IEEE Geoscience and Remote Sensing Magazine - June 2014 - 24
Making Satellite
Precipitation Data Work
for the Developing World
Abebe GebreGiorGis And FAisAl HossAin
Department of Civil and Environmental Engineering, University of Washington, Seattle, USA
Abstract-In an era of declining ground-based networks
for measurement of precipitation, satellite precipitation
data, that is now routinely available in increasing frequency
and spatial coverage, represents an interesting paradox.
Specifically, effective assessment frameworks and error
metrics for satellite precipitation data must be developed
for advancing the utility of satellite data for global applications. While there seems to be a concerted effort by the community to evaluate satellite precipitation data, there does
not seem to be similar efforts to resolve the paradoxical
issue of balancing the need for global uncertainty information and the stark lack of global GV datasets for doing so. In
this article, we present one practical approach to estimating
satellite precipitation uncertainty that is not dependent on
the notion of ground validation (GV) data. By using input
that is more readily available around the globe (i.e., satellite
data and geophysical features of terrain, climate and seasons), the approach can potentially advance applications as
it allows a coherent way to merge available satellite precipitation data products to a more superior state, particularly
for hydrologic applications. We provide an assessment of
how the approach works in various regions of the developing world as a way to encourage the community to further
the development of such ideas and provide end-users with
a practical decision-making tool.
1. IntroductIon
he traditional approach to measuring precipitation by
placing a probe on the ground will likely never be adequate or affordable in most parts of the world. Fortunately,
satellites today provide a continuous global bird's-eye view
(above ground) at any given location. Emerging high resolution and multi-sensor satellite-based precipitation estimates,
such as those anticipated from the Global Precipitation Measurement (GPM) [1], [2] satellites, now hold great promise,
especially over parts of the world where surface observation
T
Digital Object Identifier 10.1109/MGRS.2014.2317561
Date of publication: 24 June 2014
24
networks are sparse, declining or non-existent. Among
applications, most aspects of a hydrological study and its
findings have a clear benefit in terms of societal value.
Whether it is floods, droughts, climate change, ecosystem impacts, land use management or agriculture, the
importance of knowing the hydrological mechanisms for
better prediction, forecasting and decision making has always been obvious [3]. Thus, satellite precipitation data,
which is a key input to hydrologic models, is a benefactor of many hydrologic applications over regions where
it is already difficult to obtain data from conventional
ground networks. These regions are typically the developing world faced with challenging financial resources.
Hereafter, we shall interchangeably use the term 'rainfall'
with 'precipitation' to signify the same.
However, the usefulness of such precipitation products
for hydrological applications depends on their error characteristics and how intelligently we can harness the implications of uncertainty for surface hydrology [4]-[12]. The
need to take advantage of uncertainty represents a unique
paradox when it comes to making satellite precipitation
data 'work' for the developing world. On one hand, the
decline of the few existing global ground based measurement networks for precipitation means that ground validation data from in-situ measurements are mostly absent in
most parts of the world for estimating the uncertainty. On
the other hand, satellite precipitation data is most useful
where there exists little to none conventional measurements. As a result, the conventional method of comparing satellite estimate against in-situ records to 'harness'
the uncertainty is unrealistic and impractical [9], [12]. As
a community tasked with the job of making satellite precipitation 'work' for applications in most parts of the world,
there is now a need think outside the box [13]-[16].
2. tHE KEY HurdLE to MAKInG SAtELLItE
PrEcIPItAtIon dAtA WorK
Obviously the existing high resolution satellite rainfall
estimates have a significant role to play in filling this
2168-6831/14©2014IEEE ieee Geoscience and remote sensing magazine
june 2014
Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - June 2014
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