A51B-01 09:30h
Early Results from the Mauna Loa Atmospheric Pressure Network
A network of ten atmospheric pressure/temperature/humidity data loggers was established on the windward slope of Mauna Loa volcano in March 2004. Seven of the instruments are located along the road from Hilo to the NOAA Mauna Loa Observatory between sea level and 3400 meters elevation at intervals of about 560 meters. The remaining three are at Keahole point (leeward sea level) and on neighboring Mauna Kea volcano (Hale Pohaku, 2830 meters and the summit, 4200 meters). These measurements will allow us to monitor the atmospheric pressure tide as a function of altitude in the marine boundary layer and lower free troposphere. Using Hilo radiosonde data, we will investigate how the tidal components are influenced by local abundances of water vapor, cloudiness, and precipitation. Results from the first four months of operation will be presented.
A51B-02 09:45h
Validations of the NCEP MSM Coupled With an Advanced LSM Over the Hawaiian Islands
The hydrostatic version of the Regional Spectral Model (RSM) with a 10-km resolution was implemented into the operational runstream for the state of Hawaii by the National Centers for Environmental Prediction (NCEP) in early 1997. From preliminary analyses and feedback from forecasters, it is apparent that the 10-km RSM forecasts show improvements over the Global Forecast System (GFS) runs. However, orographic effects and diurnal weather patterns are not well simulated by the RSM because the complex island terrain is not adequately resolved by the 10-km horizontal grid. Recently, the nonhydrostatic version of the RSM (referred to as the Mesoscale Spectral Model, MSM) was developed at NCEP. Preliminary applications of the MSM in Hawaii at high resolutions (< 3 km) show improvements over the 10-km RSM in simulating localized heavy rainfall and high wind events. Nevertheless, the MSM poorly resolves the diurnal cycles of temperature and wind within the boundary layer over the Hawaiian Islands due to the fact that the heterogeneous surface properties are not adequately represented by the MSM. In this work, the MSM has been coupled with an advanced Land Surface Model (LSM) with improved lower boundary conditions for three sub-regions of the state of Hawaii: the Hawaii-Maui-Molokai domain at a 3-km resolution, the Oahu domain at a 1.5-km resolution, and the Kauai domain at a 1.5-km resolution. Since April 2002, we have been conducting daily high-resolution (1.5 km), 48-h experimental forecasts for the Oahu domain using the coupled MSM/LSM with improved surface boundary conditions. Our results suggest that (a) over land with adequate representation of the terrain and surface properties, the coupled MSM/LSM shows improvements over the RSM and MSM in simulating 2-m temperature, 2-m dew point temperature and 10-m wind. In particular, the daytime cold bias and over-estimation of surface wind speed experienced by the RSM and MSM are largely removed by the coupled MSM/LSM; and (b) the high-resolution (< 3 km), coupled MSM/LSM demonstrates substantial improvements over the 10-km RSM in simulating localized heavy rainfall and high wind events over the Hawaiian Islands. Major model bias is that the MSM/LSM tends to over-estimate (under-estimate) precipitation on windward (lee) side of steep mountains.
http://www.soest.hawaii.edu/MET/Faculty/rsm
A51B-03 10:00h
Numerical Studies of the Mesoscale Precipitation Systems over Taiwan
The particular shape of the Central Mountain Range(CMR) over Taiwan is oriented in NNE-SSW direction with the maximum height over 3000m. Over this complicated topography, there are not only the passage of environment flow will be modified by CMR tremendously, but also severe local storm associated with local circulations will be initiated resulted from the differential heating and the terrain blocking ffects . It is also found that the rainfall distribution is concentrated on some special region and location in Taiwan.When northeastern monsoon prevailed , precipitation in the windward side of northeastern Taiwan was very significant. For example, the maximum of long-term monthly mean precipitation at I-Lan occurred in Autumn season. The percentage of monthly precipitation to annual precipitation rangeed from 11% to 17% during Autumn season. The maximum daily rainfall amount during this season can be over 300 mm at some station in northeastern Taiwan. The Mei-Yu is a climatic phenomenon found over southeaster China , Taiwan and Japan. It occurs during the transition period between the northeastly monsoon in the winter and the southwestly monsoon in summer. During this period ,a number of flash floods occurred in the island of Taiwan. In this study, the PSU/NCAR MM5was used to simulate the mesoscale weather and precipitation systems over Taiwan to investigate the orographic effects on the distribution and the characteristics of precipitation in Taiwan and the surrounding area. A Mei-Yu front passed over Taiwan during 7-8 June 1987. There were two types of precipitation system found during this passage. One of them is the prefrontal local convection, and the other is the frontal precipitation. Modeling studies showed that prefrontal convection is af first triggered on the slop of CMR by the local convergence formed by the environmental flow with the thermal induced circulation. The sensitivity tests also indicate that the land-sea breeze, latent heat release and the surface fluxes have influence effects on the generation on the mesoscale convection systems. As the shallow front penetrated to Taiwan, the local convergence was intensified due to the interaction between Mei-Yu front and the CMR.Deep convetion associated with front passage made heavy rainfall in the inland area of Taiwan. For the northeasterly monsoon precipitation, the heavy rain event occurred on 10-12 December ,1998 will be presented in this studies. It is found that the northeasterly flow was retarded by the CMR and the local convergence was generated in the windward slop. The upstream influence results from the flow blocking and spliting with the supplying moisture and the surface fluxes triggered the local convective. systems
A51B-04 10:15h
Climatology of the Trade Wind Inversion Over Hawaii
The trade-wind regime is a dominant influence on Hawaiian weather. Within that regime, the trade-wind inversion (TWI) is a common phenomenon which influences cloud development and island-scale circulation. This study explores the TWI climatology over Hawaii using soundings from Hilo and Lihue (00 & 12 Z). Hilo is located on the Big Island, the southeastern-most island in the chain, and Lihue is on Kauai, on the northwestern end of the chain. Days when the trade wind flow was interrupted or the winds became variable were excluded from the statistics. Our analysis shows that the trade-wind inversion is the highest during summer when the subtropical high is well developed and reaches the northern most position north of the island chain. The trade-wind inversion is the lowest during winter when the subtropical high retreats southeastward over the East Pacific with a ridge axis just north of the Hawaiian Islands. Hilo is several degrees southeast of Lihue, which causes Hilo soundings year-round to have a higher inversion base. Drought is often associated with El Nino winters in Hawaii with a negative Standard Precipitation Index (SPI). For a strong El Nino winter ('97-'98), the SPI at Hilo was -1.36. During this event, the TWI at Hilo has a lower base, a shallower inversion layer, and greater inversion strength as compared with long term winter TWI statistics for Hilo. These differences are related to a southward shift of the subtropical high over the eastern Pacific during the El Nino winter. SPI for Lihue was -0.63 during the winter of 97-98 and the TWI statistics were not significantly affected by this El Nino event. The TWI statistics for a few wet winters (SPI > 1) and dry winters (SPI < -1) were compiled at both Hilo and Lihue. For both sites, wet seasons have a higher TWI base, thicker and weaker inversion layer than climatology while dry seasons show an opposite signal.
A51B-05 10:30h
Forecasting C$_{n}^{2}$ and Seeing for Mauna Kea
Atmospheric turbulence is of primary concern to astronomers. Turbulence induces amplitude and phase fluctuations in electromagnetic waves propagating through the atmosphere, resulting in image degradation. The turbulent fluctuations of the atmospheric refractive index are described by the refractive index structure function, C$_{n}^{2}$. The maximum telescope resolution is defined by a parameter called seeing, which is the full width at half-maximum of a long-exposure stellar image at zenith. C$_{n}^{2}$ and seeing are commonly used by astronomers to describe the turbulent state of the atmosphere at the time of their observations. In this paper we investigate the possibility of predicting C$_{n}^{2}$ and seeing using forecast fields output from a mesoscale numerical weather prediction model (MM5). A parameterization scheme is employed to establish relationships between observable bulk properties of the atmosphere predicted by MM5 and the small-scale turbulence structure that contributes to C$_{n}^{2}$ and seeing. Preliminary results of predicted seeing and C$_{n}^{2}$ will be presented along with observations of seeing and C$_{n}^{2}$ collected at the summit of Mauna Kea by recently installed instrumentation.
A51B-06 10:45h
On the Relationship Between Lightning and Convective Rainfall Over the Pacific Ocean
The wave guide between the Ionosphere and the Earth's surface allows VLF emissions generated by lightning between 5 and 25 kHz (sferics) to propagate over very long distances. Long-range, VLF lightning detection offers accurate and continuous monitoring of convective storms over the data-sparse Pacific Ocean. Four new generation Pacnet (Pacific Lightning Detection Network) sensors have been installed on Unalaska, Kauai, island of Hawaii and Kwajalein. Enabling the Pacnet sensors improved the detection efficiency significantly over the central and northern Pacific Ocean compared to the existing International Long-Range Network. The storms over the Pacific are often beyond the range of weather radars and low orbiting satellites equipped with microwave radiometers provide only intermittent glimpses of convective precipitation. The distribution of moisture and latent heating in deep convective systems is critical for accurate initialization of forecast models. A promising application of Pacnet is to derive estimates of the rainfall rate from the lightning observations. In this study, the ratio of lightning to convective rainfall over the Pacific is investigated by comparing the number of lightning strokes measured by Pacnet with convective rainfall obtained from Aqua's and TRMM's microwave sensors for a variety of storm systems. Preliminary results hold promise that lightning data over the Pacific can be assimilated into numerical models as a proxy for latent heat release in deep convective clouds.