the Earth System Science Partnership (ESSP).
CCAFS seeks to overcome the threats to agriculture and food security in a changing climate, exploring new ways of helping vulnerable rural communities adjust to global changes in climate.”
Thus CCAFS already started with a perspective that accepts the model results as being able to accurately simulate changes in climate, before they performed their study. They are commended, however, for doing an evaluation of model skill and reporting on the issues that they have found. The news article is, apparently, based on a video presentation at How good are current climate models for predicting agricultural impacts in Africa and South Asia?.
The article reads [highlight added]
Global climate change models are of limited use to agricultural policymakers in some regions of the developing world, according to a report by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).
The report was launched at the Climate Models and Farm Crop Forecasting in South Asia and Africa meeting last month (21 February).
The researchers, from Oxford University, United Kingdom, and the University of Cape Town, South Africa, studied the ability of global climate models to predict regional climate events such as monsoon rains and temperatures — and found mixed results.
“The models have a reasonable capability in terms of reproducing [trends in the] East African climate,” said Richard Washington, professor of climate science at the University of Oxford.
But in West Africa, particularly in the Sahel region, the models predicted more monsoon rains, of different duration, to those that were actually observed.
Similar difficulties were encountered with India’s monsoons, the authors said. Global models were generally accurate in predicting large-scale horizontal movement of air (atmospheric flow), but not the specific timing or patterns of monsoon rainfall, according to Mark New, professor of climate science at the University of Cape Town.
The authors said global models often failed to take account of complex regional climatic factors — making them less useful for policymakers.
For example, Asia’s monsoons are affected by many region-specific factors, such as El Niño events, atmospheric pressure over the North Atlantic Ocean, and Asia’s so-called ‘brown cloud’ air pollution.
“If you want a climate model that predicts monsoon rainfall variability you need one that gets each of these factors right,” New told SciDev.Net.
The authors suggested greater use of ‘ensemble’ models which combine results from several models to generate averages; and also the use of global models in conjunction with regional ones, to enable regional information to be factored in alongside larger-scale processes.
Washington said it was also important to improve field data on which models are based, and remove any existing biases.
“Otherwise we are left to choose between models that are different [without knowing] which one is better,” he said.
Philip Thornton, a senior scientist at the International Livestock Research Institute in Kenya and a modelling tools leader at CCAFS told SciDev.Net: “The more we understand [uncertainty in models], the better we can deal with it”.
My Comment: It is refreshing to see that the impacts community is starting to assess the skill of the multi-decadal climate model predictions. This article highlights that climate prediction models predictions of multi-decadal changes in climate statistics are misleading policymakers in parts of the world. The authors of the report, however, also need to recognize that model predictions will be correct in some regions part of the time by chance, one does not know if they will be correct in the future. Their finding that trends in East Africa were correctly predicted, but that the trends were not accurate in West Africa and Asia should be a red flag that the agreement for the one region may be fortuitous. An evaluation of the predictive skill of the models, however, appears to be a goal of CCAFS, which should be emulated by other stakeholder communities.