Observing Weather and Climate from the Ground Up A Nationwide Network of Networks (2009) / Chapter Skim
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2 Observations Supporting the Fundamental Infrastructure for Mesoscale Monitoring and Prediction
2 Observations Supporting the Fundamental Infrastructure for Mesoscale Monitoring and Prediction
Pages 23-41
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From page 23... ...
Given the heavy reliance of intermediate users on the raw observations and computer analyses and predictions, and the emphasis of the National Weather Service on the protection of life and property, this section focuses on observations required to support these functions. More specifically, it 23
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From page 24... ...
focus on the atmospheric boundary layer, but keep the deep troposphere in mind. Within this context, the hazardous weather events most important to detect, monitor, and predict are • flooding from a large-scale storm • Nor'easters • snowstorms and ice storms (For the above three items, precipitation type, intensity, and amount [in the case of snow and ice, liquid equivalent and accumulation on the ground]
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From page 25... ...
And, although some of the phenomena near the top of the list are large and persist for days, mesoscale features embedded within them, especially convective elements, cause most of the havoc. Observations useful in the context of this study are equally useful for monitoring phenomena that lie outside the time-space envelope considered FIGURE 2.1 Time and space scales associated with the "high-impact" weather 2-1.eps phenomena that are discussed in Appendix A and summarized here.
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From page 26... ...
In order to capture gravity waves, the observational net has to be fine enough to resolve the layer of static stability in which the waves move, most often at the tropopause or in the lower troposphere, and often within an inversion. This implies, roughly, a horizontal resolution of 5-10 km and a vertical resolution of 100 m, in temperature, moisture, and wind measurements.
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From page 27... ...
TABLE 2.1 Emphasizing observation requirements not currently met in the vicinity of listed phenomena that would improve definition of mesoscale structure and predictions out to 48 hours Resolution Parameters to Phenomenon Size Duration Observe ∆x ∆t ∆z Flooding from 300-2000 km 0.5-5.0 days Temperature 50 km 3h 200 m (up to 5 km MSL) large-scale storms Moisture Wind Precipitation Nor'easter 500-2000 km 0.5-4.0 days SST 10 km 12 h Temperature Moisture 50 km 3h 100 m (up to 12 km)
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From page 28... ...
Wind Soil moisture Spherics Flash floods 2-20 km 5 min-1 h Temperature Assess instability Moisture 50 km 1h 200 m (up to 12 km) Wind Characterize sub-cloud layer Soil moisture 20 km 15 min 100 m (up to 2 km AGL)
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From page 29... ...
100 km Wind Local variability Across wind 1 km 15 min 100 m (up to 15 km) Pressure- gradient 100-300 km 2-12 H Temperature 100 km 6h 500 m windstorms Moisture Wind Pressure Fire Weather 10-100 km 2 h to 5 days Temperature 1 km 15 min 100 m (up to 5 km)
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From page 30... ...
Wind Notes* : km / m kilometers / meters h / min / s hours / minutes / seconds ∆x / ∆t / ∆z horizontal resolution / temporal frequency / vertical resolution MSL / AGL above mean sea level / above ground level SST sea-surface temperature PBL planetary boundary layer *
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From page 31... ...
There are several reasons for this: (1) The planetary boundary layer, that part of the atmosphere most responsive to surface conditions and the diurnal cycle, is where many mesoscale phenomena have their roots.
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From page 32... ...
Office of Hydrology based on radar reflectivity measurements, rain gauge data, and sometimes satellite information; and model integration. Spin-up time is measured in months, yet the use of LDASs has led to a more complete characterization of soil moisture than could be obtained by the direct measurements alone and, collaterally, to somewhat improved forecasts of convective precipitation in summer.
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From page 33... ...
SPECIAL REQUIREMENTS FOR CLIMATE MONITORING To reiterate a point made in the introduction, climate, like weather, has mesoscale variability occasioned by topography and land/ocean surface conditions. That is why climate monitoring cannot be ignored in this discussion; it is one of multiple national applications supported by mesoscale observations.
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From page 34... ...
Conversely, the mesoscale observations indicate how larger-scale climate trends are experienced on the regional scale and modulated by characteristics of the lower boundary. The effects of climate change may well have high spatial variability.
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From page 35... ...
What we now view as core components of an operational weather monitoring network typically had their origin in the academic community and/or national research laboratories. Examples include but are not limited to Doppler radar, polarimetric radar, radio-acoustic sounding systems, wind profilers, eye-safe aerosol backscatter lidar, portable automated mesonet systems, use of geostationary satellites as primary data collection platforms, a data transfer system for dropwindsondes, and solid state sensors and digital electronic systems that enabled markedly improved performance of surface meteorological stations at the dawn of the digital electronics era.
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From page 36... ...
A more seamless blending of formal university education with observations, operational forecasting, and research will promote the capacity building required to satisfy personnel needs of the future. The developmental role carried out jointly by the scientific and research engineering communities is pivotal to successful implementation of a national mesoscale network.
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From page 37... ...
Because these fluxes influence the evolution of the boundary layer and ultimately the initiation of convection, their calculation must be improved. That will be difficult without more complete observations of soil moisture and temperature and vegetation fraction (Advanced VeryHigh-Resolution Radiometer [AVHRR]
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From page 38... ...
Research Example 3: Surface Heterogeneity and Its Impact on BoundaryLayer Structure and Convective Precipitation Although weather prediction has improved, the prediction of warm season convective precipitation has lagged behind. One of the suspected
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From page 39... ...
A good estimate of the horizontal variation of precipitation would be obtainable from network Doppler and polarimetric radars when assimilated with network precipitation gauge data. The unique contributions of a national mesoscale network would be long-term regional scale observations of soil moisture and temperature, profiles of winds and divergence fields, water vapor distribution, and gauge/ radar coverage of precipitation.
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From page 40... ...
The forecasting of chemical weather has become a new application area, providing important information to the public, decision makers, and researchers. National weather services throughout the world are broadening their traditional role of mesoscale weather prediction to also include prediction of other environmental phenomena (e.g., plumes from biomass burning, volcanic eruptions, dust storms, and urban air pollution)
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From page 41... ...
Preliminary studies at the UK Met Office have shown that soundings derived from the Atmospheric Infrared Sounder and the Infrared Atmospheric Sounding Interferometer, when inserted into computer prediction models, have had a greater impact on numerical predictions than the direct assimilation of radiance from those sensors, contrary to prevailing opinion. The reason may be that the radiance data are thinned both spatially and spectrally, whereas the derived soundings use all of the spectral information.
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