High-Resolution Monthly Rainfall Database for Ethiopia: Homogenization, Reconstruction, and Gridding

Tsidu, Gizaw Mengistu

doi:10.1175/jcli-d-12-00027.1

Cited by 82 publications

(48 citation statements)

References 57 publications

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“…In addition, we replicate the procedures above for the sparsely distributed stations over western China and the Tibetan Plateau. The PMTred algorithm and the QM adjustment have recently been used successfully to homogenize climatic time series (Aarnes et al, 2015;Tsidu, 2012;Dai et al, 2011;Siswanto et al, 2015;Wang and Wang, 2016;Zhou et al, 2017). As such, the significant breakpoints are detected and adjusted at a confidence level of 95 % at 1092 of the 2193 …”

Section: Methods Used To Homogenize the Observed Time Seriesmentioning

confidence: 99%

On the suitability of current atmospheric reanalyses for regional warming studies over China

Zhou

Wang

2018

Atmos. Chem. Phys.

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Abstract. Reanalyses are widely used because they add value to routine observations by generating physically or dynamically consistent and spatiotemporally complete atmospheric fields. Existing studies include extensive discussions of the temporal suitability of reanalyses in studies of global change. This study adds to this existing work by investigating the suitability of reanalyses in studies of regional climate change, in which land-atmosphere interactions play a comparatively important role. In this study, surface air temperatures (T a ) from 12 current reanalysis products are investigated; in particular, the spatial patterns of trends in T a are examined using homogenized measurements of T a made at ∼ 2200 meteorological stations in China from 1979 to 2010. The results show that ∼ 80 % of the mean differences in T a between the reanalyses and the in situ observations can be attributed to the differences in elevation between the stations and the model grids. Thus, the T a climatologies display good skill, and these findings rebut previous reports of biases in T a . However, the biases in theT a trends in the reanalyses diverge spatially (standard deviation = 0.15-0.30 • C decade −1 using 1 • × 1 • grid cells). The simulated biases in the trends in T a correlate well with those of precipitation frequency, surface incident solar radiation (R s ) and atmospheric downward longwave radiation (L d ) among the reanalyses (r = −0.83, 0.80 and 0.77; p < 0.1) when the spatial patterns of these variables are considered. The biases in the trends in T a over southern China (on the order of −0.07 • C decade −1 ) are caused by biases in the trends in R s , L d and precipitation frequency on the order of 0.10, −0.08 and −0.06 • C decade −1 , respectively. The biases in the trends in T a over northern China (on the order of −0.12 • C decade −1 ) result jointly from those in L d and precipitation frequency. Therefore, improving the simulation of precipitation frequency and R s helps to maximize the signal component corresponding to regional climate. In addition, the analysis of T a observations helps represent regional warming in ERA-Interim and JRA-55. Incorporating vegetation dynamics in reanalyses and the use of accurate aerosol information, as in the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), would lead to improvements in the modelling of regional warming. The use of the ensemble technique adopted in the twentieth-century atmospheric model ensemble ERA-20CM significantly narrows the uncertainties associated with regional warming in reanalyses (standard deviation = 0.15 • C decade −1 ).

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Section: Methods Used To Homogenize the Observed Time Seriesmentioning

confidence: 99%

On the suitability of current atmospheric reanalyses for regional warming studies over China

Zhou

Wang

2018

Atmos. Chem. Phys.

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“…However, Dinku et al (2008) have evaluated the spatio-temporal reliability of this data set over the complex highland regions of Ethiopia, and found strong agreement with their reference rain gauge data set. Similarly, Tsidu (2012) evaluated the spatio-temporal reliability of CRU and other gridded data sets using rainfall records of 233 gauge stations over Ethiopia for the , and found statistically significant correlations of 0.81-0.95 over central and northern Ethiopia, 0.66-0.80 over western and southeastern Ethiopia, and 0.52-0.65 over other parts of the country. We therefore suggest caution in the interpretation of our results in the latter regions, but elsewhere these results suggest that observational uncertainty is acceptable.…”

Section: Methodsmentioning

confidence: 99%

Teleconnections between Ethiopian rainfall variability and global SSTs: observations and methods for model evaluation

Degefu

Rowell

Bewket

2016

Meteorol Atmos Phys

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Rainfall variability in Ethiopia has significant effects on rainfed agriculture and hydropower, so understanding its association with slowly varying global sea surface temperatures (SSTs) is potentially important for prediction purposes. We provide an overview of the seasonality and spatial variability of these teleconnections across Ethiopia. A quasi-objective method is employed to define coherent seasons and regions of SST-rainfall teleconnections for Ethiopia. We identify three seasons (March-May, MAM; July-September, JAS; and OctoberNovember, ON), which are similar to those defined by climatological rainfall totals. We also identify three new regions (Central and western Ethiopia, CW-Ethiopia; Southern Ethiopia, S-Ethiopia; and Northeast Ethiopia, NE-Ethiopia) that are complementary to those previously defined here based on distinct SST-rainfall teleconnections that are useful when predicting interannual anomalies. JAS rainfall over CW-Ethiopia is negatively associated with SSTs over the equatorial east Pacific and Indian Ocean. New regional detail is added to that previously found for the whole of East Africa, in particular that ON rainfall over S-Ethiopia is positively associated with equatorial east Pacific SSTs and with the Indian Ocean Dipole (IOD). Also, SST-to-rainfall correlations for other season-regions, and specifically for MAM in all regions, are found to be negligible. The representation of these teleconnections in the HadGEM2 and HadGEM3-GA3.0 coupled climate models shows mixed skill. Both models poorly represent the statistically significant teleconnections, except that HadGEM2 and the low resolution (N96) version of Had-GEM3-GA3.0 better represent the association between the IOD and S-Ethiopian ON rainfall. Additionally, both models are able to represent the lack of SST-rainfall correlation in other seasons and other parts of Ethiopia.

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“…A full description of the EM algorithm can be found in McLachlan and Krishnan (1997). EM has been widely used in recent years for computation of missing rainfall data (Firat et al, 2010;Tsidu 2012;Alamgir et al, 2015).…”

Section: Study Areamentioning

confidence: 99%

“…Relative methods are more reliable and recommended as the test is conducted by correlating the test data series with the homogeneous data series of a neighboring station. On the other hand, when homogeneous data series is not available or if the correlation between test series and reference series suggest a weak association, absolute methods are preferred (Tayanç et al, 1998;Wijngaard et al, 2003;Tsidu, 2012). Therefore, the selection of absolute tests depends on the availability of homogeneous data series as well as information about climatic or topographic conditions of a region.…”

Section: Introductionmentioning

confidence: 99%

Absolute homogeneity assessment of precipitation time series in an arid region of Pakistan

Ahmed

Shahid

Ismail

et al. 2018

Atm

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RESUMENLas evaluaciones de homogeneidad se realizan por lo general mediante datos de precipitación total anual, que a menudo fallan en la detección de homogeneidad en la precipitación estacional. Más aún, es necesario valorar la homogeneidad utilizando varios métodos, ya que el desempeño del método para probar la homogeneidad depende de la distribución de los datos. Esto es particularmente importante en regiones áridas, donde la distribución de la precipitación anual y estacional a menudo no son normales. En este estudio se evaluó la homogeneidad de conjuntos de datos de precipitación mensual y anual de 14 estaciones meteorológicas ubicadas en la región árida de Paquistán, utilizando para ello las pruebas bayesiana, de Pettitt, de homogeneidad normal estándar (SNHT, por sus siglas en inglés), de desviación acumulativa, de proporcionalidad de von Neumann, de verosimilitud de proporciones de Worsley y t de Student a un nivel de confianza de 95%. Las series de precipitación se clasificaron en tres clases, a saber "útiles", "dudosas" y "sospechosas", con base en los resultados de diferentes pruebas de homogeneidad. Los resultados sugieren que las series de tiempo de precipitación para la mayoría de los meses en todas las estaciones son útiles. Las series de tiempo de precipitación resultan dudosas para junio en dos estaciones y para abril en una estación; también se sospecha que sean dudosas para noviembre en otra estación. Por otra parte, se encontró que las series anuales son útiles en 12 estaciones y sospechosas en otras dos. La comparación de diferentes pruebas de homogeneidad reveló que las pruebas SNHT y Worsley son más sensibles, en tanto que la prueba de desviación acumulativa es la menos sensible a los cambios en los datos de precipitación mensual. En el caso de la precipitación anual, se encontró que la prueba de von Neumann es más sensible en comparación con las otras. ABSTRACTHomogeneity evaluations are usually performed on the total annual precipitation data, which often fails to detect non-homogeneity in seasonal precipitation. Furthermore, it is required to assess homogeneity using multiple methods as the performance of homogeneity testing methods depend on the distribution of the data. This is particularly important for the arid region where distributions of seasonal and annual rainfall are often non-normal. The homogeneity of annual and monthly precipitation datasets of 14 meteorological stations located in the arid region of Pakistan was assessed in this study using the Pettitt's test, the standard normal homogeneity test (SNHT), the cumulative deviation test, the von Neumann's ratio test, the Bayesian test, the Worsley's likelihood ratio test, and Student's t-test at a 95% confidence level. The rainfall series were categorized into three classes, namely "useful", "doubtful" and "suspect" based on the results of different homogeneity tests. Results suggest that rainfall time series for most of the months in all the stations are

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High-Resolution Monthly Rainfall Database for Ethiopia: Homogenization, Reconstruction, and Gridding

Cited by 82 publications

References 57 publications

On the suitability of current atmospheric reanalyses for regional warming studies over China

On the suitability of current atmospheric reanalyses for regional warming studies over China

Teleconnections between Ethiopian rainfall variability and global SSTs: observations and methods for model evaluation

Absolute homogeneity assessment of precipitation time series in an arid region of Pakistan

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