Abstract. 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.
Abstract. The midsummer drought (MSD) in Central America is characterised in order to create annual indexes representing the timing of its phases (start, minimum and end), and other features relevant for MSD forecasting such as the intensity and the magnitude. The MSD intensity is defined as the minimum rainfall detected during the MSD, meanwhile the magnitude is the total precipitation divided by the total days between the start and end of the MSD. It is shown that the MSD extends along the Pacific coast, however, a similar MSD structure was detected also in two stations in the Caribbean side of Central America, located in Nicaragua. The MSD intensity and magnitude show a negative relationship with Niño 3.4 and a positive relationship with the Caribbean low-level jet (CLLJ) index, however for the Caribbean stations the results were not statistically significant, which is indicating that other processes might be modulating the precipitation during the MSD over the Caribbean coast. On the other hand, the temporal variables (start, minimum and end) show low and no significant correlations with the same indexes.The results from canonical correlation analysis (CCA) show good performance to study the MSD intensity and magnitude, however, for the temporal indexes the performance is not satisfactory due to the low skill to predict the MSD phases. Moreover, we find that CCA shows potential predictability of the MSD intensity and magnitude using sea surface temperatures (SST) with leading times of up to 3 months. Using CCA as diagnostic tool it is found that during June, an SST dipole pattern upon the neighbouring waters to Central America is the main variability mode controlling the inter-annual variability of the MSD features. However, there is also evidence that the regional waters are playing an important role in the annual modulation of the MSD features. The waters in the PDO vicinity might be also controlling the rainfall during the MSD, however, exerting an opposite effect at the north and south regions of Central America.
Central America is a region susceptible to natural disasters and climate change. We reviewed the literature on the main atmospheric and oceanographic forces and climate modulators affecting Central America, for different spatial and time scales. We also reviewed the reported correlation between climate variability, natural hazards and climate change aspects (in the past and future). In addition, we examined the current state of seasonal prediction systems being applied to the region. At inter-annual scales, El Niño/Southern Oscillation is the main climate modulator; however, other indices such as the Tropical North Atlantic, Atlantic Multi-Decadal Oscillation and Pacific Decadal Oscillation, have shown a correlation with precipitation anomalies in the region. Current seasonal forecast systems in the region have shown a constant development, including incorporation of different approaches ranging from statistical to dynamical downscaling, improving prediction of variables such as precipitation. Many studies have revealed the need of including –in addition to the climatic information– socio-economic variables to assess the impact of natural disasters and climate change in the region. These studies highlight the importance of socio-economic and human life losses associated with the impacts caused by natural hazards for organizations and governments. Rev. Biol. Trop. 66(Suppl. 1): S153-S175. Epub 2018 April 01.
We explored the relationship between the precipitation anomalies during May to June as the first peak of the rainy season in the Pacific slope of Central America, and sea surface temperature (SST) fluctuations in the surrounding oceans, using canonical correlation analysis (CCA). With this approach, we studied variations in total precipitation, frequency of rainy days and the monthly occurrence of days with rainfall above (below) the 80th (20th) percentile, due to changes in the nearby SST. Composites of the sea‐level pressure (SLP), geopotential heights (200 hPa), relative humidity (700 hPa), horizontal moisture flux and wind at 850 hPa were estimated to provide a dynamical analysis. The composites are calculated using the information obtained with CCA. In addition, we used a general circulation model forced with fixed SST to explore the sensitivity of the model to the SST patterns found using CCA. The results show that the SST over the tropical North Atlantic controls the precipitation fluctuations at interannual scales, due to its connection with the tropical upper tropospheric trough. Warmer (colder) temperatures result in SLP below normal in the Caribbean region, associated with an increase in the heights at 200 hPa. This vertical configuration reduces the wind shear between 850 and 200 hPa and increases the input of humidity to mid‐levels, creating favourable conditions for deep convection, and favouring the generation of tropical cyclone activity. In the Pacific, a positive anomalous low‐level moisture flux is observed from the ocean to the continental parts of the region and may enhance the formation of mesoscale systems. The classic prediction schemes show a lead time of 1 or 2 months; this is an advantage for climate services operative work. The atmospheric model outcomes replicate the main results found in the composite analysis, reflecting its potential use for model output statistics predictive schemes.
An index capturing the anomalies of the zonal wind at 925 hPa from 1950 to 2010 was defined to explore the relationship between the fluctuations of the Caribbean low-level jet (CLLJ) and the main climate variability modes affecting the Intra-Americas Sea Region. El Niño Southern Oscillation (ENSO) events, here defined using the Niño 3.4 index, are found to be the most important variability modes for the jet anomalies, in agreement with previous studies. However, the Pacific Decadal Oscillation (PDO) and the Pacific/North American (PNA) teleconnection pattern also show significant correlations with the CLLJ anomaly index during February. The North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) reveal a possible interaction with the jet anomalies that could be connected with the cold fronts and cold air surges arriving to the Caribbean basin from the Northern Hemisphere during winter. A composite technique is used to explain the correlations with the Pacific indexes. We found that ENSO events are connected to CLLJ anomalies by modulating the sea-level pressure (SLP) near the east coast of the United States and the Aleutian Low. The pattern displayed by the SLP anomalies (SLPa) is also associated with the PNA. During warm (cold) ENSO phases, negative (positive) anomalies in the SLP field over the east coast of North America produce cyclonic (anticyclonic) circulations at low levels. However, the ENSO signal in the SLPa and the PNA pattern are modulated by the phases of the PDO. Results indicate that when the ENSO and PDO are in phase (out of phase), the SLPa signal is enhanced (weakened or cancelled), affecting the CLLJ anomalies in both direction and intensity, also changing the spatial distribution of precipitation.
The Caribbean low‐level jet (CLLJ) is an important modulator of regional climate, especially precipitation, in the Caribbean and Central America. Previous work has inferred, due to their semiannual cycle, an association between CLLJ strength and meridional sea surface temperature (SST) gradients in the Caribbean Sea, suggesting that the SST gradients may control the intensity and vertical shear of the CLLJ. In addition, both the horizontal and vertical structure of the jet have been related to topographic effects via interaction with the mountains in Northern South America (NSA), including funneling effects and changes in the meridional geopotential gradient. Here we test these hypotheses, using an atmospheric general circulation model to perform a set of sensitivity experiments to examine the impact of both SST gradients and topography on the CLLJ. In one sensitivity experiment, we remove the meridional SST gradient over the Caribbean Sea and in the other, we flatten the mountains over NSA. Our results show that the SST gradient and topography have little or no impact on the jet intensity, vertical, and horizontal wind shears, contrary to previous works. However, our findings do not discount a possible one‐way coupling between the SST and the wind over the Caribbean Sea through friction force. We also examined an alternative approach based on barotropic instability to understand the CLLJ intensity, vertical, and horizontal wind shears. Our results show that the current hypothesis about the CLLJ must be reviewed in order to fully understand the atmospheric dynamics governing the Caribbean region.
Surface and upper air observations and MM5v3 simulations examined the structure and inland penetration of sea breeze (SB) along the Grande de Tárcoles river basin (GTRB), central Pacific, Costa Rica, for two different intensity regimes of the Caribbean Low-Level Jet (CLLJ). Data comprise the period of 1 July to 16 September 2004 from Ticosonde-North American Monsoon Experiment, and a local University of Costa Rica-National Meteorological Institute field campaign. Maximum precipitation occurs between 14:00–17:00 LST, showing a time lag of 2 to 3 h after the temperature maximum, suggesting that local diurnal heating is key to convection. July–August precipitation exhibited a rainfall decrease along GTRB due to the SB dynamical processes interaction with a strong CLLJ. The SB maximum inland incursion was 24 km, with no evidence of its penetration into the Central Valley. The MM5v3 simulations for two convective and boundary layer (BL) schemes captured some SB structure features along the GTRB. Comparison of model results with observed data shows deficiencies in the model representation of the surface flow near coastal regions. Differences may be the result of time lag model’s poor responses to actual early morning BL sea–land temperature gradients. MM5v3 configurations used in this study resulted in biased wind speed simulations.
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