Recent Trends and Future Predictions until 2060 of Urban Warming in Four Israeli Cities Employing the RegCM Climate Model

During periods of global warming (GW), expected increases in urban temperatures can have adverse impacts on city climate and thermal discomfort due to combined urban and global warming effects. The different climates in four cities in Israel are studied for the purpose of differentiating global vs. urban warming. Trends in urban and nearby rural areas were compared in order to estimate the urbanization effect on the local climate zones. Daily 06:00 and 15:00 Local Time (LT) temperatures for July 1980-2014 were investigated. The linear relationship between the urban warming and population growth observed in present climate data is assumed to continue into the near future. The Regional Climate Model (RegCM) temperature trends into the 21st century are assumed to represent primarily the GW because of the relatively coarse grid interval of 25 km. Hence, this study first differentiates between global and local warming past trends, and then uses this past result to make future projections that consider both factors. A unique feature of this study is the large climatic variety over Israel—a small country that encompasses no less than 5 different K?ppen climatic zones. The urban minus rural temperature (1980-2014) changes, ΔTu-r, show more intense warming in the afternoon in all 4 cities. For instance, in Jerusalem and Eilat, the ΔTu-r has increased by ~1.2°C. Following the RegCM predictions, by 2060 with “No population growth”, this temperature increase is expected to continue, by 1.114°C and 1.119°C, respectively. If, however, these cities grow rapidly, air temperature will increase by 2.937°C - 4.129°C and 2.778°C - 3.939°C, respectively.

Removing Moisture Effect on Soil Reflectance Properties: A Case Study of Clay Content Prediction

Visible, near-infrared and shortwave-infrared(VNIR-SWIR) spectroscopy is an efficient approach for predicting soil properties because it reduces the time and cost of analyses. However, its advantages are hampered by the presence of soil moisture, which masks the major spectral absorptions of the soil and distorts the overall spectral shape. Hence, developing a procedure that skips the drying process for soil properties assessment directly from wet soil samples could save invaluable time. The goal of this study was twofold:proposing two approaches, partial least squares(PLS) and nearest neighbor spectral correction(NNSC), for dry spectral prediction and utilizing those spectra to demonstrate the ability to predict soil clay content. For these purposes, we measured 830 samples taken from eight common soil types in Israel that were sampled at 66 different locations. The dry spectrum accuracy was measured using the spectral angle mapper(SAM) and the average sum of deviations squared(ASDS), which resulted in low prediction errors of less than 8% and 14%, respectively. Later, our hypothesis was tested using the predicted dry soil spectra to predict the clay content, which resulted in R^2 of 0.69 and 0.58 in the PLS and NNSC methods, respectively. Finally, our results were compared to those obtained by external parameter orthogonalization(EPO) and direct standardization(DS). This study demonstrates the ability to evaluate the dry spectral fingerprint of a wet soil sample, which can be utilized in various pedological aspects such as soil monitoring, soil classification,and soil properties assessment.