Since 1994, the NOAA Research-Forecast Systems Laboratory (NOAA /FSL) has been evaluating the utility of ground-based Global Positioning System (GPS) remote sensing techniques for operational weather forecasting, climate monitoring, atmospheric research, and other applications such as satellite calibration and validation. Techniques have been developed to acquire, process, distribute GPS integrated precipitable water vapor (IPW) retrievals and ancillary surface meteorological observations every 30-minutes with less than 15 minute latency. Techniques to assimilate these observations into the research version of the Rapid Update Cycle (RUC) numerical weather prediction assimilation/model system running hourly at NOAA /FSL have been developed, and the impacts of these observations on shortrange weather forecast accuracy have been evaluated since 1998 using a 60-km version of the system. These assessments consist of data denial experiments (parallel runs with and without GPS water vapor observations) to determine the impact that GPS-derived integrated (or total column) precipitable water vapor (IPW) retrievals have on short-range moisture and precipitation forecasts. The experiments have been conducted over a portion of the central United States that, from a meteorological perspective, is one of the best-observed areas on Earth. While this greatly facilitates the impact assessments, it also presents a special challenge to a new observing system under evaluation, such as GPS-Met, since relatively few measurements have to ''compete'' with an enormous number of other (conventional and nonconventional) observations of similar and related parameters. Despite this, five years of experiments inCorresponding author: Seth I. Gutman, Chief, GPS-Met Observing Systems Branch, NOAA Forecast Systems Laboratory, 325 Broadway R/FS3, Boulder CO 80305-3328, USA E-mail: Seth.I.Gutman@noaa.gov ( 2004, Meteorological Society of Japan dicate more or less continuous improvements in 3-hour relative humidity forecasts at pressure levels below 500 hPa. The greatest skill is seen during the cold season when moisture changes are dominated by synoptic-scale weather systems. Perhaps the most significant result is that the impact in improved forecast skill from assimilation of GPS-IPW data has increased each year as the number of stations has increased, suggesting that further increases in the network density over the United States will result in further forecast improvement.

[1] In the tropics, understanding the shallow-to-deep transition and organization of convection on the mesoscale is made difficult due the paucity of long-term high spatial/temporal resolution data. In this paper, data from the world's first long-term equatorial Global Navigational Satellite System meteorological station in Manaus (Central Amazon) is used to create a new metric, a water vapor convergence time scale, to characterize the temporal evolution of deep convection over a tropical continental region. From 3.5 years of data, 320 convective events were analyzed using a compositing analysis. Results reveal two characteristic time scales of water vapor convergence; an 8 h time scale of weak convergence and 4 h timescale of intense water vapor convergence associated with the shallow-to-deep convection transition. The 4 h shallow-to-deep transition time scale is particularly robust, regardless of convective intensity, seasonality, or nocturnal versus daytime convection. This new result provides a useful metric for both high resolution and global climate models to replicate.

Table Mountain Facility in California (TMF). The main objectives of the campaign were to (1) validate the water vapor measurements of several instruments, including, three Raman lidars, two microwave radiometers, two Fourier-Transform spectrometers, and two GPS receivers (column water), (2) cover water vapor measurements from the ground to the mesopause without gaps, and (3) study upper tropospheric humidity variability at timescales varying from a few minutes to several days.Correspondence to: T. Leblanc (leblanc@tmf.jpl.nasa.gov) A total of 58 radiosondes and 20 Frost-Point hygrometer sondes were launched. Two types of radiosondes were used during the campaign. Non negligible differences in the readings between the two radiosonde types used (Vaisala RS92 and InterMet iMet-1) made a small, but measurable impact on the derivation of water vapor mixing ratio by the FrostPoint hygrometers. As observed in previous campaigns, the RS92 humidity measurements remained within 5 % of the Frost-point in the lower and mid-troposphere, but were too dry in the upper troposphere.Over 270 h of water vapor measurements from three Raman lidars (JPL and GSFC) were compared to RS92, CFH, and NOAA-FPH. The JPL lidar profiles reached 20 km when integrated all night, and 15 km when integrated for 1 h. Excellent agreement between this lidar and the frost-point hygrometers was found throughout the measurement range, Published by Copernicus Publications on behalf of the European Geosciences Union. T. Leblanc et al.: MOHAVE-2009: overview of campaign operations and resultswith only a 3 % (0.3 ppmv) mean wet bias for the lidar in the upper troposphere and lower stratosphere (UTLS). The other two lidars provided satisfactory results in the lower and midtroposphere (2-5 % wet bias over the range 3-10 km), but suffered from contamination by fluorescence (wet bias ranging from 5 to 50 % between 10 km and 15 km), preventing their use as an independent measurement in the UTLS.The comparison between all available stratospheric sounders allowed to identify only the largest biases, in particular a 10 % dry bias of the Water Vapor Millimeterwave Spectrometer compared to the Aura-Microwave Limb Sounder. No other large, or at least statistically significant, biases could be observed.Total Precipitable Water (TPW) measurements from six different co-located instruments were available. Several retrieval groups provided their own TPW retrievals, resulting in the comparison of 10 different datasets. Agreement within 7 % (0.7 mm) was found between all datasets. Such good agreement illustrates the maturity of these measurements and raises confidence levels for their use as an alternate or complementary source of calibration for the Raman lidars.Tropospheric and stratospheric ozone and temperature measurements were also available during the campaign. The water vapor and ozone lidar measurements, together with the advected potential vorticity results from the high-resolution transport model MIMOSA, allowed the identification and study of a deep stratospheri...

The complex interactions between water vapor fields and deep atmospheric convection remain one of the outstanding problems in tropical meteorology. The lack of high spatial–temporal resolution, all-weather observations in the tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. Global Navigation Satellite System (GNSS) meteorology, which provides all-weather, high-frequency (5 min), precipitable water vapor estimates, can help. The Amazon Dense GNSS Meteorological Network experiment, the first of its kind in the tropics, was created with the aim of examining water vapor and deep convection relationships at the mesoscale. This innovative, Brazilian-led international experiment consisted of two mesoscale (100 km × 100 km) networks: 1) a 1-yr (April 2011–April 2012) campaign (20 GNSS meteorological sites) in and around Manaus and 2) a 6-week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, the latter in collaboration with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) Project in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor associated with sea-breeze convection in Belem and seasonal and topographic influences in and around Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor in high-resolution models. These experiments also demonstrate that GNSS meteorology can expand into logistically difficult regions such as the Amazon. Other GNSS meteorology networks presently being constructed in the tropics are summarized.