Application of long-range weather forecasts to agricultural decision problems in Europe

被引:40
作者
Calanca, P. [1 ]
Bolius, D. [1 ]
Weigel, A. P. [2 ]
Liniger, M. A. [2 ]
机构
[1] Agroscope Reckenholz Tanikon, Res Stn ART, Air Pollut & Climate Grp, CH-8032 Zurich, Switzerland
[2] MeteoSwiss, Fed Off Meteorol & Climatol, CH-8044 Zurich, Switzerland
基金
瑞士国家科学基金会;
关键词
ENSEMBLE-PREDICTION SYSTEM; SEASONAL CLIMATE FORECASTS; CROP SIMULATION; WHEAT GROWTH; DAILY PRECIPITATION; YIELD PREDICTION; WATER-BALANCE; SKILL SCORES; MODEL; TEMPERATURE;
D O I
10.1017/S0021859610000729
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Agriculture can benefit substantially from long-range weather forecasts, for the month or the season, which can help to optimize farming operations and deal more effectively with the adverse impacts of climate variability, including extreme weather events. In the context of climate change, long-range weather forecasts also represent key elements for the development of adaptation strategies. In spite of an undeniable potential, long-range forecasts issued for instance by the European Centre for Medium-Range Weather Forecasts (ECMWF) have yet to find widespread application in European agriculture. To address partially the question of why this is the case, the performance of the ECMWF monthly ensemble forecasting system was examined. It was noted that predictability is currently limited to about 3 weeks for temperature and 2 weeks for precipitation and solar radiation. This may appear deceptive at first sight, but it was noticed that precipitation forecasts over a month are, overall, at least as valuable as information obtained from observed climatology. Encouraged by this finding, the possibility of using monthly forecasts to predict soil water availability was tested. In an operational context, this could serve as a basis for scheduling irrigation. Positive skills were found for lead times of up to 1 month. It was concluded that more systematic investigations of the possibilities offered by long-range forecasts should be undertaken in the future. However, this will require additional efforts to increase the quality of the forecasts, design appropriate application tools and promote the dissemination of the outcome within the agriculture community.
引用
收藏
页码:15 / 22
页数:8
相关论文
共 56 条
[1]   The carbon budget of newly established temperate grassland depends on management intensity [J].
Ammann, C. ;
Flechard, C. R. ;
Leifeld, J. ;
Neftel, A. ;
Fuhrer, J. .
AGRICULTURE ECOSYSTEMS & ENVIRONMENT, 2007, 121 (1-2) :5-20
[2]   The 2003 heat wave in Europe: A shape of things to come? An analysis based on Swiss climatological data and model simulations [J].
Beniston, M .
GEOPHYSICAL RESEARCH LETTERS, 2004, 31 (02) :L022021-4
[3]  
Buizza R, 1999, WEATHER FORECAST, V14, P168, DOI 10.1175/1520-0434(1999)014<0168:PPOPUT>2.0.CO
[4]  
2
[5]   Statistical downscaling model based on canonical correlation analysis for winter extreme precipitation events in the Emilia-Romagna region [J].
Busuioc, A. ;
Tomozeiu, R. ;
Cacciamani, C. .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2008, 28 (04) :449-464
[6]   Climate change and drought occurrence in the Alpine region: How severe are becoming the extremes? [J].
Calanca, Pierluigi .
GLOBAL AND PLANETARY CHANGE, 2007, 57 (1-2) :151-160
[7]   Seasonal weather forecasts for crop yield modelling in Europe [J].
Cantelaube, P ;
Terres, JM .
TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY, 2005, 57 (03) :476-487
[8]   Developments in dynamical seasonal forecasting relevant to agricultural management [J].
Doblas-Reyes, F. J. ;
Hagedorn, R. ;
Palmer, T. N. .
CLIMATE RESEARCH, 2006, 33 (01) :19-26
[9]   A method for statistical downscaling of seasonal ensemble predictions [J].
Feddersen, H ;
Andersen, U .
TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY, 2005, 57 (03) :398-408
[10]  
Garbrecht J., 2005, EOS T AM GEOPHYS UN, V86, P227, DOI DOI 10.1029/2005E324005