An assessment of regional climate trends and changes to the Mt. Jaya glaciers of Irian Jaya

Over the past century, glaciers throughout the tropics have predominately retreated. These small glaciers, which respond quickly to climate changes, are becoming increasingly important in understanding glacier-climate interactions. The glaciers on Mt. Jaya in Irian Jaya, Indonesia are the last remaining tropical glaciers in the Western Pacific region. Although considerable research exists investigating the climatic factors most affecting tropical glacier mass balance, extensive research on the Mt. Jaya glaciers has been lacking since the early 1970s. Using IKONOS satellite images, the ice extents of the Mt. Jaya glaciers in 2000, 2002, 2003, 2004, and 2005 were mapped. The mapping indicates that the recessional trend which began in the mid-19th century has continued. Between 1972 (Allison, 1974; Allison and Peterson, 1976) and 2000, the glaciers lost approximately 67.6% of their area, representing a reduction in surface ice area from 7.2 km2 to 2.35 km2. From 2000 to 2005, the glaciers lost an additional 0.54 km2, representing approximately 24% of the 2000 area. Rates of ice loss, calculated from area measurements for the Mt. Jaya glaciers in 1942, 1972, 1987, and 2005, indicate that ice loss on Mt. Jaya has increased during each subsequent period. Preliminary modeling, using 600 hPa atmospheric temperature, specific humidity, wind speeds, surface precipitation, and radiation values, acquired from the NCEP Reanalysis dataset, indicates that the only climate variable having a statistically-significant change with a magnitude great enough to strongly affect ice loss on these glaciers was an increase in the mean monthly atmospheric temperature of 0.24ðC between 1972 and 1987. However, accelerated ice loss occurring from 1988-2005 without large observed changes in the weather variables indicates that a more complex explanation may be required. Small, though statistically-significant changes were found in regional precipitation, with precipitation decreasing from 1972-1987 and increasing from 1988-2005. While, individually, these changes were not of sufficient magnitude to have greatly affected ice loss on these glaciers, increased precipitation along with a rising freezing level may have resulted in a greater proportion of the glacier surface being affected by rain. This may account for the increased recession rate observed in the latter period

Quality in the GLIMS glacier database

Global Land Ice Measurements from Space (GLIMS) is an international initiative to map the world’s glaciers and to build a geospatial database of glacier vector outlines that is usable via the World Wide Web. The GLIMS initiative includes glaciologists at 82 institutions, organized into 27 Regional Centers (RCs), who analyze satellite imagery to map glaciers in their regions of expertise. The results are collected at the U.S. National Snow and Ice Data Center (NSIDC) and ingested into the GLIMS Glacier Database. A concern for users of the database is data quality. The process of classifying multispectral satellite data to extract vector outlines of glaciers has been automated to some degree, but there remain stages requiring human interpretation. To quantify the repeatability and precision of data provided by different RCs, we designed a method of comparative image analysis whereby analysts at the RCs and NSIDC derived glacier outlines from the same set of images, chosen to contain a variety of glacier types. We carried out four such experiments. The results were compiled, compared, and analyzed to quantify inter-RC analysis consistency. These comparisons have improved RCs’ ability to produce consistent data, and in addition show that in the lower reaches of a glacier, precision of glacier outlines is typically 3 to 4 pixels. Variability in the accumulation area and over parts of the glacier that are debris-covered tends to be higher. The ingest process includes quality control steps that must be passed before data are accepted into the database. These steps ensure that ingested data are well georeferenced and internally consistent. The GLACE experiments and ingest-time quality control steps have led to improved quality and consistency of GLIMS data. This chapter presents the GLACE experiments and the quality control steps incorporated into the data ingest process. More recent similar studies are referenced