Le Sommer, J., Chassignet, E. P., & Wallcraft, A. J. (2018). Ocean Circulation Modeling for Operational Oceanography: Current Status and Future Challenges. In and J. Verron J. Tintoré A. Pascual E. P. Chassignet (Ed.), New Frontiers in Operational Oceanography (pp. 289–305). Tallahassee, FL: GODAE OceanView.
Abstract: This chapter focuses on ocean circulation models used in operational oceanography, physical oceanography and climate science. Ocean circulation models area particular branch of ocean numerical modeling that focuses on the representation of ocean physical properties over spatial scales ranging from the global scale to less than a kilometer and time scales ranging from hours to decades. As such, they are an essential build-ing block for operational oceanography systems and their design receives a lot of attention from operational and research centers.
Lee, C. M., Starkweather, S., Eicken, H., Timmermans, M. - L., Wilkinson, J., Sandven, S., et al. (2019). A Framework for the Development, Design and Implementation of a Sustained Arctic Ocean Observing System. Front. Mar. Sci. , 6 .
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.
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.
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. (2020). The impact of varying seasonal lengths of the rainy seasons of India on its teleconnections with tropical sea surface temperatures. Atmos Sci Lett , 21 (3), 9658–9689.
Abstract: We present in this paper the interannual variability of seasonal temperature and rainfall in the Indian meteorological subdivisions (IMS) for boreal winter and summer seasons that take in to account the varying length of the seasons. Our study reveals that accounting for the variations in the length of the seasons produces stronger teleconnections between the seasonal anomalies of surface temperature and rainfall over India with corresponding sea surface temperature anomalies of the tropical Oceans (especially over the northern Indian and the equatorial Pacific Oceans) compared to the same teleconnections from fixed length seasons over the IMS. It should be noted that the IMS show significant spatial heterogeneity in these teleconnections.
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.
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.
