Liu, M., Lin, J., Wang, Y., Sun, Y., Zheng, B., Shao, J., et al. (2018). Spatiotemporal variability of NO2 and PM2.5 over Eastern China: observational and model analyses with a novel statistical method. Atmos. Chem. Phys. , 18 (17), 12933–12952.
Abstract: Eastern China (27-41 degrees N, 110-123 degrees E) is heavily polluted by nitrogen dioxide (NO2), particulate matter with aerodynamic diameter below 2.5 mu m (PM2.5), and other air pollutants. These pollutants vary on a variety of temporal and spatial scales, with many temporal scales that are nonperiodic and nonstationary, challenging proper quantitative characterization and visualization. This study uses a newly compiled EOF-EEMD analysis visualization package to evaluate the spatiotemporal variability of ground-level NO2, PM2.5, and their associations with meteorological processes over Eastern China in fall-winter 2013. Applying the package to observed hourly pollutant data reveals a primary spatial pattern representing Eastern China synchronous variation in time, which is dominated by diurnal variability with a much weaker day-to-day signal. A secondary spatial mode, representing north-south opposing changes in time with no constant period, is characterized by wind-related dilution or a buildup of pollutants from one day to another.
Liu, Q., Tan, Z. - M., Sun, J., Hou, Y., Fu, C., & Wu, Z. (2020). Changing rapid weather variability increases influenza epidemic risk in a warming climate. Environmental Research Letters , 15 (4).
Abstract: The continuing change of the Earth's climate is believed to affect the influenza viral activity and transmission in the coming decades. However, a consensus of the severity of the risk of influenza epidemic in a warming climate has not been reached. It was previously reported that the warmer winter can reduce influenza epidemic-caused mortality, but this relation cannot explain the deadly influenza epidemic in many countries over northern mid-latitudes in the winter of 2017-2018, one of the warmest winters in recent decades. Here we reveal that the widely spread 2017-2018 influenza epidemic can be attributed to the abnormally strong rapid weather variability. We demonstrate, from historical data, that the large rapid weather variability in autumn can precondition the deadly influenza epidemic in the subsequent months in highly populated northern mid-latitudes; and the influenza epidemic season of 2017-2018 was a typical case. We further show that climate model projections reach a consensus that the rapid weather variability in autumn will continue to strengthen in some regions of northern mid-latitudes in a warming climate, implying that the risk of influenza epidemic may increase 20% to 50% in some highly populated regions in later 21st century.
Liu, Y., Tan, Z. - M., & Wu, Z. (2019). Noninstantaneous Wave-CISK for the Interaction between Convective Heating and Low-Level Moisture Convergence in the Tropics. J. Atmos. Sci. , 76 (7), 2083–2101.
Abstract: The interaction between tropical convective heating and thermally forced circulation is investigated using a global dry primitive-equation model with the parameterization of wave-conditional instability of the second kind (CISK). It is demonstrated that deep convective heating can hardly sustain itself through the moisture convergence at low levels regardless of the fraction of immediate consumption of converged moisture. In contrast, when the fraction is large, shallow convective heating and its forced circulation exhibit preferred growth of small scales. As the “CISK catastrophe” mainly comes from the instantaneous characters of moisture-convection feedback in the conventional wave-CISK, a noninstantaneous wave-CISK is proposed, which highlights the accumulation-consumption (AC) time scale for the convective heating accumulation and/or the converged moisture consumption. In the new wave-CISK, once moisture is converged, the release of latent heat takes place gradually within an AC time scale. In this sense, convective heating is not only related to the instantaneous moisture convergence at the current time, but also to that which occurred in the past period of the AC time scale. The noninstantaneous wave-CISK could guarantee the occurrence of convective heating and/or moisture convergence at larger scales, and then favor the growth of long waves, and thus solve the problem of CISK catastrophe. With the new wave-CISK and AC time scale of 2 days, the simulated convective heating-driven system bears a large similarity to that of the observed convectively coupled Kelvin wave.
Luecke, C. A., Arbic, B. K., Bassette, S. L., Richman, J. G., Shriver, J. F., Alford, M. H., et al. (2017). The Global Mesoscale Eddy Available Potential Energy Field in Models and Observations: GLOBAL LOW-FREQUENCY EDDY APE. J. Geophys. Res. Oceans , 122 (11), 9126–9143.
Abstract: Global maps of the mesoscale eddy available potential energy (EAPE) field at a depth of 500 m are created using potential density anomalies in a high‐resolution 1/12.5° global ocean model. Maps made from both a free‐running simulation and a data‐assimilative reanalysis of the HYbrid Coordinate Ocean Model (HYCOM) are compared with maps made by other researchers from density anomalies in Argo profiles. The HYCOM and Argo maps display similar features, especially in the dominance of western boundary currents. The reanalysis maps match the Argo maps more closely, demonstrating the added value of data assimilation. Global averages of the simulation, reanalysis, and Argo EAPE all agree to within about 10%. The model and Argo EAPE fields are compared to EAPE computed from temperature anomalies in a data set of “moored historical observations” (MHO) in conjunction with buoyancy frequencies computed from a global climatology. The MHO data set allows for an estimate of the EAPE in high‐frequency motions that is aliased into the Argo EAPE values. At MHO locations, 15–32% of the EAPE in the Argo estimates is due to aliased motions having periods of 10 days or less. Spatial averages of EAPE in HYCOM, Argo, and MHO data agree to within 50% at MHO locations, with both model estimates lying within error bars observations. Analysis of the EAPE field in an idealized model, in conjunction with published theory, suggests that much of the scatter seen in comparisons of different EAPE estimates is to be expected given the chaotic, unpredictable nature of mesoscale eddies.
Magar, V., Godínez, V. M., Gross, M. S., López-Mariscal, M., Bermúdez-Romero, A., Candela, J., et al. (2020). In-stream Energy by Tidal and Wind-driven Currents: An Analysis for the Gulf of California.
Maksimova, E. V. (2018). A conceptual view on inertial internal waves in relation to the subinertial flow on the central west Florida shelf. Sci Rep , 8 (1), 15952.
Abstract: The study reported here focuses on inertial internal wave currents on the west Florida midshelf in 50 m depth. In situ observations showed that the seasonal shifts in stratification change both the frequency range of inertial internal waves and their modulation time scales. According to the analysis, the subinertial flow evolution time scales also undergo compatible seasonal variations, and the inertial internal wave currents appear to be temporally and spatially related to the subinertial flow. Specifically, the subinertial flow evolving on frontal-/quasi-geostrophic time scales appears to be accompanied by the near-inertial oscillations/inertia-gravity waves in corresponding small/finite Burger number regimes, respectively. The quasi-geostrophic subinertial currents on the west Florida shelf are probably associated with the synoptic wind-forced flow, whereas the frontal-geostrophic currents are related to the evolution of density fronts. Further details of this conceptual view should, however, be elucidated in the future.
Maloney, E. D., Gettelman, A., Ming, Y., Neelin, J. D., Barrie, D., Mariotti, A., et al. (2019). Process-Oriented Evaluation of Climate and Weather Forecasting Models. Bull. Amer. Meteor. Soc. , 100 (9), 1665–1686.
Abstract: Realistic climate and weather prediction models are necessary to produce confidence in projections of future climate over many decades and predictions for days to seasons. These models must be physically justified and validated for multiple weather and climate processes. A key opportunity to accelerate model improvement is greater incorporation of process-oriented diagnostics (PODs) into standard packages that can be applied during the model development process, allowing the application of diagnostics to be repeatable across multiple model versions and used as a benchmark for model improvement. A POD characterizes a specific physical process or emergent behavior that is related to the ability to simulate an observed phenomenon. This paper describes the outcomes of activities by the Model Diagnostics Task Force (MDTF) under the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP) program to promote development of PODs and their application to climate and weather prediction models. MDTF and modeling center perspectives on the need for expanded process-oriented diagnosis of models are presented. Multiple PODs developed by the MDTF are summarized, and an open-source software framework developed by the MDTF to aid application of PODs to centers' model development is presented in the context of other relevant community activities. The paper closes by discussing paths forward for the MDTF effort and for community process-oriented diagnosis.
Mende, M., & Misra, V. (2020). Time to Flatten the Curves on COVID-19 and Climate Change. Marketing Can Help. Journal of Public Policy & Marketing , .
Abstract: The health, economic, and social impact of the COVID-19 pandemic is unprecedented in our lifetime, and no individual in this globalized, interconnected world is immune from its effects. This pandemic is a fundamental challenge for consumers, companies, and governments. Against this background, our commentary underscores linkages between public health, environment, and economy and explores how lessons from COVID-19 can help prevent other large-scale disasters.1 We focus on global climate change (GCC), because rising temperatures increase the likelihood of future pandemics.2 Accordingly, experts consider GCC “the largest public health threat of the century” (Wyns 2020). Although societal crises are underresearched in marketing, we propose that marketers should add their expertise to help avoid future crises. Notably, the Journal of Public Policy & Marketing (JPP&M) is uniquely positioned as a premier outlet for corresponding research at the intersection of marketing and policy.
Misra, V., & Bhardwaj, A. (2019). Defining the Northeast Monsoon of India. Mon. Wea. Rev. , 147 (3), 791–807.
Abstract: This study introduces an objective definition for onset and demise of the Northeast Indian Monsoon (NEM). The definition is based on the land surface temperature analysis over the Indian subcontinent. It is diagnosed from the inflection points in the daily anomaly cumulative curve of the area-averaged surface temperature over the provinces of Andhra Pradesh, Rayalseema, and Tamil Nadu located in the southeastern part of India. Per this definition, the climatological onset and demise dates of the NEM season are 6 November and 13 March, respectively. The composite evolution of the seasonal cycle of 850hPa winds, surface wind stress, surface ocean currents, and upper ocean heat content suggest a seasonal shift around the time of the diagnosed onset and demise dates of the NEM season. The interannual variations indicate onset date variations have a larger impact than demise date variations on the seasonal length, seasonal anomalies of rainfall, and surface temperature of the NEM. Furthermore, it is shown that warm El Niño�Southern Oscillation (ENSO) episodes are associated with excess seasonal rainfall, warm seasonal land surface temperature anomalies, and reduced lengths of the NEM season. Likewise, cold ENSO episodes are likely to be related to seasonal deficit rainfall anomalies, cold land surface temperature anomalies, and increased lengths of the NEM season.
Misra, V., & Bhardwaj, A. (2019). Understanding the seasonal variations of Peninsular Florida. Clim Dyn , 54 (3-4), 1873–1885.
Abstract: This study accounts for varying lengths of the seasons, which turns out to be an important consideration of climate variability over Peninsular Florida (PF). We introduce an objective definition for the onset and demise of the winter season over relatively homogenous regions within PF: North Florida (NF), Central Florida (CF), Southeast Florida (SeF), and Southwest Florida (SwF). We first define the summer season based on precipitation, and follow this by defining the winter season using surface temperature analysis. As a consequence, of these definitions of the summer and the winter seasons, the lengths of the transition seasons of spring and fall also vary from year to year. The onset date variations have a robust relationship with the corresponding seasonal length anomalies across PF for all seasons. Furthermore, with some exceptions, the onset date variations are associated with corresponding seasonal rainfall and surface temperature anomalies, which makes monitoring the onset date of the seasons a potentially useful predictor of the following evolution of the season. In many of these instances the demise date variations of the season also have a bearing on the preceding seasonal length and seasonal rainfall anomalies. However, we find that variations of the onset and the demise dates are independent of each other across PF and in all seasons. We also find that the iconic ENSO teleconnection over PF is exclusive to the seasonal rainfall anomalies and it does not affect the variations in the length of the winter season. Given these findings, we strongly suggest monitoring and predicting the variations in the lengths of the seasons over PF as it is not only an important metric of climate variability but also beneficial to reduce a variety of risks of impact of anomalous seasonal climate variations.
