Agriculture Reference
In-Depth Information
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humidity, and orography for computing daily estimates of accumulated
rainfall (Herman et al., 1997;
http://edcintl.cr.usgs.gov/adds/RFEPaper.
php).
Since January 1, 2001, the RFE version 2.0, which has been imple-
mented by National Oceanic and Atmospheric Administration's Climate
Prediction Center (Xie and Arkin, 1997) to replace RFE 1.0, has been used
by LEWS. RFE 2.0 uses additional techniques to better estimate precipita-
tion while continuing the use of cold cloud duration (derived from cloud
top temperature) and station rainfall data. The METEOSAT 7 geostation-
ary satellite is the primary satellite data source.
The LEWS system acquires rainfall data from
ftp.ncep.noaa.gov/pub/
cpc/fews/newalgo est/ site,
minimum temperature from
ftp.ncep.noaa.gov/
pub/cpc/fews/daily gdas avgs/tmin/ site,
and maximum temperature from
ftp.ncep.noaa.gov/pub/cpc/fews/daily gdas avgs/tmax/ site.
These data are
placed on the Web (
http://cnrit.tamu.edu.edu/rsg/rainfall/rainfall.cgi)
for
public use. These geo-referenced values of rainfall, minimum/maximum
temperature, and generated radiation data are linked to the PHYGROW
model to provide weather data to derive the model in the automated sys-
tem. Temperature provided is skin temperature, which is not the same
as the typical 2-m shaded thermometer data, reported by most standard
weather status, requiring modification of model equations to accommodate
this type of temperature measure. There is a need for biophysical modelers
to recognize the new emerging measures of temperature, wind, and humid-
ity from satellites and explore new algorithms to take advantages of these
geographically robust data.
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U
sing Meteorological Projections
Capturing near-real time weather data linked with automated biophysical
models provides an incremental stream of analysis to the decision-maker,
allowing the assessment of emerging trends. In the case of the LEWS pro-
gram, information is provided in a 10-day interval. This information in-
cludes deviation from long-term average of standing crops forage availabil-
ity to cattle, sheep, goats, camels, and donkeys, the percentile ranking of
that response, and the estimated amount of forage available for each target
herbivore. Examples of emerging trends in the state of livestock forage that
can be seen in the LEWS products are shown in figures 22.3 and 22.4.
Using strong shifts in percentile ranking of current standing crops rela-
tive to 30-year averages from generated weather data and changes in NDVI
satellite greenness data, it was possible to project forward 30-120 days
with a relatively high confidence, allowing decision-makers time to begin
planning for adjustments in livestock numbers or movements.
The LEWS program has recently developed a collaborative relationship
with the Drought Monitoring Center in Nairobi, Kenya to integrate the
quarterly Climate Outlook Forum (COF) 90-day projections of above, be-
low, and average rainfall conditions as well as the 10-day and 30-day pro-
jections. Each 10-day report projects 90 days forward using the 25, 50, and
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