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1.
This study compares responses to seasonal climate forecasts conducted by farmers of three agro-ecological zones of Burkina Faso, including some who had attended local level workshops and others who had not attended the workshops. While local inequalities and social tensions contributed to excluding some groups, about two-thirds of non-participants interviewed received the forecast from the participants or through various means deployed by the project. Interviews revealed that almost all those who received the forecasts by some mechanism (workshop or other) shared them with others. The data show that participants were more likely to understand the probabilistic aspect of the forecasts and their limitations, to use the information in making management decisions and by a wider range of responses. These differences are shown to be statistically significant. Farmers evaluated the forecasts as accurate and useful in terms of both material and non-material considerations. These findings support the hypothesis that participatory workshops can play a positive role in the provision of effective climate services to African rural producers. However, this role must be assessed in the context of local dynamics of power, which shape information flows and response options. Participation must also be understood beyond single events (such as workshops) and be grounded in sustained interaction and commitments among stakeholders. The conclusion of this study point to lessons learned and critical insights on the role of participation in climate-based decision support systems for rural African communities.  相似文献   

2.
The importance of anchoring seasonal climate forecasts to user needs is examined in this paper. Although it is generally accepted that seasonal climate forecasts have potential value, many constraints preclude the optimal use of these forecasts, including the way forecasts are produced, interpreted and applied in a variety of decision-making processes. In South Africa, a variety of agricultural users exists, ranging from the small-scale farmer to larger commercial farming entities. Useful seasonal are those produced and disseminated with the end user in mind. A retroactive test period during the 1990s, evaluates the perceived impact of incorporating seasonal rainfall forecasts into decisions made by commercial crop farmers in the central parts of South Africa. Although a small sample of commercial farmers was interviewed, the results show some benefits to commercial agriculture if seasonal climate forecast information is continuously and effectively applied over the long-term.  相似文献   

3.
Ecosystem Modeling Adds Value to a South African Climate Forecast   总被引：2，自引：0，他引：2  
Livestock production in South Africa is limited by frequent droughts. The South African Weather Service produces climate forecasts estimating the probability of low rainfall three and six months into the future. We used the ecosystem model SAVANNA applied to five commercial farms in the Vryburg region of the North-West Province, and five communal areas within the Province, to assess the utility of a climate forecast in refining drought coping strategies. Rainfall data from 1970 to 1994 were modified to represent a drought (225 mm of rainfall) in 1977/1978, and used in simulations. In a simulation on an example commercial farm we assumed a forecast was available in 1977 portending an upcoming drought, and that the owner sold 490 cattle and 70 sheep prior to the drought. Over the simulation period, the owner sold 31% more cattle when the forecast was used,versus when the forecast was ignored. Populations of livestock on both commercial and communal farms recovered more quickly following the drought when owners sold animals in response to the forecast. The economic benefit from sales is being explored using optimization techniques. Results and responses from South African livestock producers suggest that a real-time farm model linked with climate forecasting would be a valuable management tool.  相似文献   

4.
Water resources, and in particular run-off, are significantly affected by climate variability. At present, there are few examples of how the water management sector integrates information about changing intra-annual climate conditions in a systematic manner in developing countries. This paper, using the case study of Cape Town in the Western Cape, South Africa, identifies processes and products to facilitate increased uptake of seasonal climate forecasts among water resource managers. Results suggest that existing seasonal forecasts do not focus enough on specific users’ needs. In order to increase uptake, forecasts need to include information on the likely impact of precipitation variability on runoff and water availability. More opportunities are also needed for those with climate knowledge to interact with water resource managers, particularly in the developing country context where municipal managers’ capacity is strained. Although there are challenges that need to be overcome in using probabilistic climate information, seasonal forecast information tailored to the needs of water resource planners has the potential to support annual planning and is therefore a means of adapting to climate change.  相似文献   

5.
Multiple cropping systems provide more harvest security for farmers, allow for crop intensification and furthermore influence ground cover, soil erosion, albedo, soil chemical properties, pest infestation and the carbon sequestration potential. We identify the traditional sequential cropping systems in ten sub-Saharan African countries from a survey dataset of more than 8600 households. We find that at least one sequential cropping system is traditionally used in 35% of all administrative units in the dataset, mainly including maize or groundnuts. We compare six different management scenarios and test their susceptibility as adaptation measure to climate change using the dynamic global vegetation model for managed land LPJmL. Aggregated mean crop yields in sub-Saharan Africa decrease by 6–24% due to climate change depending on the climate scenario and the management strategy. As an exception, some traditional sequential cropping systems in Kenya and South Africa gain by at least 25%. The crop yield decrease is typically weakest in sequential cropping systems and if farmers adapt the sowing date to changing climatic conditions. Crop calorific yields in single cropping systems only reach 40–55% of crop calorific yields obtained in sequential cropping systems at the end of the 21st century. The farmers’ choice of adequate crops, cropping systems and sowing dates can be an important adaptation strategy to climate change and these management options should be considered in climate change impact studies on agriculture.  相似文献   

6.
Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall   总被引：1，自引：0，他引：1  
The Yangtze River has been subject to heavy flooding throughout history,and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods.Dams along the river help to manage flood waters,and are important sources of electricity for the region.Being able to forecast high-impact events at long lead times therefore has enormous potential benefit.Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services.The teleconnection from El Ni ?no to Yangtze River basin rainfall meant that the strong El Ni ?no in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system.This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin,building on previous work demonstrating the retrospective skill of such a forecast.A simple forecasting methodology is presented,in which the forecast probabilities are derived from the historical relationship between hindcast and observations.Its performance for2016 is discussed.The heavy rainfall in the May–June–July period was correctly forecast well in advance.August saw anomalously low rainfall,and the forecasts for the June–July–August period correctly showed closer to average levels.The forecasts contributed to the confidence of decision-makers across the Yangtze River basin.Trials of climate services such as this help to promote appropriate use of seasonal forecasts,and highlight areas for future improvements.  相似文献   

7.
Public weather services are trending toward providing users with probabilistic weather forecasts, in place of traditional deterministic forecasts. Probabilistic forecasting techniques are continually being improved to optimize available forecasting information. The Bayesian Processor of Forecast (BPF), a new statistical method for probabilistic forecast, can transform a deterministic forecast into a probabilistic forecast according to the historical statistical relationship between observations and forecasts generated by that forecasting system. This technique accounts for the typical forecasting performance of a deterministic forecasting system in quantifying the forecast uncertainty. The meta-Gaussian likelihood model is suitable for a variety of stochastic dependence structures with monotone likelihood ratios. The meta-Gaussian BPF adopting this kind of likelihood model can therefore be applied across many fields, including meteorology and hydrology. The Bayes theorem with two continuous random variables and the normal-linear BPF are briefly introduced. The meta-Gaussian BPF for a continuous predictand using a single predictor is then presented and discussed. The performance of the meta-Gaussian BPF is tested in a preliminary experiment. Control forecasts of daily surface temperature at 0000 UTC at Changsha and Wuhan stations are used as the deterministic forecast data. These control forecasts are taken from ensemble predictions with a 96-h lead time generated by the National Meteorological Center of the China Meteorological Administration, the European Centre for Medium-Range Weather Forecasts, and the US National Centers for Environmental Prediction during January 2008. The results of the experiment show that the meta-Gaussian BPF can transform a deterministic control forecast of surface temperature from any one of the three ensemble predictions into a useful probabilistic forecast of surface temperature. These probabilistic forecasts quantify the uncertainty of the control forecast; accordingly, the performance of the probabilistic forecasts differs based on the source of the underlying deterministic control forecasts.  相似文献   

8.
Organic farmers are a prime clientele for climate services by virtue of their social profile and vulnerability of produce to climate extremes. The study draws on an online survey and in-depth interviews with organic farmers in Georgia (United States). It shows that organic farmers access and act on climate information in ways that reflect their emphasis on diversified and flexible systems. They favor a pluralistic knowledge base that integrates scientific expertise with place-based experience and intuitive understandings. Their management style combines information at multiple temporal scales and draws on a range of technical and social resources. Translating climate forecasts into usable science for organic farming requires attention to the identities, commitments, and relationships that define the organic farming community.  相似文献   

9.
Adaptation to climate change in Uganda: Evidence from micro level data   总被引：1，自引：0，他引：1  
This study employed data from the 2005/06 Uganda national household survey to identify adaptation strategies and factors governing their choice in Uganda's agricultural production. Factors that mediate or hinder adaptation across different shocks and strategies include age of the household head, access to credit and extension facilities and security of land tenure. There are also differences in choice of adaptation strategies by agro-climatic zone. The appropriate policy level responses should complement the autonomous adaptation strategies by facilitating technology adoption and availing information to farmers not only with regard to climate related forecasts but available weather and pest resistant varieties.  相似文献   

10.
According to the Anderson-Darling principle, a method for forecast of extremely heavy rainfall (abbreviated as extreme rainfall/precipitation) was developed based on the ensemble forecast data of the T213 global ensemble prediction system (EPS) of the China Meteorological Administration (CMA). Using the T213 forecast precipitation data during 2007-2010 and the observed rainfall data in June-August of 2001-2010, characteristics of the cumulative distribution functions (CDFs) of the observed and the T213 EPS forecast precipitation were analyzed. Accordingly, in the light of the continuous differences of the CDFs between model climate and EPS forecasts, a mathematical model of Extreme Precipitation Forecast Index (EPFI) was established and applied to forecast experiments of several extreme rainfall events in China during 17-31 July 2011. The results show that the EPFI has taken advantage of the tail information of the model climatic CDF and provided agreeable forecasts of extreme rainfalls. The EPFI based on the T213 EPS is useful for issuing early warnings of extreme rainfalls 3-7 days in advance. With extension of the forecast lead time, the EPFI becomes less skillful. The results also demonstrate that the rationality of the model climate CDF was of vital importance to the skill of EPFI.  相似文献   

11.
Climate and crop yield variability associated with El Niño—Southern Oscillation (ENSO) are now predictable within limits. This predictability suggests a potential to tailor agricultural management to mitigate impacts of adverse conditions and to take advantage of favorable conditions. However, improved climate predictions may benefit society only with parallel advances in our ability to use this knowledge. We show that the value that will accrue to any given actor from an ENSO phase forecast should be viewed not as a known number but instead as a random draw from a distribution, even when the forecast is always correct. Forecast value depends on the highly variable contexts in which forecasts are used. Randomness in forecast value has significant implications for choices made by forecasters, forecast users and policy makers. To show randomness, we estimate potential economic values of ENSO forecasts for agricultural producers based on two realistic assumptions: the crop prices farmers receive are uncertain; and within an ENSO phase, the actual climate is variable in ways that affect profits. The use of synthetic weather and crop price series, with crop simulation models, helps show the range and likelihood of climate forecast value.  相似文献   

12.
Evidence of increasing nitrogen levels in the Suwannee River Basin in North Florida demands a collaborative effort to find creative ways to reduce N pollution. This study explores the perspectives, perceptions, and attitudes of dairy farmers regarding adoption of climate forecasts as a potential way to mitigate the problem. These farmers are heavily scrutinized because of their nitrogen emissions. By contrasting scientists' pre-conceived attitudes about the usefulness of ENSO-based forecasts with dairy farmers' perceptions, gathered in a participatory and consensual manner, valuable lessons were learned. A deeper understanding of the day to day realities of dairy farming systems help researchers pinpoint management adaptations that are not only useful, but feasible, in light of improved seasonal climate forecasts. Furthermore, dairy farmers' perceptions regarding the use of seasonal climate information to mitigate the nitrate problem are critical for designing future dairy systems.  相似文献   

13.
Summary Objective combination schemes of predictions from different models have been applied to seasonal climate forecasts. These schemes are successful in producing a deterministic forecast superior to individual member models and better than the multi-model ensemble mean forecast. Recently, a variant of the conventional superensemble formulation was created to improve skills for seasonal climate forecasts, the Florida State University (FSU) Synthetic Superensemble. The idea of the synthetic algorithm is to generate a new data set from the predicted multimodel datasets for multiple linear regression. The synthetic data is created from the original dataset by finding a consistent spatial pattern between the observed analysis and the forecast data set. This procedure is a multiple linear regression problem in EOF space. The main contribution this paper is to discuss the feasibility of seasonal prediction based on the synthetic superensemble approach and to demonstrate that the use of this method in coupled models dataset can reduce the errors of seasonal climate forecasts over South America. In this study, a suite of FSU coupled atmospheric oceanic models was used. In evaluation the results from the FSU synthetic superensemble demonstrate greater skill for most of the variables tested here. The forecast produced by the proposed method out performs other conventional forecasts. These results suggest that the methodology and database employed are able to improve seasonal climate prediction over South America when compared to the use of single climate models or from the conventional ensemble averaging. The results show that anomalous conditions simulated over South America are reasonably realistic. The negative (positive) precipitation anomalies for the summer monsoon season of 1997/98 (2001/02) were predicted by Synthetic Superensemble formulation quite well. In summary, the forecast produced by the Synthetic Superensemble approach outperforms the other conventional forecasts.  相似文献   

14.
The importance of climate services, i.e. providing targeted, tailored, and timely weather and climate information, has gained momentum, but requires improved understanding of user needs. This article identifies the opportunities and barriers to the use of climate services for planning in Malawi, to identify the types of information that can better inform future adaptation decisions in sub-Saharan Africa. From policy analysis, stakeholder interviews, and a national workshop utilizing serious games, it is determined that only 5–10 day and seasonal forecasts are currently being used in government decision making. Impediments to greater integration of climate services include spatial and temporal scale, accessibility, timing, credibility and the mismatch in timeframes between planning cycles (1–5 years) and climate projections (over 20 years). Information that could more usefully inform planning decisions includes rainfall distribution within a season, forecasts with 2–3 week lead times, likely timing and location of extreme events in the short term (1–5 years), and projections (e.g. rainfall and temperature change) in the medium term (6–20 years). Development of a national set of scenarios would also make climate information more accessible to decision makers, and capacity building around such scenarios would enable its improved use in short- to medium-term planning. Improved climate science and its integration with impact models offer exciting opportunities for integrated climate-resilient planning across sub-Saharan Africa. Accrual of positive impacts requires enhanced national capacity to interpret climate information and implement communication strategies across sectors.

Policy relevance

For climate services to achieve their goal of improving adaptation decision making, it is necessary to understand the decision making process and how and when various types of weather and climate information can be incorporated. Through a case study of public sector planning in Malawi, this article highlights relevant planning and policy-making processes. The current use of weather and climate information and needs, over various timescales – sub-annual to short term (1–5 years) to medium term (6–20 years) – is outlined. If climate scientists working with boundary organizations are able to address these issues in a more targeted, sector-facing manner they will improve the uptake of climate services and the likelihood of climate-resilient decisions across sub-Saharan Africa.  相似文献   

15.
Summary This study examines the predictability of weather over several regions in Africa using a multimodel superensemble technique developed at the Florida State University, which is an objective means of combining daily forecasts from multilevel global models. It is referred to as FSUSE and up to 7 different models are used to construct the superensemble. The benchmark reanalysis fields used are the precipitation data sets from CMORPH and all other global fields from ECMWF daily operational analysis. The FSUSE works by using multiple linear regression to derive weights from a comparison of each member model forecast to the benchmark analysis during a training period of the most recent 120 days, and these weights are passed to the forecast phase. This procedure removes the bias of each model and allows for an optimal linear combination of the individual model forecasts by taking account of the relative skill of each model to give a consensus forecast that is superior to the ensemble mean and all the members. Results show that bad models and poor analysis fields used during the training phase degrade the skill of the FSUSE. In the forecasts of rainfall events over all regions of Africa, the FSUSE root-mean-square (R M S) error, equitable threat skill score (E T S), and bias on the daily forecasts of rainfall were invariably superior to the best member model. The skills deteriorate as the forecast lead time in days increases, with the degradation being most significant beyond day 3. In all cases, the bias score of the FSUSE was approximately 1, while the anomaly correlation scores were to the order of 0.9. These scores indicate the robustness of the FSUSE forecasts. Over East Africa, the FSUSE forecasts were consistent with the spatial-temporal pattern of the Intertropical Convergence Zone (ITCZ), the main rain bearing synoptic mechanism across tropical Africa. Thus, in addition to superior forecasts, the use of FSUSE based data sets may provide a better understanding of the dynamical processes within the ITCZ over the region. These results could be further improved if the daily series of operational analysis had included gauge data and if the resolution were higher. It is hardly possible to get uniformly consistent and continuous daily observations over these diverse regions of Africa. However, given the availability of the satellite based estimates of daily rainfall, such as CMORPH and global analysis that are exchanged very fast nowadays, the FSUSE scheme for numerical weather predictions (N W P) provides useful medium range weather forecasts in real-time.  相似文献   

16.
基于集合预报的中国极端强降水预报方法研究   总被引：3，自引：1，他引：2  
刘琳  陈静  程龙  林春泽  吴志鹏 《气象学报》2013,71(5):853-866
极端强降水天气属于小概率事件,其发生具有很多不确定的因素,预报难度很大。根据Anderson-Darling检验原理研究基于集合预报资料的极端强降水天气预报方法,利用2007—2010年中国T213集合预报资料和2001—2010年6—8月中国降水观测资料,分析观测与集合预报累积概率密度分布函数的特征,建立基于集合预报与模式历史预报累积概率密度分布函数连续差异的数学模型——极端降水天气预报指数(EPFI),并对2011年7月中国极端强降水天气进行预报试验。结果表明,极端降水天气预报指数可以充分利用集合降水累积概率密度分布的尾端信息,为极端强降水提供科学合理的预报,基于中国气象局(CMA) T213集合预报的极端降水天气预报指数可提前3—7 d发出极端强降水预警信号,随着预报时效的延长,预报技巧逐渐降低。研究还表明,模式气候累积概率分布的合理性将直接影响极端强降水天气识别能力。  相似文献   

17.
数值预报误差订正技术中相似-动力方法的发展   总被引：3，自引：0，他引：3       下载免费PDF全文
Due to the increasing requirement for high-level weather and climate forecasting accuracy, it is necessary to exploit a strategy for model error correction while developing numerical modeling and data assimilation techniques. This study classifies the correction strategies according to the types of forecast errors, and reviews recent studies on these correction strategies. Among others, the analogue-dynamical method has been developed in China, which combines statistical methods with the dynamical model, corrects model errors based on analogue information, and effectively utilizes historical data in dynamical forecasts. In this study, the fundamental principles and technical solutions of the analogue-dynamical method and associated development history for forecasts on different timescales are introduced. It is shown that this method can effectively improve medium- and extended-range forecasts, monthly-average circulation forecast, and short-term climate prediction. As an innovative technique independently developed in China, the analogue- dynamical method plays an important role in both weather forecast and climate prediction, and has potential applications in wider fields.  相似文献   

18.
East Africa is particularly vulnerable to precipitation variability, as the livelihood of much of the population depends on rainfed agriculture. Seasonal forecasts of the precipitation anomalies, when skillful, can therefore improve implementation of coping mechanisms with respect to food security and water management. This study assesses the performance of Nanjing University of Information Science and Technology Climate Forecast System version 1.0(NUISTCFS1.0) on forecasting June–September(JJAS) seasonal precipitation anomalies over East Africa. The skill in predicting the JJAS mean precipitation initiated from 1 May for the period of 1982–2019 is evaluated using both deterministic and probabilistic verification metrics on grid cell and over six distinct clusters. The results show that NUIST-CFS1.0 captures the spatial pattern of observed seasonal precipitation climatology, albeit with dry and wet biases in a few parts of the region. The model has positive skill across a majority of Ethiopia, Kenya, Uganda, and Tanzania, whereas it doesn’t exceed the skill of climatological forecasts in parts of Sudan and southeastern Ethiopia. Positive forecast skill is found over regions where the model shows better performance in reproducing teleconnections related to oceanic SST. The prediction performance of NUIST-CFS1.0 is found to be on a level that is potentially useful over a majority of East Africa.  相似文献   

19.
Rural, resource-poor communities currently face a number of stressors that curtail livelihood options and reduce overall quality of life. Climate stress in southern Africa could potentially further threaten the livelihoods of such communities. Inappropriate response and adaptation options to risks, including climate stress, could further undermine development efforts in the region. The design and effective implementation of strategies to improve coping and adaptation to possible future risks cannot be undertaken without a detailed assessment of current response options to various risks. By using the Sustainable Livelihoods Framework, this pilot study identifies some of the strategies and constraints to secure livelihoods that are currently being used by small-scale farmers in the Muden area of KwaZulu-Natal. The role and perception of climate risks in relation to a variety of other constraints and risks in the area are also examined. Health status, lack of information and ineffective institutional structures and processes are shown to be some of the key factors aggravating current response options and overall development initiatives with potential negative outcomes for future adaptation to periods of possible heightened climate stress.  相似文献   

20.
The article explores the strategies employed by smallholder farmers in Mexico to cope with the affects of climatic variability, and how seasonal climate forecasts may assist these farmers in mitigating climatic risk. Recognizing that the decisions of smallholder farmers are intricately tied to the political-economic circumstances in which they operate, the article discusses how agricultural policy in Mexico affects the vulnerability of small-scale producers and may inhibit their ability to use climatic forecasts to their advantage. The article first reviews the literature on smallholder adaptation in Mexico, and discusses briefly policy and institutional issues affecting adaptation at the farm-level. Using the case of small-scale maize producers in Tlaxcala, Mexico, as an illustration, the article then argues that political-economic uncertainty outweighs climatic variability as a determinant of the production strategies of small-scale producers. In these circumstances, the farmers are unlikely to use new seasonal climate forecasts.  相似文献   

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