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We study phase-locking between the El Niño - Southern Oscillation (ENSO) and precipitation at inter-annual time scales over northern South America. To this end, we characterize the seasonality of the regional patterns of sea surface temperature, surface pressure levels, and precipitation anomalies associated with the states of the canonical ENSO. We find that the positive (negative) precipitation anomalies experienced in northern South America differ from those previously reported in the literature in some continental regions. In particular, the Orinoco Low-level Jet corridor separates two regions with negative (positive) rainfall anomalies during El Niño (La Niña), which are located in the Guianas (northeastern Amazon) and the Caribbean. Moreover, we show that the ENSO signal is phase-locked with the inter-annual rainfall variability in most of the study regions although some areas exhibit phase-locking without a significant change in the anomalies of precipitation. This suggests that ENSO could induce changes only in terms of phases and not so in terms of magnitude. This work provides new insights into the non-linear interactions between ENSO and hydro-climatic processes over the tropical Americas.

We studied the most active season of the Orinoco Low-Level jet (OLLJ), December-January-February (DJF), during the El Niño-Southern Oscillation canonical phases, El Niño and La Niña. In particular, we studied the occurrence days of the jet in each month, wind speed, moisture transport and precipitation over northern south America. In terms of the occurrence of the OLLJ, during El Niño in January, the jet exhibits its highest reduction with changes up to 24% in the eastern Colombian plains. On the contrary, during La Niña, the jet exhibits an increase between 6–16% in the frequency of occurrence mainly located in the eastern Colombian plains and the border between Colombia, Ecuador and Peru. Although the diurnal cycle of the OLLJ windspeed remains unaltered during the ENSO phases the maximum decrease (increase) up to -2m/s (up to 1 m/s) during El Niño (La Niña). Regarding moisture transport there is a gradual reduction during the season in both ENSO phases reaching up to 18 gm-1 kgm-1 during El Niño, and the precipitation also shows a reduction of around 5 mm/day. In conclusion, during DJF at the ENSO canonical phases the OLLJ shows changes in its occurrence along the jet corridor, and the region experiences changes in both moisture transport and precipitation.

We investigated the relationship between the frequency of occurrence of the Orinoco low-level jet (OLLJ) and hydroclimatic variables over northern South America. We use data from the ERA5 atmospheric reanalysis to characterize the spatial and temporal variability of the OLLJ in light of the low-level jet (LLJ) classification criteria available in the literature. An index for the frequency of occurrence of an LLJ was used, based on the hourly maxima of wind speed. The linkages among the OLLJ, water vapor flux, and precipitation were analyzed using a composite analysis. Our results show that during December–February (DJF), the OLLJ exhibits its maximum wind speed, with values around 8–10 m s−1. During DJF, the analysis shows how the OLLJ transports atmospheric moisture from the tropical North Atlantic Ocean. During this season, the predominant pathway of the OLLJ is associated with an area of moisture flux divergence located over northeastern South America. During June–August (JJA), an area of moisture flux convergence associated with the northernmost location of the ITCZ inhibits the entrance of moisture from northerlies. We also show that the occurrence of the OLLJ is associated with the so-called cross-equatorial flow. During DJF, the period of strongest activity of the OLLJ is associated with the northerly cross-equatorial flow and dry season, whereas during JJA the southerly cross-equatorial flow from the Amazon River basin predominates and contributes to the rainy season over the Orinoco region.

Resumen Con el fin de representar la precipitación y evaporación total mensual en una cuenca hidrográfica del Orinoco colombiano, este trabajo evaluó la capacidad de los modelos climáticos regionales incluidos en el Experimento regional coordinado de reducción de escala (CORDEX-CORE). Para ello, complementariamente, se incluyeron datos de precipitación y evaporación total de fuentes como Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS), el reanálisis atmosférico (ERA5), Global Precipitation Climatology Center (GPCC) y Global Land Evaporation Amsterdam Model (GLEAM). Las comparaciones entre los ensambles de los modelos y las observaciones se hicieron utilizando métodos gráficos y métodos cuantitativos, entre ellos: diagramas de cajas, porcentajes de sesgo, eficiencia de Nash-Sutcliffe, entre otros. Los resultados evidencian que los valores promedio de precipitación están adecuadamente representados, en términos de su temporalidad y magnitud, por el ensamble del modelo RegCM, mientras que los valores promedio de evaporación total están mejor representados por el ensamble del modelo REMO en términos de la temporalidad, más no en su magnitud. Por otra parte, las estimaciones de caudal de largo plazo evidencian que los valores de evaporación total proporcionados por los modelos permiten una adecuada estimación del caudal promedio de largo plazo, pero no la adecuada estimación del ciclo anual de caudales. Este trabajo es pionero en la evaluación de los datos de precipitación y evaporación total mensual suministrados por CORDEX-CORE en el Orinoco colombiano, sienta precedentes para la incorporación de datos de modelos regionales para fines hidrológicos en zonas poco instrumentadas del país, y es el primer paso hacia la evaluación de escenarios regionalizados de cambio climático. Abstract We evaluate the capacity of the Regional Climate Models, included in the regional scale reduction experiment (CORDEX-CORE), to represent the monthly precipitation and evaporation in a watershed of the Colombian Orinoco region. In addition, we use precipitation and evaporation data from sources such as Climate Hazards Center InfraRed Precipitation with Station data, ERA5 atmospheric reanalysis, Global Precipitation Climatology Center and Global Land Evaporation Amsterdam Model. The comparisons between the assemblies of the RCMs and the observations were done using graphical and quantitative methods, among them: box plots, percentages of bias, Nash-Sutcliffe efficiency, among others. Our results allow concluding that the average precipitation values are adequately represented, in terms of their temporality and magnitude, by the assembly of the RegCM model while the average values of total evaporation are better represented by the assembly of the REMO model in terms of temporality, but not in its magnitude. Furthermore, the long-term flow estimation shows that the total evaporation values provided by the RCMs allow an adequate estimation of the long-term average flow, but not the adequate estimation of the annual flow cycle. This work is a pioneer in the evaluation of the monthly precipitation and evaporation data provided by CORDEX-CORE in the Colombian Orinoco, sets precedents for the incorporation of regional models data for hydrological purposes in poorly instrumented areas of the country, and is the first step towards the evaluation of regional climate change scenarios.

We classified events of extreme Orinoco Low-Level Jet (OLLJ) activity using the ERA5 time series of daily winds at 925 hPa averaged over the 6°S–8°N/67°W–69°W area for the period 1981-2019. This area exhibits an overall mean of 3.7 m/s easterly wind speed and an overall standard deviation of 3.5 m/s. Then, during December-January-February (June-July-August), the season of strong (weak) OLLJ activity, we defined the events below (above) one standard deviation from the overall mean. Hence, days with easterly wind speeds higher than 7.2 m/s are considered events with strong activity during DJF. In contrast, days with westerly wind speed higher than 0.2 m/s are the events with weak activity during JJA. A composite analysis of precipitation from CHIRPS dataset during the days classified as strong or weak OLLJ activity showed that during the most active period (DJF), daily precipitation values are close to 0 mm/day; except for increased precipitation in the border between Colombia, Ecuador, Peru, and Brazil. In contrast, precipitation composites during the period of non-activity of the OLLJ (JJA), showed that precipitation increases in the range 5–10 mm/day along the OLLJ corridor. A detailed analysis of the precipitation time series used for composite analysis indicates that the probability of precipitation during DJF (JJA) is less (more) than 20% (80%) over Venezuela and the Guianas. In terms of advective water transport (qV) during the most active events of the OLLJ water is transported from the Tropical Atlantic towards northern South America through the OLLJ corridor, whilst during the less active events water transport along the OLLJ corridor comes from the north Amazon basin towards northern South America. In conclusion, during DJF the OLLJ is associated with the northerly cross-equatorial flow and dry season, whereas during JJA the southerly cross-equatorial flow from the Amazon river basin predominates, which contributes to the rainy season over the Orinoco region.

We investigate the behavior of the Shannon entropy, S ( T ) , and the time generalized q -entropy, S q ( T ) , at increasing aggregation intervals, T , using series of 15-min and hourly rainfall records in the tropical Andes of Colombia, spanning from 21 months to 40 years, as well as average daily streamflows in Colombia, the Amazon River basin, and USA, spanning from 34 to 69 years. Results for rainfall show that S ( T ) ∼ T β with β = 0.5 , valid up to a timescale 〈 T M a x E n t 〉 = 83 h, and β = 0 for T > T M a x E n t . Scaling exponents ( β = 0.5 ) are statistically independent of record length, although not so the values of T M a x E n t , owing to the greater amount of zeros in rainfall series during El Nino in Colombia. Maximum entropy is reached through a dynamic Generalized Pareto distribution, whose parameters are not statistically affected by record length. Entropy for daily streamflows behaves as S ( T ) ∼ T β with β ≳ 0 , consistently with the theoretical limit. The scaling behavior of entropy differs between rainfall and streamflows due to the presence of zeros in rainfall series, and by the rate at which they vanish upon temporal aggregation. The amount of zeros exhibit two different scaling regimes with T , separated at 〈 T b 〉 = 24 h. Rainfall series get devoid of zeros at 〈 T n o z 〉 = 164 h, but later on for longer record lengths. A power law relates both timescales: T M a x E n t ∼ T n o z 0.62 . Besides, S q ( T ) consists of a continuous set of power laws with respect to T , for increasing values of q , whose scaling exponents vary nonlinearly with q , thus implying multi-scaling of the time generalized q -entropy, which in turn inherits all the conclusions from the Shannon entropy, since it is recovered at S q = 1 ( T ) .

We study spatial scaling and complexity properties of Amazonian radar rainfall fields using the Beta-Lognormal Model (BL-Model) with the aim to characterize and model the process at a broad range of spatial scales. The Generalized Space q-Entropy Function (GSEF), an entropic measure defined as a continuous set of power laws covering a broad range of spatial scales, S q ( λ ) ∼ λ Ω ( q ), is used as a tool to check the ability of the BL-Model to represent observed 2-D radar rainfall fields. In addition, we evaluate the effect of the amount of zeros, the variability of rainfall intensity, the number of bins used to estimate the probability mass function, and the record length on the GSFE estimation. Our results show that: (i) the BL-Model adequately represents the scaling properties of the q-entropy, S q, for Amazonian rainfall fields across a range of spatial scales λ from 2 km to 64 km; (ii) the q-entropy in rainfall fields can be characterized by a non-additivity value, q s a t, at which rainfall reaches a maximum scaling exponent, Ω s a t; (iii) the maximum scaling exponent Ω s a t is directly related to the amount of zeros in rainfall fields and is not sensitive to either the number of bins to estimate the probability mass function or the variability of rainfall intensity; and (iv) for small-samples, the GSEF of rainfall fields may incur in considerable bias. Finally, for synthetic 2-D rainfall fields from the BL-Model, we look for a connection between intermittency using a metric based on generalized Hurst exponents, M ( q 1 , q 2 ), and the non-extensive order (q-order) of a system, Θ q, which relates to the GSEF. Our results do not exhibit evidence of such relationship.

We study diverse scaling and information theory characteristics of Mesoscale Convective Systems (MCSs) as seen by the Tropical Rainfall Measuring Mission (TRMM) over continental and oceanic regions of tropical South America, and 2-D radar rainfall fields from Amazonia. The bi-dimensional Fourier spectra of MCSs exhibit inverse power laws with respect to the spatial scale, whose scaling exponents, β, capture the type of spatial correlation of rainfall among the study regions, including those over the Andes of Colombia as well as over oceanic and Amazonian regions. The moment-scaling analysis evidences that the structure function deviates from simple scaling at order q > 1.0, thus signaling the multi-scaling nature of rainfall fields within MCSs in tropical South America, with departures from simple scaling associated with the physical characteristics of MCSs over the different study regions. Entropy is estimated for a large set of radar rainfall fields during the distinctive atmospheric regimes (Easterly and Westerly events) in this part of Amazonia. Results evidence that there are significant differences in the dynamics of rainfall among regimes. No clear-cut relationship is found between entropy and the first two statistical moments, but power fits in space and time, S(γ) ∼ γ(-η) for skewness and, S(κ) ∼ κ(-ϵ) for kurtosis. The exponents η and ϵ are statistically different between Easterly and Westerly events, although the significance of fits is less when L-moments are used to estimate skewness and kurtosis. Interesting differences are identified between the time and space generalized q-entropy functions of Amazonian rainfall fields. In both cases, the functions are a continuous set of power laws (analogous to the structure function in turbulence), S(T, q) ∼ T(β), and, S(λ, q) ∼ λ(β), covering a broad range of temporal and spatial scales. Both time and space generalized q-entropy functions exhibit linear growth in the range -1.0