Spatio-temporal analysis of rainfall is crucial for water-resource management including water supply, risk management, sustainable agriculture and hydrological infrastructure. These aspects must be addressed and discussed before promulgating public policies in order to achieve the best climate-adapted development. Over South America, at continental scale, the rainfall distributions and related processes, such as moisture sources and transport, atmospheric circulation over oceans and continents, and the Andes range forcing, are fairly well-documented [1
]. At regional scale, the Ecuadorian Pacific slope and coast (EPSC) is an area of particular interest due to its physiographic features (surface, altitudinal range and the considerable horizontal distance from the coastal border to the watershed division on the high Andes) because they have a strong impact on the spatial variability of rainfall. In addition, the El Niño-Southern Oscillation (ENSO) is commonly identified as the main driver of temporal rainfall variability along the Ecuadorian coastal region and how the influence of this is different on the Andes [5
High-rainfall events over the EPSC, generally associated with El Niño events, are responsible for increases in runoff that cause major floods over Ecuador and Peru. The results of a 35-year simulation of rivers’ runoff over the Pacific Slope and coast of South America (PSCSA) showed that 15% of the total PSCSA runoff comes from the EPSC [6
] making it one of the main runoff surfaces over the PSCSA. By comparison, the Peruvian Pacific slope produces 17% of the PSCSA runoff over the area that is six times the area of the EPSC [6
]. This highlights the importance of conducting more detailed climatological and hydrological studies over the whole EPSC and also in its two largest basins (the Guayas and Esmeraldas basins) considering different types of ENSO events in terms of strength and seasonality.
The rainfall distribution and anomalous heavy rainfall in the coastal area of Ecuador are known to be related to the strong positive Sea-Surface Temperature Anomalies (SSTA) in the El Niño 1 + 2 region (N1 + 2) located between 0–10° S/80–90° W [7
]. The spreading of atmospheric instability in the N1 + 2 Pacific region to the eastern escarpment of the Andes could be a result of the temporary eastward shift of the Walker circulation [8
]. Moreover, over the Andes, the rainfall patterns are driven by the influence of both the Pacific Ocean and the Amazon basin [8
] and the combinations of regional and local atmospheric processes which interact with the topography [5
]. Currently, various datasets are available to study different aspects of the Ecuadorian climate, such as the spatio-temporal rainfall patterns over this region. These datasets include the best rainfall estimates from gauge analyses such as the best-estimate precipitation rate with multiple independent precipitation estimates of the Tropical Rainfall Measuring Mission (TRMM) sensors and rain-gauge analysis (TRMM 3B43 monthly Version 7 product) or called TRMM Multi-Satellite Precipitation Analysis (TMPA/3B43) [12
] that later we will name only TRMM.
A few studies have investigated the rainfall patterns over Ecuadorian areas [9
], but they do not examine in detail the entire EPSC surface. One of the objectives of this study is to better understand rainfall behavior over the EPSC. A critical step to achieving this goal consists in identifying the best regionally available dataset (e.g., based on synoptic observations from in situ networks, model reanalyzes, or derived from remote sensing) to represent the rainfall patterns over the EPSC. Consequently, this identified dataset will provide a more realistic framework to advance further hydro-climatic studies. Of course, in situ observations, that pass a quality-control process, constitute the most valuable source of information for climate studies. However, post-processing of satellite information contribute to enhancing the products that are only based on in situ observations, particularly on areas where it is too difficult to install a weather station. Over South America, TRMM products were used for regional analyses of rainfall variability already tested, e.g., the Peruvian [15
] and Central Andes [18
], Brazil [19
], Andean–Amazon River Basins [20
] or the Amazon Basin [22
]. Therefore, this study aims to test whether TRMM information represents the climatological conditions of the EPSC obtained from in situ observations better than the other three datasets (Global Precipitation Climatology Centre (GPCC), Climatic Research Unit–University of East Anglia (CRU), and ERA-Interim Reanalysis). To determine which global dataset provides the better results, a monthly 5-km resolution product was generated from the rain gauge network that covers the entire EPSC region. This product served as reference for the comparison with the four other datasets.
This study is organized as follows: the details of the study area are presented in Section 2
, whilst Section 3
presents the data. First, the quality-control process applied to the information of all available rain gauges in Ecuadorian territory that are maintained by the Meteorological and Hydrological National Institute of Ecuador (INAMHI); second, the process to generate the 5-km gridded rainfall dataset applying the cokriging method (COK) to the rain-gauge data; and last, a brief overview of the other rainfall products. Section 4
presents methods for comparing the different products based on statistical metrics, principal component analysis (PCA), and an analysis of selected El Niño rainfall events corresponding to different types and amplitudes. Section 5
is dedicated to the summary of the results. Section 6
presents the discussion. Finally, Section 7
presents the conclusions of this work.
2. Study Area
Ecuador is located in north-western South America, between Colombia and Peru, between 81.03° W–75.16° W, 1.48° N–5.04° S. Ecuador extends from the Pacific coast in the west to the Amazon plain in the east. Following a north–south direction, the Andes range crosses the entire Ecuadorian territory. Along this section, the Andes are divided in two main chains, the western and eastern ranges. These two quasi-parallel lines form an inter-Andean zone characterized by several valleys where many human settlements are found, including the capital of Ecuador, Quito. The highest watershed altitude divides the territory into two large drainage surfaces, with main flow directions towards the Pacific Ocean and the Amazon basin respectively (Figure 1
). Over the western Andes slopes, rainfall is produced from moist air coming from the Pacific Ocean, whilst over the western Andes the moisture comes from the Amazon basin and the Atlantic Ocean. The eastern side, through the trade winds, generally receive more moist air than the western slope [5
]. In addition, the inter-Andean valleys are influenced by both the oceanic and continental air masses [5
], the prevailing easterly moisture flow extends across the mountains depending on the speed of trade winds, especially in the south (around 3° S), where the mountain chain is generally lower [10
Our study area, the EPSC, is delimited to the west by the Pacific Ocean and to the east by the Andes watershed division. From west to east, the EPSC can be divided into the coastal region, the low-altitude coastal cordillera (extending from 1° N to 2° S, with a maximum altitude of 860 m.a.s.l.), an inland low valley, the western flanks of the Andes, the western high Andes ranges until they reach the tropical glaciers, and finally an inter-Andean region in the north (Figure 1
). The EPSC covers an area of ~116,436 km2
and represents about 47% of Ecuadorian territory with a total wide range of altitudes varying from 0 to 5870 m.a.s.l. from the coastal border to the higher Andes summits. Due to the complex topography of the study area, 74 basins are delimited according to level five of the Pfafstetter methodology [24
]. The Esmeraldas and Guayas basins are the largest of the EPSC, covering 19,680 km2
and 32,300 km2
respectively, together representing 44.6% of the EPSC surface.
The singular rainfall distribution of the EPSC is related to the two relevant mountains chains. The coastal border is characterized by low rainfall (<600 mm/year); the rainfall amount increases over the low coastal cordillera; and eastwardly, between this chain and the start of the Andes foothills, rainfall amounts reach the maximum of the region (>2000 mm/year). Then, to the east, rainfall decreases with altitude towards the high Andes (~400 to 1200 mm) [25
]. Over the entire region, large rainfall variability is associated with the influence of the Pacific Ocean warming during extreme El Niño events [7
], which induce extensive floods that can become devastating during the extreme El Niño years [26
] over the lowlands.
Our work presents a detailed rainfall distribution for the EPSC, which shows a significant correlation with orographic features. The high amount of climatology rainfall is concentrated in the north at the western windward side of the Andes and in the low coastal cordillera due to the intense low-level convergence when the ITCZ is placed on the north of the equator (almost in line with the oceanic ITCZ) in austral winter [4
]. The mountain slopes exposed perpendicularly to frequent winds that transport moisture [11
] can produce this highest amount of rainfall. This could also be supported by a larger cloud frequency observed in the north (~0) than the south (~4 S) [61
]. The spatial rainfall distribution over the EPSC is clearly delimited by its two mountain chains, which act as weather divisions, mainly the Andes, as the major borderline between Pacific and Amazonian climatic influences. These two chains have permanent interactions with tropospheric flow, which is more remarkable during the rainy season due the ITCZ seasonal migration and the interannual ENSO influence periodicity (ranging from 2 to 7 years [62
]). The particular case of the coastal border, where the rainfall amount is minimum, can be related to the influence of the SE Pacific anticyclone and the cold water upwelling of the Humboldt Current in austral winter [61
]. As for the temporary rainfall distribution over the EPSC, the first rainfall seasons starts in November–December when the ITCZ begins its southern displacement, then a second marked season, due to the direct influence of the ITCZ on convective processes, starts in Jan–May reaching a maximum in March. A third season with lower (minimum) rainfall occurs during Jul–Sep due to the northward shift of the ITCZ, during the northern hemisphere summer, and the intensified Walker circulation that produces advective low cloud [63
The largest interannual variability within the EPSC region is mostly produced by the ENSO conditions and influenced by the seasonal meridional migration of the ITCZ. This relationship is supported by the fact that the ITCZ migration is delayed (favored) during warm (cool) ENSO phases [64
] because the ITCZ generally migrates toward a differentially warming hemisphere [65
]. The spatial component of the second EOF mode is consistent with the higher cloud frequency during the ITCZ meridional migration over the EPSC and, therefore, closely related to the ENSO events represented by the first EOF mode. The spatial component of the first EOF specifically reveals the zonal rainfall variability influence of El Niño events, which is highest over the lowlands, specifically higher over the center south (Guayas basin), low over the Andes slope, and very low over the Andes. This was clear, for example, during the extreme 1998 El Niño, with a high rainfall variability impact towards the center-south according to the spatial rainfall variability presented by the first EOF mode and the event rainfall accumulation over the Esmeraldas and Guayas basins. The higher rainfall variability for the Guayas basin (center-south region) than for the Esmeraldas basin (north region) can be accounted for by evidence of historic strong and extreme El Niño events, which clearly separate the moist northern Ecuadorian coast, under the normal influence of the ITCZ, from the south coast of Ecuador, which is the driest region and sensitive to ENSO events [66
]. It should be noted that the ITCZ shift during warm ENSO episodes reduces rainfall by about 100 mm/year along the northern edge of the normal ITCZ over the eastern Pacific [67
], mostly in December–February (DJF) and March–May (MAM). It is equally important to mention that the western and central Pacific ITCZ shifts southward by about 2° S on typical ENSO conditions, and by about 5° S during strong El Niño events (such as in 1983 and 1998) [65
] with the longitudinal ITCZ structure modified by ENSO’s zonal rearrangement of convection [67
Although the monthly global datasets as GPCC and CRU obtained by interpolating global gauges’ observations allow for fairly good rainfall data for the study region, TRMM 3B34 V7 is the better source among all the datasets considered in this study. TRMM showed good agreement with gauge data compared with GPCC and CRU, and it showed to be superior to the global atmospheric reanalysis of ERA-Interim. Nevertheless, TRMM presents some overestimations over lowlands (mean Rbias of 7%) and has more underestimations over the Andes (mean Rbias of −28%) when compared with in situ gauges. For the El Niño rainfall events, TRMM presents mostly underestimations for the considered El Niño events. This could be explained because the TRMM dataset is the result of the combination of multiple independent precipitation estimates from the TRMM microwave imager (TMI), visible and infrared scanner (VIRS), rain gauge data and the precipitation radar (PR). PR underestimates rainfall rate for extremely intense convective rainfall [68
], especially for extreme precipitating systems that contain significant mixed phase and/or frozen hydrometeors [69
], as on the Andes. There is also the limitation of the VIRS data that provide information of cloud-top height, which do not correlate well enough with ground precipitation [70
]. Different cloud types may have similar cloud-top temperatures and are associated with different amounts of rainfall at the ground [71
]; for higher convective cloud there are normally underestimations compared to low-level short convection [72
]. Finally, the TMI also missed the light and heavy rainfall because of its small scale (swath width of 758.5 km) [73
] and/or type of rainfall according to its nature as, for example, the warm rain (derived from non ice-phase processes in clouds) [74
]. As shown by [61
], over Ecuadorian territory the average cloud-top height increases from west to east during the wet season (December–May), which means W–E rainfall cloud-top height increases; thus, this results in important underestimation over the Andes against a reasonably small overestimation over lowlands. It could also suggest that during the lower rainfall season (July–September), as shown in [75
], TRMM overestimations over the dry areas could be attributed to sub-cloud evaporation.
Comparison of the gridded observations with the commonly used rainfall datasets from GPCC, CRU, ERA-Interim reanalysis, and the satellite estimates from TRMM 3B43, showed that the satellite-based rainfall product provides the more reliable estimates. Overall, considering the 1998–2015 period, there is a good agreement between observations and TRMM with an average lowest RMSE of 68.7 mm/year and Rbias of −2.8% for the entire EPSC. We can note that, for the lowlands, the Rbias obtained (7%) are closer (small overestimation) to the observations than for the Andes (−28%) (underestimation). These results can be related to the uncertainties associated with the TRMM 3B43 algorithm and the errors from the different sensors onboard the satellite (TMI, PR and VIRS) which are responsible for underestimations of the rainfall during the wet season (December–May) when top-cloud heights increase from W–E of the EPSC over the Andes slopes and inter-Andean basin.
Very similar spatial and temporal patterns were found, especially for the first mode (Crr = 0.91 and 0.95 and RSME = 55 mm and 0.07 mm), when applying the PCA to deseasonalized anomalies of rainfall from TRMM 3B43 and in situ gridded observations over the EPSC between 1998 and 2015. For the spatial component, some differences can be observed in terms of rainfall variability amplitude and structures form over the Andes foothills (lower for TRMM) and over the lowlands (higher for TRMM). The first temporal component is dominated by the signature of the ENSO events, especially the extreme event of 1998. The first PCA spatial mode clearly shows the location of heavy rainfall impact of El Niño events and their zonal rainfall variability influence, which is highest over the lowland and lower towards the Andes.
The TRMM 3B43 product showed a generally good capability for providing realistic rainfall estimates during extreme El Niño 1998 (mean Rbias of +7.7%), and moderate El Niño of 2002–2003 (mean Rbias of −2.4%) over the EPSC. Nevertheless, rainfall for the El Niño 2007–2008 and 2009–2010 events were underestimated by TRMM (mean Rbias of −11% and −17.1%) over the EPSC and more notably underestimated for the 2009–2010 event for the Esmeraldas (−23.7%) than the Guayas basin (−18.9%). General good agreement was also found over the Esmeraldas basin for the extreme El Niño 1998 (mean Rbias 6.3%) and over the Guayas basins for the extreme 1998 and moderate 2002–2003 El Niño events (mean Rbias of +8.5%, +5.3%) in spite of small overestimations. All these results confirm that TRMM 3B43 V7 reports reasonable levels of heavy rainfall detection over the EPSC and specifically towards the center-south of the EPSC (Guayas basin) but presents a general underestimation for the moderate and weak El Niño events. Over the whole EPSC, the seasonal features and quantity are relatively well estimated by TRMM and the long-term climatology patterns are well represented. The present study validates the use of remotely sensed rainfall data in regions with sparse rain-gauge stations and high rainfall variability, taking into account the potentialities and limitations of satellite estimates.