Insights into the Hydrological Cycle via GPS RO and its future cousin, ATOMMS
Speaker: Rob Kursinski, Moog Advanced Missions & Science
When: Wednesday, April 2, 2014, 3:30 p.m. Mountain Time
Location: Room 2A305, DSRC (NOAA Building), 325 Broadway, Boulder
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Water vapor is fundamental to weather and climate. It is both a tracer and a driver of atmospheric circulation via its changes in phase which couple it tightly to clouds and precipitation, two other fundamental and difficult to predict variables. The water vapor feedback, perhaps the largest in the climate system, amplifies other feedbacks. Water is also critical to the strongly negative lapse rate feedback.
Improving our understanding of hydrological processes and their representation in models, as required to improve weather and climate forecasting, requires globally distributed, precise, accurate, and all-weather observations that capture the important scales of variation. While long known to contain significant and unique information about water vapor, GPS radio occultation (RO) profiles have yet to have significant impact on NWP moisture. We will discuss some ideas as to why this is so.
Histograms of humidity distributions provide a more stringent evaluation of hydrological realism than low order moments like mean & variance. Perhaps surprisingly, GPS RO histograms from the COSMIC GPS RO mission reveal higher percentages of extremely moist and dry air than AIRS, climate models and NWP moisture analyses. A diffusion-free, saturation-advection model yields still higher percentages of moisture extremes than those observed by GPS RO, suggesting that some diffusion is required to reproduce the observations, but less than that in GCMs.
GCMs that under-represent high relative humidity air while producing realistic clouds and precipitation, must utilize parameterizations that compensate for the unrealistic moisture distribution. Until NWP model and observational moisture climatologies match, data assimilation systems will have difficulty significantly improving moisture, cloud and precipitation forecasts.
We find CMIP5 climate models agree better with GPS RO than AR4/CMIP3 models, indicating improving model realism. While increasing resolution no doubt helps, other factors are important as well because NCEP analyses have comparably fine or finer resolution.
GPS RO reveals interesting water vapor pattern variations over the seasonal and ENSO cycles. A cluster analysis reveals significant ENSO-related signatures in GPS RO water vapor data not present in moisture analyses or GCMs. The COSMIC-observed water vapor variations over the recent ENSO cycles suggest that GCMs may be overestimating the water vapor feedback.
Given that GPS frequencies were chosen specifically to minimize their interaction with the atmosphere, an RO system using frequencies near the 22 and 183 GHz water vapor absorption lines would yield a significantly more powerful than GPS RO. We have developed a prototype instrument for such a next generation system called Active Temperature, Ozone and Moisture Microwave Spectrometer (ATOMMS) RO system which promises significant improvements beyond GNSS RO.
We will summarize expected areas of future impact and improvement including a brief summary of ATOMMS capabilities and applications.