Assessment of Differences between Near-Surface Air and Soil Temperatures for Reliable Detection of High-Latitude Freeze and Thaw States

Near-surface air temperature and the underlying soil temperature are among the key components of the Earth’s surface energy budget, and they are important variables for the comprehensive assessment of global climate change. Better understanding of the difference in magnitude between these two variables over high-latitude regions is also crucial for accurate detections of freeze and thaw (FT) states. However, these differences are not usually considered and included in current remote sensing-based FT detection algorithms. In this study, the difference between near-surface air temperature at the 2-meter height and soil temperature at the 5-centimeter depth is assessed using ground-based observations that span a three-year period from 2013 to 2015. Results show noticeable differences between air and soil temperatures over temporal scales that range from diurnal to seasonal. The study also suggests that the ground-based upper layer soil temperature may be a better surrogate than the near-surface air temperature for the reliable detection of FT states at high-latitudes. Furthermore, the results from this study are particularly useful for better understanding the surface energy budget that ultimately drives the land surface processes that are embedded within weather and climate models

Observed Differences between Near-Surface Air and Skin Temperatures Using Satellite and Ground-based Data

Accurate estimates of long-term land surface temperature (Ts) and near-surface air temperature (Ta) at finer spatio-temporal resolutions are crucial for surface energy budget studies, for environmental applications, for land surface model data assimilation, and for climate change assessment and its associated impacts. The Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Aqua satellite provide a unique opportunity to estimate both temperatures twice daily at the global scale. In this study, differences between Ta and Ts were assessed locally over regions of North America from 2009 to 2013 using ground-based observations covering a wide range of geographical, topographical, and land cover types. The differences between Ta and Ts during non-precipitating conditions are generally 2–3 times larger than precipitating conditions. However, these differences show noticeable diurnal and seasonal variations. The differences between Ta and Ts were also investigated at the global scale using the AIRS estimates under clear-sky conditions for the period 2003–2015. The tropical regions showed about 5–20 °C warmer Ts than Ta during the day-time, whereas opposite characteristics (about 2–5 °C cooler Ts than Ta) are found over most parts of the globe during the night-time. Additionally, Ts estimates from the AIRS and the MODIS sensors were inter-compared. Although large-scale features of Ts were essentially similar for both sensors, considerable differences in magnitudes were observed (\u3e6 °C over mountainous regions). Finally, Ta and Ts estimates from the AIRS and MODIS sensors were validated against ground-based observations for the period of 2009–2013. The error characteristics notably varied with ground stations and no clear evidence of their dependency on land cover types or elevation was detected. However, the MODIS-derived Ts estimates generally showed larger biases and higher errors compared to the AIRS-derived estimates. The biases and errors increased steadily when the spatial resolution of the MODIS estimates changed from finer to coarser. These results suggest that representativeness error should be properly accounted for when validating satellite-based temperature estimates with point observations

Peer-Led Team Learning in Mathematics: An Effort to Address Diversity and Inclusion Through Learning and Leadership

The Peer-Led Team Learning (PLTL) model has shown to be an effective instructional method to support females, underrepresented minorities, and first-generation students in Science, Technology, Engineering, and Mathematics (STEM). The collaborative problem-solving setting, led by a peer leader, fosters learning that engages all the students. There are six critical components that are vital to the PLTL model: 1) The PLTL Workshop is integral to the course; 2) Faculty is actively involved; 3) Peer Leaders are well trained; 4) The PLTL Workshop modules are challenging; 5) PLTL workshops are allocated time and space; and 6) There is institutional support. City Tech has implemented the PLTL workshops in selected foundation mathematics courses over the past five years because of the dismal pass and withdrawal rates. Overall results have shown that females, underrepresented minorities, and first-generation college students who actively participated in the PLTL workshops have higher course grades and lower withdrawal rates. Students are also afforded the opportunity to participate in the PLTL Leadership program. Through the PLTL Leadership program, females, underrepresented minorities, and first-generation college students (107 peer leaders in total) who have successfully completing their STEM degrees, are either in the STEM workforce or pursuing advanced STEM degrees. The PLTL model supports students who are academically disadvantaged, and provides students with an opportunity to build their leadership skills and to create a pathway to graduate school

Observed differences between near-surface air and skin temperatures using satellite and ground-based data

Accurate estimates of long-term land surface temperature (T-s) and near-surface air temperature (T-a) at finer spatio-temporal resolutions are crucial for surface energy budget studies, for environmental applications, for land surface model data assimilation, and for climate change assessment and its associated impacts. The Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Aqua satellite provide a unique opportunity to estimate both temperatures twice daily at the global scale. In this study, differences between T-a and T-s were assessed locally over regions of North America from 2009 to 2013 using ground-based observations covering a wide range of geographical, topographical, and land cover types. The differences between T-a and T-s during non-precipitating conditions are generally 2-3 times larger than precipitating conditions. However, these differences show noticeable diurnal and seasonal variations. The differences between T-a and T-s were also investigated at the global scale using the AIRS estimates under clear-sky conditions for the period 2003-2015. The tropical regions showed about 5-20 degrees C warmer T-s than T-a during the day-time, whereas opposite characteristics (about 2-5 degrees C cooler T-s than T-a) are found over most parts of the globe during the night-time. Additionally, T-s estimates from the AIRS and the MODIS sensors were inter-compared. Although large-scale features of T-s were essentially similar for both sensors, considerable differences in magnitudes were observed (>6 degrees C over mountainous regions). Finally, T-a and T-s estimates from the AIRS and MODIS sensors were validated against ground-based observations for the period of 2009-2013. The error characteristics notably varied with ground stations and no clear evidence of their dependency on land cover types or elevation was detected. However, the MODIS-derived T-s estimates generally showed larger biases and higher errors compared to the AIRS-derived estimates. The biases and errors increased steadily when the spatial resolution of the MODIS estimates changed from finer to coarser. These results suggest that representativeness error should be properly accounted for when validating satellite-based temperature estimates with point observations