Mekonnen Gebremichael

Evaluation of High-Resolution Satellite Precipitation Products over Very Complex Terrain in Ethiopia

Abstract This study focuses on the evaluation of 3-hourly, 0.25° × 0.25°, satellite-based precipitation products: the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT, the NOAA/Climate Prediction Center morphing technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). CMORPH is primarily microwave based, 3B42RT is primarily microwave based when microwave data are available and infrared based when microwave data are not available, and PERSIANN is primarily infrared based. The results show that 1) 3B42RT and CMORPH give similar rainfall fields (in terms of bias, spatial structure, elevation-dependent trend, and distribution function), which are different from PERSIANN rainfall fields; 2) PERSIANN does not show the elevation-dependent trend observed in rain gauge values, 3B42RT, and CMORPH; and 3) PERSIANN considerably underestimates rainfall in high-elevation areas.

Evaluation of High-Resolution Satellite Rainfall Products through Streamflow Simulation in a Hydrological Modeling of a Small Mountainous Watershed in Ethiopia

AbstractThis study focuses on evaluating four widely used global high-resolution satellite rainfall products [the Climate Prediction Center’s morphing technique (CMORPH) product, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) near-real-time product (3B42RT), the TMPA method post-real-time research version product (3B42), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) product] with a spatial resolution of 0.25° and temporal resolution of 3 h through their streamflow simulations in the Soil and Water Assessment Tool (SWAT) hydrologic model of a 299-km2 mountainous watershed in Ethiopia. Results show significant biases in the satellite rainfall estimates. The 3B42RT and CMORPH products perform better than the 3B42 and PERSIANN. The predictive ability of each of the satellite rainfall was examined using a SWAT model calibrated in two different approaches: with rain gauge rainfall as input, and with each...

Assessment of the Statistical Characterization of Small-Scale Rainfall Variability from Radar: Analysis of TRMM Ground Validation Datasets

Abstract The main objective of this study is to assess the ability of radar-derived rainfall products to characterize the small-scale spatial variability of rainfall. The authors use independent datasets from high-quality dense rain gauge networks employed during the Texas and Florida Underflights (TEFLUN-B) and Tropical Rainfall Measuring Mission component of the Large-Scale Biosphere–Atmosphere (TRMM-LBA) field experiments conducted by NASA in 1998 and 1999. A detailed comparison between gauge- and radar-derived spatial variability estimates is carried out by means of a correlation function, covariance, variogram, scaling characteristics, and variance reduction due to spatial averaging. Emphasis is given to the correlation function because it is involved in most of these statistics. The approach followed in the analysis addresses the problems associated with the traditional estimation methods and the recognized differences in the scales of observation. The performance of the radar-derived correlation fu...

Understanding the Scale Relationships of Uncertainty Propagation of Satellite Rainfall through a Distributed Hydrologic Model

The study presents a data-based numerical experiment performed to understand the scale relationships of the error propagation of satellite rainfall for flood evaluation applications in complex terrain basins. A satellite rainfall error model is devised to generate rainfall ensembles based on two satellite products with different retrieval accuracies and space‐time resolutions. The generated ensembles are propagated through a distributed physics-based hydrologic model to simulate the rainfall‐runoff processes at different basin scales. The resulted hydrographs are compared against the hydrograph obtained by using high-resolution radar rainfall as the ‘‘reference’’ rainfall input. The error propagation of rainfall to stream runoff is evaluated for a number of basin scales ranging between 100 and 1200 km 2 . The results from this study show that (i) use of satellite rainfall for flood simulation depends strongly on the scale of application (catchment area) and the satellite product resolution, (ii) different satellite products perform differently in terms of hydrologic error propagation, and (iii) the propagation of error depends on the basin size; for example, this study shows that small watersheds (,400 km 2 ) exhibit a higher ability in dampening the error from rainfall to runoff than larger-sized watersheds, although the actual error increases as drainage area decreases.

Error Uncertainty Analysis of GPCP Monthly Rainfall Products: A Data-Based Simulation Study

Abstract This paper focuses on estimating the error uncertainty of the monthly 2.5° × 2.5° rainfall products of the Global Precipitation Climatology Project (GPCP) using rain gauge observations. Two kinds of GPCP products are evaluated: the satellite-only (MS) product, and the satellite–gauge (SG) merged product. The error variance separation (EVS) method has been proposed previously as a means of estimating the error uncertainty of the GPCP products. In this paper, the accuracy of the EVS results is examined for a variety of gauge densities. Three validation sites—two in North Dakota and one in Thailand—all with a large number of rain gauges, were selected. The very high density of the selected sites justifies the assumption that the errors are negligible if all gauges are used. Monte Carlo simulation studies were performed to evaluate sampling uncertainty for selected rain gauge network densities. Results are presented in terms of EVS error uncertainty normalized by the true error uncertainty. These res...

Rainfall Variability over Mountainous and Adjacent Lake Areas: The Case of Lake Tana Basin at the Source of the Blue Nile River

Abstract The water resource of the Blue Nile River is of key regional importance to the northeastern African countries. However, little is known about the characteristics of the rainfall in the basin. In this paper, the authors presented the space–time variability of the rainfall in the vicinity of Lake Tana, which is the source of the Blue Nile River. The analysis was based on hourly rainfall data from a network of newly installed rain gauges, and cloud temperature indices from the Meteosat Second Generation (MSG–2) Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite sensor. The spatial and temporal patterns of rainfall were examined using not only statistical techniques such as exceedance probabilities, spatial correlation structure, harmonic analysis, and fractal analysis but also marginal statistics such as mean and standard deviation. In addition, a convective index was calculated from remote sensing images to infer the spatial and temporal patterns of rainfall. Heavy rainfall is frequen...

A Detailed Evaluation of GPCP 1° Daily Rainfall Estimates over the Mississippi River Basin

Abstract This study provides an intensive evaluation of the Global Precipitation Climatology Project (GPCP) 1° daily (1DD) rainfall products over the Mississippi River basin, which covers 435 1° latitude × 1° longitude grids for the period of January 1997–December 2000 using radar-based precipitation estimates. The authors’ evaluation criteria include unconditional continuous, conditional (quasi) continuous, and categorical statistics, and their analyses cover annual and seasonal time periods. The authors present spatial maps that reflect the results for the 1° grids and a summary of the results for three selected regions. They also develop a statistical framework that partitions the GPCP–radar difference statistics into GPCP error and radar error statistics. They further partition the GPCP error statistics into sampling error and retrieval error statistics and estimate the sampling error statistics using a data-based resampling experiment. Highlights of the results include the following: 1) the GPCP 1DD ...

Evaluation of CMORPH Precipitation Products at Fine Space–Time Scales

Abstract In this study, a comparison of the spatial patterns of high-resolution precipitation products obtained from the Climate Prediction Center’s morphing technique (CMORPH), which is a satellite-only product, and gauge-adjusted Next Generation Weather Radar (NEXRAD) rainfall observations is performed using a variety of statistical techniques for the Little Washita watershed region in Oklahoma for a 3-yr period. Results show that 1) the performance statistics of CMORPH show tremendous variability from one hour to the next, suggesting that the performance statistics are dynamic in time, and therefore each satellite rainfall product should be accompanied by an error product to make it more meaningful; 2) CMORPH is positively biased in summer and negatively biased in winter, consistent with the findings of previous studies; 3) CMORPH spatial fields tend to be smoother than NEXRAD output; 4) the errors are temporally correlated, in particular within the range from 1 to 6 accumulation hours, implying that a...

SENSITIVITY ANALYSIS OF THE SURFACE ENERGY BALANCE ALGORITHM FOR LAND (SEBAL)

New versions of evapotranspiration (ET) algorithms based on the Surface Energy Balance Algorithm for Land (SEBAL) are being published, each containing slightly different equations to calculate the energy balance. It is difficult to determine what impact changing one or more of the equations or coefficients in the series of equations of SEBAL has on the final calculation of ET. The objective of this article is to conduct a sensitivity analysis of ET estimates in SEBAL to identify the most sensitive variables and equations. A remote sensing ET model based on SEBAL was programmed and validated against eddy-covariance data. A sensitivity analysis was conducted for three contrasting land surface conditions: full, half, and sparse canopy cover in pecan orchards. Results were most sensitive to the selection (according to temperature) of the dry (~zero ET) reference pixel and to c (the estimated ratio of soil heat flux to net solar radiation). At all the three degrees of canopy cover, estimated ET changed by 40% to 270% (1 to 2 mm d-1) when either variable changed from its baseline value by ±50% of the permissible range. Estimated ET was also sensitive to the selection of the wet (full ET) reference pixel and to dT (aerodynamic difference of air and land temperatures). Changes in ET estimates were 47% to 72% (1.3 to 3.7 mm d-1) at both the full and half canopy areas under changes from baseline values equal to 50% of the permissible range for either variable. In addition, ET was sensitive to the roughness length in areas of half canopy cover (ET changed by 61% [1.5 mm d-1]) and to the value of the normalized difference vegetation index (NDVI) in areas of sparse canopy cover (ET changed by 118% [0.35 mm d-1]). Future research on ET algorithm improvement should focus on the above variables and relative equations. The selection of the wet- and dry-spots should be automated to avoid subjective errors from manual selection.

Evaluation Through Independent Measurements: Complex Terrain and Humid Tropical Region in Ethiopia

Evaluation of satellite rainfall products was conducted using ground-based daily rainfall measurements at 22 locations within a grid of 5×5 km collected during summer monsoon 2008 in a very complex terrain and humid tropical region in Ethiopia. Two high-resolution satellite rainfall products, namely, PERSIANN-CCS available at 1-h and 0.04° resolution, and CMORPH available at 30-min and 0.08° resolution. Both remotely-sensed products underestimated heavy events by about 50%, and so caution must be exercised when using CMORPH and PERSIANN-CCS as input for flood forecasting, as this could underestimate large flood events. The underestimation in monthly total rainfall was significant (32% for CMORPH, 49% for PERSIANN-CCS), and this error level needs to be acknowledged in applications that require monthly analyses. PERSIANN-CCS failed to detect half of the light events, and consistently those under 1.6 mm/day, indicating clearly that PERSIANN-CCS has difficulty detecting light rainfall events in complex terrain.