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Climate anomalies, both worldwide and in Ecuador, are becoming more frequent and intense, generating negative impacts on society, economy and the environment. Given the possibility of hydrometeorological events, such as an El Niño event, the question arises of whether Ecuador is prepared to face and reduce the impacts of climate change. To answer this, different factors are analyzed, such as the existence of a national policy, institutional capacity to respond, options for professional training and human resources, availability and access to updated data, and economic and technological resources. In general terms, it is concluded that Ecuador does not have an adequate national policy or an institution with sufficient resources and capacity to generate, process and disseminate data and information necessary to make decisions regarding climate change. It is necessary to address the current and structural shortcomings and establish a national policy for the management of meteorology and hydrology that generates options for professional training, a decentralized technical institution with adequate resources, and performs a role of leadership and facilitator of processes around the national policy of meteorology and hydrology., Las anomalías climáticas, tanto a nivel mundial como en Ecuador, son cada vez más frecuentes y de mayor intensidad, generando impactos negativos en la sociedad, economía y medio ambiente. Ante la posibilidad de eventos hidrometeorológicos, como un evento El Niño, surge la pregunta de si Ecuador está preparado para enfrentar y reducir los impactos del cambio climático. Para responder a esto, se analizan diferentes factores como la existencia de política nacional, institucionalidad con capacidad de respuesta, opciones de formación profesional y recursos humanos, disponibilidad y acceso a datos actualizados, y recursos económicos y tecnológicos. En términos generales, se concluye que Ecuador no cuenta con una política nacional adecuada ni una institucionalidad con recursos y capacidad suficientes para generar, procesar y difundir datos e información necesarios para tomar decisiones frente al cambio climático. Es necesario enfrentar las falencias coyunturales y estructurales y establecer una política nacional para la gestión nacional de la meteorología e hidrología que genere opciones de formación profesional, una institucionalidad técnica desconcentrada y con recursos adecuados, y cumpla un rol de rectoría y facilitador de procesos en torno a la política nacional de la meteorología e hidrología.

Harmful algal blooms (HABs) in southern Chile are a serious threat to public health, tourism, artisanal fisheries, and aquaculture in this region. Ichthyotoxic HAB species have recently become a major annual threat to the Chilean salmon farming industry, due to their severe economic impacts. In early austral autumn 2021, an intense bloom of the raphidophyte Heterosigma akashiwo was detected in Comau Fjord, Chilean Patagonia, resulting in a high mortality of farmed salmon (nearly 6000 tons of biomass) within 15 days. H. akashiwo cells were first detected at the head of the fjord on March 16, 2021 (up to 478 cells mL-1). On March 31, the cell density at the surface had reached a maximum of 2 × 105 cells mL-1, with intense brown spots visible on the water surface. Strong and persistent high-pressure anomalies over the southern tip of South America, consistent with the positive phase of the Southern Annular Mode (SAM), resulted in extremely dry conditions, high solar radiation, and strong southerly winds. A coupling of these features with the high water retention times inside the fjord can explain the spatial-temporal dynamics of this bloom event. Other factors, such as the internal local physical uplift process (favored by the north-to-south orientation of the fjord), salt-fingering events, and the uplift of subantarctic deep-water renewal, likely resulted in the injection of nutrients into the euphotic layer, which in turn could have promoted cell growth and thus high microalgal cell densities, such as reached by the bloom.

Offspring size is a key functional trait that can affect subsequent life history stages; in many species, it exhibits both local adaptation and phenotypic plasticity. Variation among populations in offspring size may be explained by various factors, including local climatic conditions. However, geographic variation in climate may be partitioned into long-term and interannual sources of variation, which may differ in their effects on population mean offspring size. To assess environmental correlates of offspring size, we evaluated geographic variation in seed mass among 88 populations representing 6 species of Streptanthus (Brassicaceae) distributed across a broad climatic gradient in California. We examined the effects of temperature-mediated growing season length and precipitation on population mean seed mass to determine whether it is best explained by (1) long-term mean climatic conditions; (2) interannual climate anomalies (i.e., deviations in climate from long-term means) during the year of seed development, or (3) interactions between climate variables. Both long-term mean climate and climate anomalies in the year of collection were associated with population mean seed mass, but their effects differed in direction and magnitude. Relatively large seeds were produced at chronically wet sites but also during drier-than-average years. This contrast indicates that these associations may be generated by different mechanisms (i.e., adaptive evolution vs. phenotypic plasticity) and may be evidence of countergradient plasticity in seed mass. In addition, populations occurring in locations characterized by relatively long growing seasons produced comparatively large seeds, particularly among chronically dry sites. This study highlights the need to consider that the responses of seed mass to long-term versus recent climatic conditions may differ and that climate variables may interact to predict seed mass. Such considerations are especially important when using these pat

Offspring size is a key functional trait that can affect subsequent life history stages; in many species, it exhibits both local adaptation and phenotypic plasticity. Variation among populations in offspring size may be explained by various factors, including local climatic conditions. However, geographic variation in climate may be partitioned into long-term and interannual sources of variation, which may differ in their effects on population mean offspring size. To assess environmental correlates of offspring size, we evaluated geographic variation in seed mass among 88 populations representing 6 species of Streptanthus (Brassicaceae) distributed across a broad climatic gradient in California. We examined the effects of temperature-mediated growing season length and precipitation on population mean seed mass to determine whether it is best explained by (1) long-term mean climatic conditions; (2) interannual climate anomalies (i.e., deviations in climate from long-term means) during the year of seed development, or (3) interactions between climate variables. Both long-term mean climate and climate anomalies in the year of collection were associated with population mean seed mass, but their effects differed in direction and magnitude. Relatively large seeds were produced at chronically wet sites but also during drier-than-average years. This contrast indicates that these associations may be generated by different mechanisms (i.e., adaptive evolution vs. phenotypic plasticity) and may be evidence of countergradient plasticity in seed mass. In addition, populations occurring in locations characterized by relatively long growing seasons produced comparatively large seeds, particularly among chronically dry sites. This study highlights the need to consider that the responses of seed mass to long-term versus recent climatic conditions may differ and that climate variables may interact to predict seed mass. Such considerations are especially important when using these pat

Negative impacts of climate change are expected in the production of Coffea arabica L. one of the most commercialized tropical agroproducts in the world. However, most studies work with global circulation models, being of little use in making decisions on the scale of farm management. Given this, the objective of this study was to identify the suitability for the cultivation of C. arabica in the face of climate change and how tree cover mitigates the impacts of climate change in an agroforestry plot. The indices of climatic extremes were calculated (1961 to 2016 for Coatepec; 1985 to 2016 for Briones) and a trend analysis was carried out (Mann-Kendall). The temperature inside a plot, and on an open site, was monitored for two years (2017-2019). This was related to the climatic requirements of C. Arabica. Trends of increase (p < 0.05) of the minimum and minimum extreme annual temperatures were identified in the two stations near the plot (0.24 and 0.69 °C·decade-1 in Coatepec and 0.46 and 0.79 °C·decade-1 in Briones). The maximum temperature did not present significant increases, reducing the thermal amplitude. Both annual and seasonal precipitation shows trends of increase in intensity. All these conditions are still suitable for the cultivation of C. arabica. At the plot scale, the importance of tree cover is demonstrated, which in this agroforestry system allows to reduce the maximum temperature by 1.9 °C compared to an open site. Tree cover has also made it possible to mitigate extreme events., Se prevén impactos negativos del cambio climático en la producción de Coffea arabica L. uno de los agroproductos tropicales más comercializados en el mundo. Sin embargo, la mayoría de los estudios trabajan con modelos de circulación global, siendo poco útiles en la toma de decisiones a escala de manejo de una finca. Ante ello, el objetivo de este estudio fue identificar la aptitud para el cultivo de C. arabica ante el cambio climático y cómo la cobertura arbórea mitiga los impactos del cambio climático en una parcela agroforestal. Se calcularon los índices de extremos climáticos (1961 a 2016 para Coatepec; 1985 a 2016 para Briones) y se realizó un análisis de tendencias (Mann-Kendall). Se monitoreó la temperatura en el interior de una parcela, y en un sitio abierto, durante dos años (2017-2019). Esto se relacionó con los requerimientos climáticos de C. arabica. Se identificaron tendencias de incremento (p<0,05) de las temperaturas mínima y mínima extrema anual en las dos estaciones cercanas a la parcela (0,24 y 0,69 °C·década-1 en Coatepec y 0,46 y 0,79 °C·década-1 en Briones). La temperatura máxima no presentó incrementos significativos, reduciendo la amplitud térmica. Tanto la precipitación anual y estacional muestran tendencias de incremento en intensidad. Todas estas condiciones siguen siendo aptas para el cultivo de C. arabica. A escala de parcela, se demuestra la importancia de la cobertura arbórea, que en este sistema agroforestal permite reducir la temperatura máxima 1,9 °C en comparación con un sitio abierto. Asimismo, la cobertura arbórea ha permitido mitigar eventos extremos.

El Niño event ranks as one of the most severe on record in terms of the magnitude and extent of sea surface temperature (SST) anomalies generated in the tropical Pacific Ocean. Corresponding global impacts on the climate were expected to rival, or even surpass, those of the 1997-1998 severe El Niño event, which had SST anomalies that were similar in size. However, the 2015-2016 event failed to meet expectations for hydrologic change in many areas, including those expected to receive well above normal precipitation. To better understand how climate anomalies during an El Niño event impact soil moisture, we investigate changes in soil moisture in the humid tropics (between k-means cluster analysis to the soil moisture estimates during the El Niño mature phase, resulting in four groups of clustered data. The strongest and most consistent decreases in soil moisture occur in the Amazon basin and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. In addition, we compare changes in soil moisture to both precipitation and evapotranspiration, which showed a lack of agreement in the direction of change between these variables and soil moisture most prominently in the southern Amazon basin, the Sahel and mainland southeastern Asia. Our results can be used to improve estimates of spatiotemporal differences in El Niño impacts on soi

Climatic anomalies affect agricultural production, so the identification of climate change at the local level is a pressing task. The Intergovernmental Panel on Climate Change (IPCC) has generated indices that allow the identification of extreme climate events. Recent studies of weather and climate variation have increasingly used the climate extreme indices defined by the IPCC. This article dwells upon the ICC (climate change indicators) software written in the Java language which is a convenient tool for storing and processing large sets of daily weather data. The software allows the calculation of 27 climate change indices and four indices for growing vines. Built-in analytical tools help identify trends and climate anomalies on different time intervals. The application is additionally supplied with important functionality for statistical data processing and visualization. Tools that help analyzing climate change can foster wiser strategic decision-making in the management of agriculture and ecosystems., Las anomalías climáticas afectan la producción agrícola, por lo que la identificación del cambio climático a nivel local es una tarea apremiante. El Panel Intergubernamental sobre Cambio Climático (IPCC) ha generado índices que permiten identificar los eventos climáticos extremos. En este artículo se trata sobre el desarrollo del software ICC (Indicadores del cambio climático). ICC es una herramienta conveniente para almacenar y procesar conjuntos grandes de datos meteorológicos diarios. El software permite el cálculo de 27 índices de cambio climático y cuatro índices para el crecimiento de la uva. Las herramientas analíticas integradas ayudan a identificar tendencias y anomalías climáticas en diferentes intervalos de tiempo. El software permite un rápido procesamiento y visualización de datos, es de fácil manejo y tiene una interfaz intuitiva. El conocimiento sobre el cambio climático puede fomentar una toma de decisiones estratégicas más sensatas en el manejo de la agricultura y los ecosistemas en general.

Climatic anomalies affect agricultural production, so the identification of climate change at the local level is a pressing task. The Intergovernmental Panel on Climate Change (IPCC) has generated indices that allow the identification of extreme climate events. Recent studies of weather and climate variation have increasingly used the climate extreme indices defined by the IPCC. This article dwells upon the ICC (climate change indicators) software written in the Java language which is a convenient tool for storing and processing large sets of daily weather data. The software allows the calculation of 27 climate change indices and four indices for growing vines. Built-in analytical tools help identify trends and climate anomalies on different time intervals. The application is additionally supplied with important functionality for statistical data processing and visualization. Tools that help analyzing climate change can foster wiser strategic decision-making in the management of agriculture and ecosystems., Las anomalías climáticas afectan la producción agrícola, por lo que la identificación del cambio climático a nivel local es una tarea apremiante. El Panel Intergubernamental sobre Cambio Climático (IPCC) ha generado índices que permiten identificar los eventos climáticos extremos. En este artículo se trata sobre el desarrollo del software ICC (Indicadores del cambio climático). ICC es una herramienta conveniente para almacenar y procesar conjuntos grandes de datos meteorológicos diarios. El software permite el cálculo de 27 índices de cambio climático y cuatro índices para el crecimiento de la uva. Las herramientas analíticas integradas ayudan a identificar tendencias y anomalías climáticas en diferentes intervalos de tiempo. El software permite un rápido procesamiento y visualización de datos, es de fácil manejo y tiene una interfaz intuitiva. El conocimiento sobre el cambio climático puede fomentar una toma de decisiones estratégicas más sensatas en el manejo de la agricultura y los ecosistemas en general.

Dinophysis acuta is a frequent seasonal lipophilic toxin producer in European Atlantic coastal waters associated with thermal stratification. In the Galician Rías, populations of D. acuta with their epicentre located off Aveiro (northern Portugal), typically co-occur with and follow those of Dinophysis acuminata during the upwelling transition (early autumn) as a result of longshore transport. During hotter than average summers, D. acuta blooms also occur in August in the Rías, when they replace D. acuminata. Here we examined a 30-year (1985–2014) time series of D. acuta from samples collected by the same method in the Galician Rías. Our main objective was to identify patterns of distribution and their relation with climate variability, and to explain the exceptional summer blooms of D. acuta in 1989–1990. A dome-shaped relationship was found between summer upwelling intensity and D. acuta blooms; cell maxima were associated with conditions where the balance between upwelling intensity and heating, leading to deepened thermoclines, combined with tidal phase (3 days after neap tides) created windows of opportunity for this species. The application of a generalized additive model based on biological (D. acuta inoculum) and environmental predictors (Cumulative June–August upwelling CUIJJA, average June–August SSTJJA and tidal range) explained more than 70% of the deviance for the exceptional summer blooms of D. acuta, through a combination of moderate (35,000–50,000 m3 s−1 km−1) summer upwelling (CUIJJA), thermal stratification (SSTJJA > 17 °C) and moderate tidal range (∼2.5 m), provided D. acuta cells (inoculum) were present in July. There was no evidence of increasing trends in D. acuta bloom frequency/intensity nor a clear relationship with NAO or other long-term climatic cycles. Instead, the exceptional summer blooms of 1989–1990 appeared linked to extreme hydroclimatic anomalies (high positive anomalies in SST and NAO index), which affected most of the European At

Aim: Bioclimatic envelope models are widely used to describe changes in climatically suitable areas for species under future climate scenarios. Climate change metrics are applied independently of species data to characterize the spatio-temporal dynamics of climate, and have also been used as indicators of the exposure of species to climate change. Here, we investigate whether these two approaches provide qualitatively similar indications about where biodiversity is potentially most exposed to climate change. Location: Sub-Saharan Africa. Methods: We compared a range of climate change metrics for sub-Saharan Africa with ensembles of bioclimatic envelope models for 2723 species of amphibians, snakes, mammals and birds. For each taxonomic group, we performed three comparisons between the two approaches: (1) is projected change in local climatic suitability (models) greater in grid cells with larger temporal differences in local climate (metrics); (2) are projected losses or gains of climatically suitable areas (models) greater for species in grid cells with climates that are projected to be less or more available in the future, respectively (metrics); and (3) are projected shifts in the position of climatically suitable areas (models) greater for species in grid cells with climates projected to move farther in space (metrics)? Results: The changes in climatic suitability projected by the bioclimatic envelope models covaried with the climatic changes measured with the metrics. Agreement between the two approaches was found for all taxonomic groups, although it was stronger for species with a narrower climatic envelope breadth. Main conclusions: For sub-Saharan African vertebrates, projected patterns of exposure to climate change given by climate change metrics alone were qualitatively comparable to bioclimatic model projections of changes in areas of suitable climate for species. Assessments based on climate change metrics can thus be useful for making first-cut infe

The global terrestrial carbon sink offsets one-third of the world's fossil fuel emissions, but the strength of this sink is highly sensitive to large-scale extreme events. In 2012, the contiguous United States experienced exceptionally warm temperatures and the most severe drought since the Dust Bowl era of the 1930s, resulting in substantial economic damage. It is crucial to understand the dynamics of such events because warmer temperatures and a higher prevalence of drought are projected in a changing climate. Here, we combine an extensive network of direct ecosystem flux measurements with satellite remote sensing and atmospheric inverse modeling to quantify the impact of the warmer spring and summer drought on biosphereatmosphere carbon and water exchange in 2012. We consistently find that earlier vegetation activity increased spring carbon uptake and compensated for the reduced uptake during the summer drought, which mitigated the impact on net annual carbon uptake. The early phenological development in the Eastern Temperate Forests played a major role for the continental-scale carbon balance in 2012. The warm spring also depleted soil water resources earlier, and thus exacerbated water limitations during summer. Our results show that the detrimental effects of severe summer drought on ecosystem carbon storage can be mitigated by warming-induced increases in spring carbon uptake. However, the results also suggest that the positive carbon cycle effect of warm spring enhances water limitations and can increase summer heating through biosphere-atmosphere feedbacks.

Aim: Bioclimatic envelope models are widely used to describe changes in climatically suitable areas for species under future climate scenarios. Climate change metrics are applied independently of species data to characterize the spatio-temporal dynamics of climate, and have also been used as indicators of the exposure of species to climate change. Here, we investigate whether these two approaches provide qualitatively similar indications about where biodiversity is potentially most exposed to climate change. Location: Sub-Saharan Africa., Methods: We compared a range of climate change metrics for sub-Saharan Africa with ensembles of bioclimatic envelope models for 2723 species of amphibians, snakes, mammals and birds. For each taxonomic group, we performed three comparisons between the two approaches: (1) is projected change in local climatic suitability (models) greater in grid cells with larger temporal differences in local climate (metrics); (2) are projected losses or gains of climatically suitable areas (models) greater for species in grid cells with climates that are projected to be less or more available in the future, respectively (metrics); and (3) are projected shifts in the position of climatically suitable areas (models) greater for species in grid cells with climates projected to move farther in space (metrics)?, Results: The changes in climatic suitability projected by the bioclimatic envelope models covaried with the climatic changes measured with the metrics. Agreement between the two approaches was found for all taxonomic groups, although it was stronger for species with a narrower climatic envelope breadth., Main conclusions: For sub-Saharan African vertebrates, projected patterns of exposure to climate change given by climate change metrics alone were qualitatively comparable to bioclimatic model projections of changes in areas of suitable climate for species. Assessments based on climate change metrics can thus be useful for making first-cut inferences about the potential effects of climate change on regions with poorly known biodiversity.

We have designed, developed, and tested a long-range forecasting system for producing forecasts of surface air temperatures and precipitation rates in the Korean Peninsula region at leads of two months for each calendar month. We tested predictors based on the following: (1) indices of the Arctic Oscillation, El Nino/La Nina, North Atlantic Oscillation, Pacific/North American Pattern, and the West Pacific Pattern; (2) 850 hectopascal geopotential heights and sea surface temperatures in specific regions; (3) persistence; and (4) year (to represent long-term trends). Our forecasting system includes 24 multiple linear regression models, one for temperature and one for precipitation for each month. Each model uses a unique set of predictors. We tested each model by conducting 43 years of cross-validated hindcasting for our 1970-2012 study period. The hindcast results showed that, overall, the models had skill in predicting above normal, near normal, and below normal temperatures and precipitation rates for the Korean Peninsula (e.g., Heidke skill scores 0). We used our January models to successfully forecast temperatures and precipitation for January 2013. We also developed a series of forecaster worksheets to be used to produce forecasts for the Korean Peninsula.

We have designed, developed, and tested a method for generating long-range forecasting systems for predicting environmental conditions at intraseasonal to seasonal lead times (lead times of several weeks to several seasons). The resulting systems use statistical, multimodel, and lagged average ensemble approaches. The ensemble members are generated by multiple regression models that relate globally distributed oceanic and atmospheric predictors to local predictands. The predictands are three tercile categorical forecast targets. The predictors are selected based on their long-lead correlations to the predictands. The models are selected based on their lagged average ensemble skill at multiple leads determined from cross-validated, multidecadal hindcasts. The main system outputs are probabilistic long-lead forecasts, and corresponding quantitative assessments of forecast uncertainty and confidence. Our forecast system development process shows a high potential for meeting a wide range of military and national intelligence requirements for operational long-lead forecast support. The main test bed for our system development was long-range forecasting of environmental conditions in Pakistan. This problem was selected based on DoD and national intelligence priorities for long-range support. For this test case, the system uses 81 ensemble forecast members that predict the probability of summer precipitation rates in north-central Pakistan up to 6 months in advance. The cross-validated hindcast results from the test case system are substantially more skillful than reference climatological forecasts at all leads. The test results also show that the combination of multiple forecast member predictions in a multimodel, lagged average ensemble approach yields more accurate forecasts than any one forecast member individually., The original document contains color images.

Global warming induced by human activity has brought about irreversible environmental changes whose consequences are still being analyzed. Of all the affected areas, the coasts are the most volatile zones due to increasing seawater temperatures and rising sea levels. These climatic changes bring about ecological shifts, strongly impacting the biological equilibrium of coastal ecosystems. These same coastal areas are the naturally occurring habitat of the most important human pathogens of Vibrio: V. cholerae and V. parahaemolyticus. For the last year, the interaction of the oceans and climactic anomalies on the dynamics of diseases associated with these pathogens has been studied with the use of oceanographic data provided by satellites. Studies carried out in Peru using these new tools have allowed the epidemic expansion of V. cholerae and V. parahaemolyticus infections in South America to be linked to the arrival and spread of the El Niño waters. Further investigation using remote sensing data to analyze the dynamic of V. parahaemolyticus outbreaks in the USA, Spain and Chile has led to the conclusion that infections in these areas have also concurred with the presence of oceanic anomalies. The movement of oceanic waters has therefore been identified as a potential vehicle for the dispersion of Vibrio infections on a global scale, opening new channels for exploring and predicting new epidemic outbreaks of these diseases., El calentamiento global producido por la actividad humana está causando un cambio ambiental irreversible, cuyas consecuencias están siendo todavía analizadas. De todas las áreas afectadas, las regiones costeras serán de las zonas más afectadas debido al calentamiento de sus aguas y al aumento del nivel del mar. Estas alteraciones climáticas van a producir cambios ecológicos que tendrán un fuerte impacto en el equilibrio biológico de los ecosistemas costeros. Estas zonas del litoral son el hábitat natural de los dos principales patógenos humanos del género Vibrio: V. cholerae y V. parahaemolyticus. Durante los últimos años, se ha estudiado la interacción de los océanos y las anomalías climáticas en la dinámica de las enfermedades causadas por estos patógenos, utilizando la información oceanográfica aportada por los satélites. Estudios realizados en Perú, empleando estas nuevas herramientas han permitido asociar la expansión epidémica de las infecciones de V. cholera y V. parahaemolyticus en Suramérica con la llegada y propagación de las aguas de El Niño. Estudios posteriores, utilizando datos de detección remota por satélite para analizar la dinámica de los brotes de infección por V. parahaemolyticus en Estados Unidos, España y Chile, han permitido establecer que la aparición de las infecciones en estas regiones fue igualmente concurrente con la presencia de anomalías oceánicas. De esta forma, se ha identificado a los movimientos de aguas oceánicas como un motor potencial de dispersión de las infecciones de Vibrio a escala global, abriendo nuevas vías para explorar y predecir los nuevos brotes epidémicos de estas enfermedades.

The climate of 2003, particularly during Northern Hemisphere summer, was marked by exceptionally abnormal events throughout the world, and Africa was no exception. As record heat waves prevailed over Europe, heavy rains and floods occurred over the west-central Sahara, across the Sudano-Sahelian region and western Kenya, while drought conditions gripped the Guinea Coast and southeastern Southern Africa, and cold waves hit southern South Africa. Among the most remarkable events were record rainfall in the western portion of the Sahara-Sahel and drought conditions over the Guinea Coast that were both caused by an extreme northward penetration of the ITCZ relative to normal years. In addition, record-breaking cold weather occurred in southern South Africa in mid-August by a strong extratropical cyclone accompanied by a cold front. During Southern Hemisphere summer, Madagascar, Mozambique, Zimbabwe, and Malawi frequently experienced heavy rains and fl oods associated with tropical cyclones and their remnants. More than 550 people died and over 2.5 million were displaced because of fl oods in Africa in 2003. Africa's vulnerability to climate hazards could be reduced through enhancements of both short- and long-term coping strategies, climate monitoring and early warning systems, fl ood control infrastructures, and other disaster preparedness measures at all levels, including sub-regional, national, and local levels. Mechanisms that caused various events in Africa in 2003, events which can be viewed as regional responses in Africa to anthropogenic global warming, must be explored from the perspective of global change.

The climate of 2003, particularly during Northern Hemisphere summer, was marked by exceptionally abnormal events throughout the world, and Africa was no exception. As record heat waves prevailed over Europe, heavy rains and floods occurred over the west-central Sahara, across the Sudano-Sahelian region and western Kenya, while drought conditions gripped the Guinea Coast and southeastern Southern Africa, and cold waves hit southern South Africa. Among the most remarkable events were record rainfall in the western portion of the Sahara-Sahel and drought conditions over the Guinea Coast that were both caused by an extreme northward penetration of the ITCZ relative to normal years. In addition, record-breaking cold weather occurred in southern South Africa in mid-August by a strong extratropical cyclone accompanied by a cold front. During Southern Hemisphere summer, Madagascar, Mozambique, Zimbabwe, and Malawi frequently experienced heavy rains and fl oods associated with tropical cyclones and their remnants. More than 550 people died and over 2.5 million were displaced because of fl oods in Africa in 2003. Africa's vulnerability to climate hazards could be reduced through enhancements of both short- and long-term coping strategies, climate monitoring and early warning systems, fl ood control infrastructures, and other disaster preparedness measures at all levels, including sub-regional, national, and local levels. Mechanisms that caused various events in Africa in 2003, events which can be viewed as regional responses in Africa to anthropogenic global warming, must be explored from the perspective of global change.

A meridional Northern Hemisphere (NH) circulation epoch, which began in 1957, is marked by changes in the temperature and precipitation regimes over southwest Russia and central USA depending on the occurrence of NH atmospheric circulation regimes

We have designed, developed, and tested a method for generating long-range forecasting systems for predicting environmental conditions at intraseasonal to seasonal lead times (lead times of several weeks to several seasons). The resulting systems use statistical, multimodel, and lagged average ensemble approaches. The ensemble members are generated by multiple regression models that relate globally distributed oceanic and atmospheric predictors to local predictands. The predictands are three tercile categorical forecast targets. The predictors are selected based on their long-lead correlations to the predictands. The models are selected based on their lagged average ensemble skill at multiple leads determined from cross-validated, multidecadal hindcasts. The main system outputs are probabilistic long-lead forecasts, and corresponding quantitative assessments of forecast uncertainty and confidence. Our forecast system development process shows a high potential for meeting a wide range of military and national intelligence requirements for operational long-lead forecast support. The main testbed for our system development was long-range forecasting of environmental conditions in Pakistan. This problem was selected based on DoD and national intelligence priorities for long-range support. For this test case, the system uses 81 ensemble forecast members that predict the probability of summer precipitation rates in north-central Pakistan up to six months in advance. The cross-validated hindcast results from the test case system are substantially more skillful than reference climatological forecasts at all leads. The test results also show that the combination of multiple forecast member predictions in a multimodel, lagged average ensemble approach yields more accurate forecasts than any one forecast member individually., http://archive.org/details/astatisticalmult109456802, Captain, United States Air Force

We have designed, developed, and tested a long-range forecasting system for producing forecasts of surface air temperatures and precipitation rates in the Korean Peninsula region at leads of two months for each calendar month. We tested predictors based on (1) indices of the Arctic Oscillation, El Nino/La Nina, North Atlantic Oscillation, Pacific/North American Pattern, and the West Pacific Pattern; (2) 850 hectopascal geopotential heights and sea surface temperatures in specific regions; (3) persistence; and (4) year (to represent long-term trends). Our forecasting system includes 24 multiple linear regression models, one for temperature and one for precipitation for each month. Each model uses a unique set of predictors. We tested each model by conducting 43 years of cross-validated hindcasting for our 1970-2012 study period. The hindcast results showed that, overall, the models had skill in predicting above normal, near normal, and below normal temperatures and precipitation rates for the Korean Peninsula (e.g., Heidke skill scores 0). We used our January models to successfully forecast temperatures and precipitation for January 2013. We also developed a series of forecaster worksheets to be used to produce forecasts for the Korean Peninsula., http://archive.org/details/longrangeforecas1094532888, Captain, United States Air Force, Approved for public release; distribution is unlimited.