Ocean land atmosphere Interaction

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

Sea ice is an important transport vehicle for gaseous, dissolved and particulate matter in the Arctic Ocean. Due to the recently observed acceleration in sea ice drift, it has been assumed that more matter is advected by the Transpolar Drift from shallow shelf waters to the central Arctic Ocean and beyond. However, this study provides first evidence that intensified melt in the marginal zones of the Arctic Ocean interrupts the transarctic conveyor belt and has led to a reduction of the survival rates of sea ice exported from the shallow Siberian shelves (−15% per decade). As a consequence, less and less ice formed in shallow water areas (<30 m) has reached Fram Strait (−17% per decade), and more ice and ice-rafted material is released in the northern Laptev Sea and central Arctic Ocean. Decreasing survival rates of first-year ice are visible all along the Russian shelves, but significant only in the Kara Sea, East Siberian Sea and western Laptev Sea. Identified changes affect bio...

1Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK, USA 2Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany 3Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA 4Natural Resources Canada, Geological Survey of Canada-Atlantic, Dartmouth, Nova Scotia, Canada 5Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia 6Mel'nikov Permafrost Institute, Siberian Branch, Russian Academy of Sciences, Yakutsk, Russia 7Department of Biology, University of Texas El Paso, El Paso, TX, USA 8U.S. Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA, USA 9Institute of Geography and Regional Development, University of Wroclaw, Wroclaw, Poland 10SINTEF AS, SINTEF Community, Trondheim, Norway 11Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark 12Centre of Geographical Studies, Institute of Geography and Spatial Pla...

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

Perennially frozen ground and sea ice are key constituents of permafrost coastal systems, and their presence is the primary difference between temperate and high-latitude coastal processes. These systems are some of the most rapidly changing landscapes on Earth and, in the Arctic, are representative of the challenges being faced at the intersection between natural and anthropogenic systems. Permafrost thaw, in combination with increasing sea level and decreasing sea-ice cover, exposes arctic coastal and nearshore areas to rapid environmental and social changes. Based on decadal timescales, observations in the Arctic indicate an increase in permafrost coastal bluff erosion and storm surge flooding of low-lying ice-rich permafrost terrain. However, circum-arctic observations remain limited and the factors responsible for the apparent increase in arctic coastal dynamics are poorly constrained. A better understanding of permafrost coastal systems and how they are responding to changes i...

The Central America region hosts a valuable amount of World Heritage Sites (WHS), many of them located in areas of floods, landslides, drought, high winds, intense precipitations, and earthquakes. The effective management of WHS requires the understanding of this type of environmental phenomena and their potential impacts on these sites. The objective of this work is twofold. To make an analysis of some of the atmospheric systems (easterly waves, cold fronts and tropical cyclones [TCs]) hitting Central America, to estimate their effects on socio-economic activities and potential impacts on WHS during the period 2002-2012. The second objective is to identify, for a case study, the potential effects of hydro-meteorological events associated with a tropical storm on the Diquis Delta region in southern Costa Rica. This site, an important unique archeological site of stone spheres, has been proposed by this country as a WHS. To achieve both, public data bases like HURDAT (North Atlantic Hurricane Database), and information from regional newspapers and National Emergency Committees, among other sources, were used for the study of socio-economic impacts caused by these natural hazards. To accomplish the latter, course resolution NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) Reanalysis atmospheric data served to initialize version 5 of a numerical atmospheric mesoscale model (MM5). This approach permitted to obtain higher resolution gridded data for a set of atmospheric variables for a case study associated with the formation of tropical storm Alma upon the Pacific basin. The MM5 resulted winds and precipitation, among other variables, were then used to evaluate potential impacts on the WHS region. Among the systems analyzed for Central America, TCs were the ones that most severely impacted regional social life and worsened the already weak regional economies. During the period analyzed, TCs affected regions where WHS are very relevant to cultural life and touristic income. The MM5 derived data shows its potential for providing detailed spacetime atmospheric data to help quantify and anticipate impacts for WHS protection and management. The overall results are expected to bring the attention of organizations and governments about the importance of socio-economic and cultural losses associated with the impacts caused by natural hazards near WHS in the region.

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

Arctic coastal zones serve as a sensitive filter for terrigenous matter input onto the shelves via river discharge and coastal erosion. This material is further distributed across the Arctic by ocean currents and sea ice. The coastal regions are particularly vulnerable to changes related to recent climate change. We compiled a pan-arctic review that looks into the changing Holocene sources, transport processes and sinks of terrigenous sediment in the Arctic Ocean. Existing paleoceanographic studies demonstrate how climate warming and the disappearance of ice sheets during the early Holocene initiated eustatic sea-level rise that greatly modified the physiography of the Arctic Ocean. Sedimentation rates over the shelves and slopes were much greater during periods of rapid sea-level rise in the early and middle Holocene, due to the relative distance to the terrestrial sediment sources. However, estimates of suspended sediment delivery through major Arctic rivers do not indicate enhanc...

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

The Web has amply demonstrated the benefits of an infrastructure that makes publishing and reference of semi-structured information easily accessible, but in many cases reference and reuse of such information is only at the level of complete files. The potential for greater benefits that may derive from sub-document structure and reference is currently being explored, but this exploration is limited by the fact that such references can only be used with a portion of the Web's content (i.e. that encoded in XML). We have developed a system, the Network-Oriented Document Abstraction Language (NODAL), that is designed to provide a common data model, schema language and sub-document reference system for web-accessible documents or databases encoded in any format (e.g. images, PDF or Word documents etc.). This system thus provides a common reference and access environment for all structured, semi-structured and unstructured data. In this paper, we describe the data model, schema language and URI-based reference language for NODAL and compare it with XML and other systems. Finally, we outline a number of ways that this system can be extended to allow for composition, synchronization and reuse of documents and databases and can thus form a hypertextual foundation for interactive application development without inhibiting interoperability with existing systems. In essence, with NODAL we can bring the benefits of markup and hypertext to all data formats.

Ongoing climate change focuses attention on the Arctic cryosphere's responses to past and future climate states. Although it is now recognized the Arctic Ocean Basin was covered by ice sheets and their associated floating ice shelves several times during the Late Pleistocene, the timing and extent of these polar ice sheets remain uncertain. Here we relate a relict barrier-island system on the Beaufort Sea coast of northern Alaska to the isostatic effects of a previously unrecognized ice shelf grounded on the adjacent continental shelf. A new suite of optically stimulated luminescence dates show that this barrier system formed during one or more marine transgressions occurring late in Marine Isotope Stage 5 (MIS 5) between 113 ka and 71 ka. Because these transgressions occurred after the warmest part of the last interglacial (ca. 123 ka) and did not coincide with the global eustatic sea-level maximum during MIS 5e, this indicates Arctic ice sheets developed out-of-phase with lower-latitude sectors of the Laurentide and Fennoscandian ice sheets. We speculate that Arctic ice sheets began development during full interglacial conditions when abundant moisture penetrated to high latitudes, and low summer insolation favored glacier growth. These ice sheets reached their full extents at interglacial-glacial transitions, then wasted away at the heights of mid-latitude glaciations because of moisture limitations.

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds-the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the midsummer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 • C (around May). Then, the SST decreases to around 1 • C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 • C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

Arctic coastal zones serve as a sensitive filter for terrigenous matter input onto the shelves via river discharge and coastal erosion. This material is further distributed across the Arctic by ocean currents and sea ice. The coastal regions are particularly vulnerable to changes related to recent climate change. We compiled a pan-Arctic review that looks into the changing Holocene sources, transport processes and sinks of terrigenous sediment in the Arctic Ocean. Existing palaeoceanographic studies demonstrate how climate warming and the disappearance of ice sheets during the early Holocene initiated eustatic sea-level rise that greatly modified the physiography of the Arctic Ocean. Sedimentation rates over the shelves and slopes were much greater during periods of rapid sea-level rise in the early and middle Holocene, as a result of the relative distance to the terrestrial sediment sources. However, estimates of suspended sediment delivery through major Arctic rivers do not indicate enhanced delivery during this time, which suggests enhanced rates of coastal
erosion. The increased supply of terrigenous material to the outer shelves and deep Arctic Ocean in the early and middle Holocene might serve as analogous to forecast changes in the future Arctic.

The relationship between monthly mean sea surface temperature (SST) anomalies in the commonly used El Niño regions and precipitation for 44 stations in Perú is documented for 1950-2002. Linear lag correlation analysis is employed to establish the potential for statistical precipitation forecasts from SSTs. Useful monthly mean precipitation anomaly forecasts are possible for several locations and calendar months if SST anomalies in El Niño 1+2, Niño 3.4, and Niño 4 regions are available. Prediction of SST anomalies in El Niño regions is routinely available from Climate Prediction Center, NOAA, with reasonable skill in the El Niño 3.4 region, but the prediction in El Niño 1+2 region is less reliable. The feasibility of using predicted SST anomalies in the El Niño 3.4 region to predict SST anomalies in El Niño 1+2 region is discussed.

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds – the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May–June and the other in August-September-October (ASO), separated by the mid-summer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 °C (around May). Then, the SST decreases to around 1 °C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 °C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.