CGMS-41, NOAA-WP-13
Prepared by
M. Goldberg Agenda Item:
II/2
Discussed in WG-II
Summary of the Working Paper
Action 40.18: CGMS Agencies to support fast delivery initiatives using direct broadcast with extensions wherever possible (e.g., IASI, METOP-B, NPP), including on future polar orbiting satellites.
The volume and coverage of polar-orbiting satellite data available to NCEP’s operational data assimilation systems depends on both the number of occupied orbits (orbital configuration) and the data latency. Both factors are critical issues for determining the accuracy and timing of NCEP’s numerical guidance. Numerical guidance is foundational to all NOAA’s forecast and warning services and future
Weather Ready Nation objectives.
Data latency is critical for the use of satellite data in numerical weather prediction forecast models. The use of direct readout over the Northern Hemisphere can improve latency of sounder data to less than 30 minutes, and as low as 15 minutes.
Direct readout of both NPP and METOP sounder data can be realized at a low cost since most of the stations are already available. Current North American stations are located at universities, and include Madison, Wisconsin, Fairbanks, Alaska, and
Oahu, Hawaii. Additional stations are needed at Monterey, California; Miami,
Florida; San Juan; Puerto Rico, Guam, and Suitland MD (or Wallops). When combined with existing stations in Japan, China, Russia, and Europe, most of the
Northern Hemisphere can be covered with excellent latency.
Our NOAA initiative for SNPP and MeTOP includes working with EUMETSAT to combine all stations to a network, which will provide data access to NCEP and the
European NWP community. Today, such a concept exists with current NOAA
POES data and is called the Early Advanced Rapid Transmission Service (EARS).
NOAA will also work with the WMO.
NOAA welcomes the participation of other CGMS agencies. We would like to include FY3 and Russian satellites and would encourage open access to level 0 and level 1 processing code to convert satellite data packets to calibrated sensor observations.

CGMS-41, NOAA-WP-13
1 INTRODUCTION
The volume and coverage of polar-orbiting satellite data available to NCEP’s operational data assimilation systems depends on both the number of occupied orbits (orbital configuration) and the data latency. Both factors are critical issues for determining the accuracy and timing of NCEP’s numerical guidance. Numerical guidance is foundational to all NOAA’s forecast and warning services and future Weather Ready Nation objectives.
Data latency is critical for the use of satellite data in numerical weather prediction forecast models. The use of direct readout over the Northern Hemisphere can improve latency of sounder data to less than 30 minutes, and as low as 15 minutes. Direct readout of both NPP and METOP sounder data can be realized at a low cost since most of the stations are already available. Current North American stations are located at universities, and include Madison,
Wisconsin, Fairbanks, Alaska, and Oahu, Hawaii. Additional stations are needed at
Monterey, California; Miami, Florida; San Juan; Puerto Rico, Guam, and Suitland MD (or
Wallops). When combined with existing stations in Japan, China, Russia, and Europe, most of the Northern Hemisphere can be covered with excellent latency.
Our NOAA initiative fpr SNPP and MeTOP includes working with EUMETSAT to combine all stations to a network, which will provide data access to NCEP and the European NWP community. Today, such a concept exists with current NOAA POES data and is called the
Early Advanced Rapid Transmission Service (EARS). NOAA will also work with the WMO.
2.
Direct Broadcast Impacts on Data Latency for NCEP’s Forecast Systems.
NCEP’s atmospheric forecast systems are the Global Forecast System (GFS), the North
American Mesoscale (NAM) system, and the Rapid Refresh (RAP) system. Each system meets a unique forecast requirement with an appropriate resolution and forecast length 1 . Both the
NAM and RAP execute partially cycled data assimilations similar in principle to the GDAS, but they both connect to a GDAS analysis in a “catch-up” cycle at various times each day. In addition, each relies additionally on external boundary conditions from a prior GFS forecast.
The GDAS assimilation and GFS forecast quality, therefore, impacts NAM and RAP forecast quality. Current analysis times are every six hours for the GFS (00, 06, 12, 18 UTC), every three hours (00, 03, 06, etc) for the NAM, and hourly for the RAP.
NCEP executes a data analysis prior to each GFS model forecast. In addition, NCEP executes the global data assimilation system (GDAS) cycle four times daily (00, 06, 12, 18 UTC). The
GDAS cycle executes with a 6 hour data cutoff and produces a 9 hour forecast as a background field for both the subsequent GFS data analysis and the next GDAS cycled assimilation. Data latency impacts the real-time GFS analysis but generally does not impact the GDAS cycle since the latter is run with a longer (6 hour) data cut-off Since the purpose of the GFS analysis is to provide the best initial conditions for the subsequent forecast, however, data latency is still a prominent issue.
1 The GFS has a global domain at coarser resolution (27 km) than the NAM which has a regional domain at higher spatial resolution (12 km) and nests over CONUS, Alaska and Hawaii/Puerto Rico at 4, 6 and 3 km respectively. The RAP has similar spatial resolution and domain as the NAM but with more frequent temporal updates. Because of their increased spatial and more frequent temporal updates, regional models have a high potential for improving critically important near term (0-12 hour) predictions that are critical to the NWS weather warning and watch process.
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CGMS-41, NOAA-WP-13
Fig. 1 summarizes the timeline for observations ingest into the data assimilation. The relevant parameters are:

Acceptance window: time interval over which observation times are accepted by the data assimilation, centered on the analysis time;

Data cutoff: time after which no delivered observations are ingested into the data processing and analysis; and

Data latency: time delay between observation time and delivery time on the NCEP computer.
Figure 1 . Time line of real-time observations ingest and the data assimilation acceptance window. Observation times must be within the acceptance window (beginning at 21 UTC for the 00 UTC analysis); they must be delivered before the data cutoff. The delay between observation time and delivery time is the data latency (horizontal arrows). Candidate observations are light green “balloons”; accepted observations are dark green; rejected observations are red. The time interval for “new” data is from 00 UTC until the Data
Cutoff time.
The following table summarizes the data acceptance window width and data cutoff times for
NCEP’s atmospheric prediction systems. With a nominal maximum data latency of 80 minutes, as anticipated from the future JPSS polar-orbiting systems, the time parameters and percent of observations used in the analysis for the NAM, GFS and RAP are:
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140
90
80
60
45
30
15
CGMS-41, NOAA-WP-13
Forecast system GFS Analysis
Data cutoff
NAM
(minutes)
75
Data assimilation acceptance window (minutes)
180
Percent of observations used
47.2
GFS
RAP
165
26
360
60
73.6
5.0
Table 1. Data cutoff, acceptance window width, and percent of observations used assuming a nominal data latency of 80 minutes.
The GFS analysis uses the largest percentage of observations since it has a later data cutoff and a wider data assimilation acceptance window. Since the NAM regional system has a data cutoff time less than the nominal 80-minute maximum data latency and a narrower acceptance window, less than 50% of the satellite observations can influence the NAM. Only 5.0 percent of the observations can influence the RAP with a latency of 80 minutes.
Over the 2015-2017, and provided sufficient computing resources are available, NCEP will seek to reconfigure its data assimilation systems to improve service delivery and accuracy from the
GFS, NAM and RAP systems. This is a fundamental and critical strategic change to provide the
Weather Enterprise with earlier GFS guidance, to improve the regional systems with more timely
(concurrent) boundary conditions, and to gain the ability to generate combined GFS and NAM products. New NWS requirements on satellite data latency will derive from this change.
In order to execute this reconfiguration with a minimum loss of polar-orbiting data in the analysis, the data latency of polar-orbiting satellite date must decrease to maintain approximately the same amount of observations currently used in the GFS analysis. Studies investigating this reconfiguration are part of this proposal.
The following table shows the benefit of reduced data latency in providing increased observations to the analysis systems and increased new observations, assuming the current configuration of the NCEP Production Suite.
Latency
(min)
Percent obs. used
(NAM)
Percent new obs. (NAM)
Percent obs.
Used (GFS)
Percent new obs. (GFS)
Percent obs.
Used (RAP)
13.9
41.7
47.2
58.3
66.7
75.0
83.3
0
0
0
16.7
33.3
50
66.7
56.9
70.8
73.6
79.2
83.3
87.5
91.7
13.9
41.7
47.2
58.3
66.7
75.0
83.3
0
0
5.0
21.7
34.2
46.7
59.2
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CGMS-41, NOAA-WP-13
Table 2. Percent of available observations used by the NAM, GFS and RAP, and percent of new observations, for various latencies. Cutoff times are as in Table 1.
3.
Next Steps
NOAA has approved the development of a network of direct broadcast stationswhich will include Suomi NPP, METOP, EOS (AIRS), and POES (AMSU), and potentially GCOM and
FY3 series satellites. Below image shows the planned network.
NOAA welcomes the participation of other CGMS agencies. We would like to include FY3 and Russian satellites and would encourage open access to level 0 and level 1 processing code to convert satellite data packets to calibrated sensor observations.
Disclaimer
The manuscript contents are solely the opinions of the authors and do not constitute a statement of policy, decision, or position on behalf of NOAA or the U.S. government
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