KEYNOTE ADDRESS: Climate Change: From Global to New York Scale

This talk is concerned with the science and impacts of climate change from global to New York scales. It will provide an assessment of how the climate has changed over the past Century based on a purely observational perspective. The scientific basis for anthroprogenic climate change will be explained and discussed including a description of the “greenhouse effect” and why it is important for life on this planet. We will briefly discuss global and local consequences of a warmer climate and what we need to be prepared for going forward in the coming decades

Tropical Cyclone Diurnal Cycle Signals in a Hurricane Nature Run

The diurnal cycle of tropical convection and tropical cyclones (TCs) has been previously described in observational-, satellite-, and modeling-based studies. The main objective of this work is to expand on these earlier studies by identifying signals of the TC diurnal cycle (TCDC) in a hurricane nature run, characterize their evolution in time and space, and better understand the processes that cause them. Based on previous studies that identified optimal conditions for the TCDC, a select period of the hurricane nature run is examined when the simulated storm was intense, in a low shear environment, and sufficiently far from land. When analyses are constrained by these conditions, marked radially propagating diurnal signals in radiation, thermodynamics, winds, and precipitation that affect a deep layer of the troposphere become evident in the model. These propagating diurnal signals, or TC diurnal pulses, are a distinguishing characteristic of the TCDC and manifest as a surge in upper-level outflow with underlying radially propagating tropical squall-line-like features. The results of this work support previous studies that examined the TCDC using satellite data and have implications for numerical modeling of TCs and furthering our understanding of how the TCDC forms, evolves, and possibly impacts TC structure and intensity

Shallow Meridional Circulations in the Tropical Atmosphere

Abstract A shallow meridional circulation (SMC) in the tropical atmosphere features a low-level (e.g., 700 hPa) flow that is in the opposite direction to the boundary layer monsoon or trade wind flow and is distinct from the meridional flow above. Representations of the SMC in three global reanalyses show both similarities and astonishing discrepancies. While the SMC over West Africa appears to be the strongest, it also exists over the eastern Atlantic and eastern Pacific Oceans, and over the Indian subcontinent, with different strength and structure. All SMCs undergo marked seasonal cycles. The SMCs are summarized into two types: one associated with the marine ITCZ and the other with the summer monsoon. The large-scale conditions for these two types of SMCs are similar: a strong meridional gradient in surface pressure linked to surface temperature distributions and an absence of deep moist convection. The processes responsible for these conditions are different for the two types of SMCs, as are their structures relative to moist convection, associated precipitation, and deep meridional overturning circulations. It is suggested that discrepancies among the representations of the SMC in the three global reanalyses stem from different treatment of physical parameterizations, especially for cumulus convection, in the models used for the data assimilation

Quantitative Content Analysis Data for Hand Labeling Road Surface Conditions in New York State Department of Transportation Camera Images

Traffic camera images from the New York State Department of Transportation (511ny.org) are used to create a hand-labeled dataset of images classified into to one of six road surface conditions: 1) severe snow, 2) snow, 3) wet, 4) dry, 5) poor visibility, or 6) obstructed. Six labelers (authors Sutter, Wirz, Przybylo, Cains, Radford, and Evans) went through a series of four labeling trials where reliability across all six labelers were assessed using the Krippendorff’s alpha (KA) metric (Krippendorff, 2007). The online tool by Dr. Freelon (Freelon, 2013; Freelon, 2010) was used to calculate reliability metrics after each trial, and the group achieved inter-coder reliability with KA of 0.888 on the 4th trial. This process is known as quantitative content analysis, and three pieces of data used in this process are shared, including: 1) a PDF of the codebook which serves as a set of rules for labeling images, 2) images from each of the four labeling trials, including the use of New York State Mesonet weather observation data (Brotzge et al., 2020), and 3) an Excel spreadsheet including the calculated inter-coder reliability metrics and other summaries used to asses reliability after each trial. The broader purpose of this work is that the six human labelers, after achieving inter-coder reliability, can then label large sets of images independently, each contributing to the creation of larger labeled dataset used for training supervised machine learning models to predict road surface conditions from camera images. The xCITE lab (xCITE, 2023) is used to store camera images from 511ny.org, and the lab provides computing resources for training machine learning models