Quantifying Water Cycle Variability in the Classroom Using
CREW GDS Data
Access water-cycle data from the homepage of Center for Research on
Environment and Water (CREW).
This webpage was created for SERC by Xia Feng in consultation with Paul Houser and Debbie
Belvedere of CREW.
The Dataset
Water-cycle data from the CREW homepage provides users the ability to access,
subset and analyze water cycle related data via the GrADS Data Server (GDS),
therefore easily manipulating and visualizing water cycle variation using the Grid
Analysis and Display System (GrADS).
Two commonly-used dataset will be briefly introduced for the creation of a water
cycle education module. The first dataset is the Global Precipitation Climatology
Project (GPCP) Version-2 monthly combined precipitation from satellite
measurements and surface rain gauge observations, extending from 1979 to
2005 with 2.5° latitude 2.5° longitude spatial resolution. The second dataset is
the National Centers for Environmental Prediction (NCEP)/Department of Energy
(DOE) Atmospheric Model Intercomparison Project (AMIP-II) reanalysis covering
the period 1979 to 2005. In particularly, it provides the surface water cycle
components, which overcome the inadequacy of sparsely distributed in situ
network, such as evaporation, runoff and soil moisture.
Use and Relevance
Earth is a unique, living planet due to the
abundance and vigorous cycling of water
throughout the global environment. The
cycling of water among three physical states
(solid, liquid and gas) not only drives the
atmospheric circulation but also provides
basic needs for human civilization. The need
for understanding the global water cycle has
provided a justification for wide ranging efforts
to quantify the variability of its components.
CREW’s large collection of water cycle datasets can be utilized to understand
water cycle variability on a broad range of spatial (global and regional) and
temporal scales (diurnal, seasonal and interannual), and the complicated ways
in which they interact. The CREW GDS data sever not only provides various
advanced water cycle datasets to research community but also to anyone else
interested in water cycle.
Use in Teaching
The datasets can be used in teaching the following topics and skills in
atmosphere science, meteorology, climate, and hydrology.
Teaching Topics
 Water cycle variation on multiple spatial and temporal scales.
 Anomalous dry and wet periods.
Teaching Skills
 Using data to make images of temporal changes of water cycle data.
 Using data to make spatial plots of water cycle data.
 Using linear regression to determine the trend of water cycle components.
 Interpreting water cycle variation from graphs.
Exploring the Data
Data Type and Presentation
GPCP and NCEP/DOE reanalysis have provided for the period 1979-2005. Data
are available in Binary format.
Accessing Data
Raw data can be accessed via the CREW GDS sever. The GDS versatile
capability allows users to remotely gain access to the desired dataset and subset
specified temporal and spatial subdomain without downloading a large dataset
for further analysis.
Manipulating Data and Creating Visualizations
Students can process the data to create graphs from raw data using GrADS.
Graphs can then be used to visualize water cycle data spatially and temporally
and to display the water cycle variation.
Tools for Data Manipulation
Users access the raw data provided from the CREW GDS sever and use GrADS
software to manipulate and visualize the dataset. A tutorial for using GrADS is
helpful to learn the basic features of GrADS.
About the Data
Collection Methods
GPCP incorporates precipitation estimates from low-orbit satellite microwave
data, geosynchronous-orbit satellite infrared data, and surface rain gauge
observations. The higher accuracy of the low-orbit microwave observations is
utilized to calibrate, or adjust, the more frequent geosynchronous infrared
observations. Then the combined satellite-based precipitation product is adjusted
to the measured rain gauge.
NCEP/DOE reanalysis aims to fix the known processing errors in NCEP/National
Center for Atmospheric Research (NCAR) with newer physics and observed soil
moisture forcing using an improved forecast model and updated data assimilation
system. When compared with NCEP/NCAR reanalysis, significant improvements
were made in NCEP/DOE reanalysis, such as land surface hydrology and landocean fluxes.
Limitations and Sources of Error
GPCP precipitation uncertainty is due to the algorithm and sampling error.
Reanalysis data are subject to the bias in uncertainty of model parameterization.
References and Resources
Scientific References that Describe these Datasets

The Version-2 Global Precipitation Climatology Project (GPCP) Monthly
Precipitation Analysis (1979-present): Research article illustrates the
features of GPCP precipitation (from Journal of Hydrometeorology).

NCEP-DEO AMIP-II Reanalysis (R-2): This research article presents
characteristics of reanalysis-2 dataset (from Bulletin of the American
Meteorological Society).
Other Related Scientific References

Contemporary Changes of the Hydrological Cycle over the Contiguous
United States: Trends Derived from In Situ Observations: A research
article describes the changes of water cycle components over the
contiguous United States during the twentieth century (from Journal of
Hydrometeorology).

Assessing a Satellite-Era Perspective of the Global Water Cycle: This
research article assesses the capability of a global data compilation to
depict the global water cycle’s mean state and variability.
Other Related Scientific Educational Resources


Introduction to the Atmosphere: Students will build a model to simulate
parts of the water cycle.
The Hydrological Cycle Online Meteorology Guide: Online module
illustrates the water cycle components.
Related Links


CREW resources provide information on global precipitation data
(including GPCP) and numerous links on water cycle educational
resources.
The NCEP/DOE reanalysis complete archive is available at NOAA/NCEP
website.