Karla Jay, Gay and Lesbian sexuality author

General note: Title and date provided by Bettye Lane.

Left to right: Jay Sah and Nilesh Timilsina measuring diameter at breast height in mangrove forests damaged by Hurricane Wilma, Harney River

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Jay Sah measuring tree height in a mangrove forest impacted by Hurricane Wilma, Harney River

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Jay Sah crossing tidal creek to measure tree damage by Hurricane Wilma, Harney River

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.

Implication of global warming on air-conditioned office buildings in Australia

With the accelerated trend of global warming, the thermal behavior of existing buildings, which were typically designed based on current weather data, may not be able to cope with the future climate. This paper quantifies, through computer simulations, the increased cooling loads imposed by potential global warming and probable indoor temperature increases due to possible undersized air-conditioning system. It is found from the sample office building examined that the existing buildings would generally be able to adapt to the increasing warmth of 2030 year Low and High scenarios projections and 2070 year Low scenario projection. However, for the 2070 year High scenario, the study indicates that the existing office buildings, in all capital cities except for Hobart, will suffer from overheating problems. When the annual average temperature increase exceeds 2°C, the risk of current office buildings subjected to overheating will be significantly increased. For existing buildings which are designed with current climate condition, it is shown that there is a nearly linear correlation between the increase of average external air temperature and the increase of building cooling load. For the new buildings, in which the possible global warming has been taken into account in the design, a 28-59% increase of cooling capacity under 2070 High scenario would be required to improve the building thermal comfort level to an acceptable standard.