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81.
Reducing Emissions from Deforestation and forest Degradation (REDD+) has emerged as a promising climate change mitigation mechanism in developing countries. In order to identify the enabling conditions for achieving progress in the implementation of an effective, efficient and equitable REDD+, this paper examines national policy settings in a comparative analysis across 13 countries with a focus on both institutional context and the actual setting of the policy arena. The evaluation of REDD+ revealed that countries across Africa, Asia and Latin America are showing some progress, but some face backlashes in realizing the necessary transformational change to tackle deforestation and forest degradation. A Qualitative Comparative Analysis (QCA) undertaken as part of the research project showed two enabling institutional configurations facilitating progress: (1) the presence of already initiated policy change; and (2) scarcity of forest resources combined with an absence of any effective forestry framework and policies. When these were analysed alongside policy arena conditions, the paper finds that the presence of powerful transformational coalitions combined with strong ownership and leadership, and performance-based funding, can both work as a strong incentive for achieving REDD+ goals.

Key policy insights

  • The positive push of already existing policy change, or the negative stress of resource scarcity together with lack of effective policies, represents institutional conditions that can support REDD+ progress.

  • Progress also requires the presence of powerful transformational coalitions and strong ownership and leadership. In the absence of these internal drivers, performance-based funding can work as a strong incentive.

  • When comparing three assessments (2012, 2014, 2016) of REDD+ enabling conditions, some progress in establishing processes of change can be observed over time; however, the overall fluctuation in progress of most countries reveals the difficulty in changing the deforestation trajectory away from business as usual.

  相似文献   
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Deo  Anil  Chand  Savin S.  Ramsay  Hamish  Holbrook  Neil J.  McGree  Simon  Magee  Andrew  Bell  Samuel  Titimaea  Mulipola  Haruhiru  Alick  Malsale  Philip  Mulitalo  Silipa  Daphne  Arieta  Prakash  Bipen  Vainikolo  Vaiola  Koshiba  Shirley 《Climate Dynamics》2021,56(11):3967-3993

Southwest Pacific nations are among some of the worst impacted and most vulnerable globally in terms of tropical cyclone (TC)-induced flooding and accompanying risks. This study objectively quantifies the fractional contribution of TCs to extreme rainfall (hereafter, TC contributions) in the context of climate variability and change. We show that TC contributions to extreme rainfall are substantially enhanced during active phases of the Madden–Julian Oscillation and by El Niño conditions (particularly over the eastern southwest Pacific region); this enhancement is primarily attributed to increased TC activity during these event periods. There are also indications of increasing intensities of TC-induced extreme rainfall events over the past few decades. A key part of this work involves development of sophisticated Bayesian regression models for individual island nations in order to better understand the synergistic relationships between TC-induced extreme rainfall and combinations of various climatic drivers that modulate the relationship. Such models are found to be very useful for not only assessing probabilities of TC- and non-TC induced extreme rainfall events but also evaluating probabilities of extreme rainfall for cases with different underlying climatic conditions. For example, TC-induced extreme rainfall probability over Samoa can vary from ~ 95 to ~ 75% during a La Niña period, if it coincides with an active or inactive phase of the MJO, and can be reduced to ~ 30% during a combination of El Niño period and inactive phase of the MJO. Several other such cases have been assessed for different island nations, providing information that have potentially important implications for planning and preparing for TC risks in vulnerable Pacific Island nations.

  相似文献   
83.
大气和植被生态及土壤系统水文过程相互作用的一些研究   总被引:8,自引:1,他引:8  
利用我国测站的降水资料、卫星测得的OLR和高云量资料、SST和137°E次表层海温资料以及NCEP/NCAR再分析资料,分析了东亚夏季风的爆发和北进的年际变化特征及其与热带西太平洋热状态的关系.分析结果表明:当春季热带西太平洋处于暖状态,菲律宾周围对流活动强,在这种情况下,南海上空对流层下层有气旋性距平环流,西太平洋副热带高压偏东,从而使得南海夏季风爆发早;并且,当夏季热带西太平洋也处于暖状态,菲律宾周围对流活动也很强,在这种情况下,西太平洋副热带高压北进时,在6月中旬和7月初存在明显的突跳,从而使得东亚季风雨带在6月中旬明显由华南北跳到江淮流域,并于7月初由江淮流域北跳到黄河流域、华北和东北地区.这将引起江淮流域和长江中、下游夏季风降水偏少,并往往发生干旱,而黄河流域、华北和东北地区的夏季降水正常或偏多.相反,当春季热带西太平洋处于冷状态,菲律宾周围对流活动弱,在这种情况下,南海上空对流层下层有反气旋性距平环流,西太平洋副热带高压偏西,从而使得南海夏季风爆发晚;并且,当夏季热带西太平洋也处于冷状态,菲律宾周围对流活动也很弱,在这种情况下,西太平洋副热带高压北进时,在6月中旬或7月初向北突跳并不明显,而是以渐进式向北移动,从而使得东亚季风雨带一直维持在长江流域和淮河流域.这将引起此两流域夏季风降水偏多,并往往发生洪涝,而黄河流域、华北和东北地区的夏季降水偏少,发生干旱.作者还从非线性多平衡态动力理论说明了菲律宾周围对流活动强弱对西太平洋副热带高压北进时以突跳或渐进式向北移动起到重要作用.  相似文献   
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Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R2 = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R2 = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R2 = 0.47 and RMSE 9.34 VWC%, and for the latter R2 = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m2 digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   
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