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APCC guidance questions and our replies related to handling seasonal climate predictions with farmers

Last modified November 20, 2012 09:08

APCC guidance questions and our replies related to handling seasonal climate predictions with farmers.

[APEC Climate Symposium 2012 (October, St. Petersburg)

Climate and Agriculture Workshop: Harnessing and Using Climate Information for Decision Making, an In-Depth Look at the Agricultural Sector.]

 

C. (Kees) J. Stigter1 and Yunita T. Winarto2

 

1Visiting professor in developing countries, Agromet Vision, Bondowoso (Indonesia) and Bruchem (Netherlands) (cjstigter@usa.net)

2Academy Professorship Indonesia (KNAW-AIPI) & Professor, Department of Anthropology, Faculty of Social & Political Sciences, Universitas Indonesia, Depok, Indonesia (yunita.winarto@gmail.com)

 

APEC, the Asian-Pacific Economic Cooperation, held its 2012 APEC Climate Symposium, where we were invited to present the opening keynote lecture “COPING WITH CLIMATE CHANGE: AN ACTIVE AGROMETEOROLOGICAL LEARNING APPROACH TO RESPONSE FARMING” (Stigter and Winarto, 2012a). APCC, the APEC Climate Centre in Korea, that organized this meeting in St. Petersburg, had sent some guiding questions to the invited speakers. Although the replies were not explicitly used, but some were implicitly covered in the presented papers (APCC, 2012), we feel that our explicit answers to these questions would be of some value to people that want to handle seasonal climate predictions with farmers. APCC gave permission to use these questions and our answers on the INSAM website.

 

Introduction (from APCC)

Climate and agriculture are inextricably linked, as climate and weather are key factors in agricultural productivity. Advance climate forecasts allow agricultural producers to make better informed decisions, plan for contingencies, exploit favorable weather conditions, and minimize risk. Learning to adapt to present-day climate variability by integrating climate information into current decision-making processes lays a critical foundation for coping with long-term climate change. APCC aims to explore the following questions through its above Workshop as part of the APCC Climate Symposium 2012.

 

Our comments based on experience in Indonesia

This statement sounds a bit as if such advance climate predictions are easily made. But take the case of the isle of Java (Indonesia). The advantage here is that there is a strong climate signal but we have influences from (i) ENSO. There are no two El-Nino’s the same. Cold and warm ENSO phases have asymmetric amplitudes and durations. There are big changes of these amplitudes with phases of two to three decades. But this Pacific Decadal Oscillation (PDO) can also be found in that part of the Pacific that is not in the tropics. And then there are (ii) the “Walker Circulation”, changing with the ENSO but having great influence on the ENSO, we have (iii) the “Trade Winds” of which the forces change during the ENSO, and we also have (iv) the “Madden-Julian Oscillation”, that brings large differences in intra-seasonal behavior. Add to this that there must be still some unknown teleconnections and the increasing indications that ENSO is changing with global warming, and it is clear that seasonal climate predictions need a long way to go to become better, that is “made with more skill”, than they are at present.

APCC guidance questions and our replies

 

  1. What is the role of forecast information in decision making? What other factors influence agricultural planning and decision making?

 

The answer to the first question here is “knowledge improvement of farmers”. This new knowledge will support their planning, management and decision making in coping with the consequences of climate change.

 

Other factors that influence this are (i) short term disasters; (ii) (semi-) permanent microclimate management and manipulation (such as in agroforestry and other intercropping); (iii) early warnings (e.g. for pests and diseases, see experience in India). And of course the availability (and its flexibility) of inputs is another important factor (that again in India is well treated at the district level).

 

 

  1. What are the opportunities and constraints to adoption by end-users?

 

Farmers must get farming systems dependent active learning opportunities. The constraints are that climate information, including raw ensemble climate predictions, must be adapted to their understanding (by making scenarios from already simplified predictions) and the use of all climate information must be followed up by active research on its use, misuse and/or lack of use.

 

The absence of any continuing facilitation by state agencies and knowledge partners will endanger adaptation strategies. If not all farmers in an area have similar access to climate information and agrometeorological learning, this could constrain those who have the understanding and capability to adopt the information and decide on adaptation strategies.

 

  1. What policies and/or institutions are needed for climate prediction to generate economic and social benefits?

 

For that we must first try out climate scenarios for the growing seasons (derived from the simplified raw ensemble climate predictions) in large scale experiments with farmers for different farming systems. Extension intermediaries should be trained by being involved in those experiments. Once we know the best way to assist farmers with such scenarios to cope with the consequences of climate change, then well trained extension intermediaries can take over to generate economic and social benefits with the farmers.

 

 

  1. How is information transferred from producers to end users? What channels and/or institutions are involved along the way?

 

See our reply to point 3. In the end, Universities, Research Institutes and/or National Meteorological Services (and/or other Environmental Services Organizations) should become responsible for the Training of (the Extension) Trainers. The latter are also called “Product Intermediaries”, because they must be trained in showing the use of the weather and climate related products of these training organizations to those extension intermediaries that work with the farmers. See for details Stigter and Winarto (2012b).

 

 

  1. How can we ensure that climate information is not only scientifically sound but relevant to user needs? How can information be improved (in either content or form) to help farmers maximize benefits?

 

The scientific soundness is out of our hands (see our second remark added to the introduction) but a general issue is that the raw ensemble climate predictions should be simplified and then made into scenarios for the growing seasons.

The relevance for farmers as users, including knowledge improvement, is in the permanent evaluation by farmers themselves, farmer-to-farmer extension, and the feedback from farmers to extension intermediaries, who discuss this feedback with their trainers (product intermediaries). In this way the prediction products will be improved in form and contents.

 

 

  1. How to distribute climate forecasts on time scales that are relevant to user’s procedural needs (e.g. purchase of seeds, determination of crops, planting schedules)?

 

It is our experience that simplified monthly climate predictions that are updated each month but have an outlook of three months (also updated monthly) are sufficient to make a scenario for the growing seasons (rainy seasons) for the farmers each month. Such scenarios must have the consequences of the climate information in terms of consequences for the growing season. This will make it possible for farmers to improve their decisions on purchase of seeds, determination of crops, planting schedules etc.

 

 

  1. How can exogenous information (climate predictions) be reconciled with endogenous information (traditional knowledge)? In what ways can we encourage local appropriation of climate information and its inclusion in decision-making processes?

 

The answer to the first issue is that both have to be taken serious and wherever possible have to be (scientifically) compared. We encourage Javanese farmers to use their “Pranata Mangsa” and compare the outcome with our advices based on scientific climate predictions. Self-Learning on limitations of traditional as well as scientific knowledge is the best way.

 

We have good experience in doing field experiments with farmers where the scientific approach is used as control while the traditional approach is carried out without modifications. These experiments may be carried out independently by farmers (both scientific approach and traditional approach) and scientists (also both). [You may find examples in Stigter, 2010.] In the end, farmers may make use of some of still valuable natural indicators at the beginning of and throughout the rainy seasons while also using simple scientific climate scenarios.

 

  1. How can information providers best communicate the probabilistic nature and limitations of seasonal climate forecasts?

 

Again it is our experience that using words instead of percentages works best. So three categories (above normal, normal, below normal), as we use on Java, or five categories (way above normal, above normal, normal, below normal and way below normal) will both work if the predictions support this. The limitations become clear by doing this work with farmers monthly for a few years and discuss predictions/scenarios and realities afterwards as to their consequences for decisions taken.

 

 

  1. How can climate forecast information be translated into terms such as agricultural impacts, management implications, and production outcomes (yields)?

 

As already indicated above, simple predictions, as derived from the raw ensemble predictions received from NOAA or APCC or others, should each month be made into a scenario for one to three months that can be applied to the growing season(s). If the raw predictions were given with an advice on skill of the prediction, this must also be translated into caution for the farmers.

 

It is our experience that farmers who measure daily rainfall in their own plots, and also make agro-ecosystem observations routinely, do understand agricultural impacts, management implications, and production outcomes (yields) better. Wherever possible, such implications should be discussed between farmers on a monthly basis, with either extension or scientists (and preferably both) present.

 

Both our experience and pitfalls exemplified in the extension literature warn against preparing on-farm decisions for the farmers. Because each region is so diverse and each field has so many unique ecosystem details, it should be only for the farmers to decide on their strategies, using local and scientific information, not for well-meaning top-down arguing outsiders.

 

 

  1. How can we improve the linkages between the meteorological and agricultural communities at the national, regional, and international level?

 

We have started with the establishment of a National Network for a Rural Response to Climate Change (NNRRCC) in Indonesia, with the National Ministry of Agriculture (representing extension and farmer capacity building), the National Weather and Climate Services, several Universities and Institutes and Farmer Facilitators (designated by farmers). This is still in its early development but is promising if we all learn to listen to each other.

 

 

  1. What new research questions can the academic community explore to address climate impacts in the agricultural sector?

 

It is clear from our second remark on the introduction that better raw ensemble climate predictions, with higher than present skills throughout the year, will be extremely welcome for many years to come. For the farmers, research on better preparedness as to understanding climate information (including seasonal scenarios), coping with disasters, using early warnings and looking for opportunities that weather and climate have to offer, is the approach that has to be taken. Applying agroforestry, multiple cropping and other microclimate management and manipulation will be of much help towards such preparedness.

 

 

References

 

APCC, 2012. Asian Pacific Climate Symposium 2012 (October, St. Petersburg) Climate and Agriculture Workshop: Harnessing and Using Climate Information for Decision Making, an In-Depth Look at the Agricultural Sector. http://www.apcc21.org/eng/acts/pastsym/japcc0202_lst.jsp

 

Stigter, Kees (Ed.), 2010. Applied Agrometeorology. Springer (Berlin etc.), xxxviii + 1101 pp.

 

Stigter, C. (Kees) J. and Winarto, Y.T., 2012a. Coping with Climate Change: An Active Agrometeorological Learning Approach to Response Farming. Opening Keynote paper in: Asian Pacific Climate Symposium 2012 (October, St. Petersburg) Climate and Agriculture Workshop: Harnessing and Using Climate Information for Decision Making, an In-Depth Look at the Agricultural Sector. http://www.apcc21.org/eng/acts/pastsym/japcc0202_viw.jsp

 

Stigter, Kees and Winarto, Yunita T., 2012b. Extension Agrometeorology as a Contribution to Sustainable Agriculture. New Clues in Sciences 2(3): 59-63. [http://www.woaj.org/NCS (October Issue)]

 

 

Note on Participants:

 

The workshop did engage participants from government agencies, particularly National Hydrological and Meteorological Services and National Agricultural Research and Extension Services, NGOs, scientific research institutes, and the private sector in the APEC economies (Australia, Canada, Chile, China, Hong Kong China, Indonesia, Japan, Republic of Korea, Malaysia, Mexico, New Zealand, Papua New Guinea, Peru, Philippines, Russia, Singapore, Chinese Taipei, Thailand, United States and Viet Nam)

 

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