The spatiotemporal variability of precipitation in regions of complex mountainous terrains constitutes one of the most challenging research topics of geosciences. This paper explores hourly precipitation data from a set of 25 stations spanning the period 1998 to 2005 within northwestern Colombia, in the Aburrá Valley and the neighboring San Nicolás plateau (75.16 • W−6 • N and 75.66 • W−6.6 • N) which accounts for a land area of ∼4,000 km 2. Our aim is to identify the main features of the diurnal cycle of precipitation over this complex terrain. We found that the average diurnal cycle of rainfall in the study region is bimodal at regional scale although it results from the superposition of two unimodal diurnal cycles shifting its phase throughout the seasons of the year. From October to April, average diurnal rainfall peaks in the afternoon hours (13:00-16:00 LST) but from May to September, the phase of the diurnal cycle changes to midnight hours (22:00-02:00 LST). Three low-level jets (LLJs), namely Caribbean, CHOCO, and the so-called Corriente de los Andes Orientales (CAO), are relevant to explain the seasonal shift of the diurnal cycle given their modulation of the seasonal variation of moisture sources and transport over this region. During June-July-August, moisture from afternoon evaporation processes at the bottom of the inter-Andean Magdalena Valley, located at the east of the study region, is transported by anabatic and easterly trade winds and contribute to explain the midnight and early morning peak. The life cycle of convective processes influences the orographic nature of rainfall distribution and timing in the region since deep convective cores are related with the afternoon peak, whereas wide convective cores with the early morning peak.

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In this study, we validate precipitation estimates remotely sensed by the Tropical Rainfall Measuring Mission (TRMM) at monthly and seasonal timescales, during the period 1998-2015, by calculating and analyzing diverse error metrics between the 3B43 V7 product and in situ measurements from 1,180 rain gauges over Colombia, of which at least 987 are fully independent of TRMM. We explore the existence of spatiotemporal patterns to assess the performance of 3B43 V7 over the five major natural regions of Colombia: Caribbean, Pacific, Andes, Orinoco and Amazon. The results show that 3B43 V7 product is able to capture the phase of the annual cycle of monthly mean precipitation, but the performance is not good for the amplitude, in particular over the Andes and Pacific regions owing to complex climatic and topographic conditions. In general, 3B43 V7 exhibits good performance in the low-lying and plain Amazon, Orinoco and Caribbean regions. Over the Andes region, characterized by complex topography, overestimation errors are identified [root mean squared error (RMSE) ≥83.59 mm•month −1 and relative bias (BIAS) ≥4.69%], whereas the extremely wet rainfall regime of the Pacific region is largely underestimated (RMSE ≥253.52 mm •month −1 and BIAS ≤−11.75%). These errors are greater during the wet seasons when the metrics reach worse scores than those reported in similar studies worldwide. Occurrence analyses showed that 3B43 V7 misses very frequent light rainfall events and less frequent but very heavy storms, which contribute to the overall underestimation (overestimation) observed over the Pacific (Andes) region. The error characteristics identified and quantified in this study confirm the well-documented limitations of remote precipitation sensing and constitute a warning about major challenges that complex climatic and physiographic features can impose on satellite rainfall missions.

Abstract:We present a simplified overview of land-atmosphere feedbacks at interannual timescales over tropical South America as structural sets of linkages among surface air temperature (T), specific humidity at 925 hPa (q 925 ), volumetric soil water content (Θ), precipitation (P), and evaporation (E), at monthly scale during 1979-2010. Applying a Maximum Covariance Analysis (MCA), we identify the modes of greatest interannual covariability in the datasets. Time series extracted from the MCAs were used to quantify linear and non-linear metrics at up to six-month lags to establish connections among variables. All sets of metrics were summarized as graphs (Graph Theory) grouped according to their highest ENSO-degree association. The core of ENSO-activated interactions is located in the Amazon River basin and in the Magdalena-Cauca River basin in Colombia. Within the identified multivariate structure, Θ enhances the interannual connectivity since it often exhibits two-way feedbacks with the whole set of variables. That is, Θ is a key variable in defining the spatiotemporal patterns of P and E at interannual time-scales. For both the simultaneous and lagged analysis, T activates non-linear associations with q 925 and Θ. Under the ENSO influence, T is a key variable to diagnose the dynamics of interannual feedbacks of the lower troposphere and soil interfaces over tropical South America. ENSO increases the interannual connectivity and memory of the feedback mechanisms.

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