Model‐simulated interannual variability of Lake Erie ice cover, circulation, and thermal structure in response to atmospheric forcing, 2003–2012

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100281/1/jgrc20312.pd

Midwest

The Midwest is home to over 60 million people, and its active economy represents 18% of the U.S. gross domestic product. The region is probably best known for agricultural production. Increases in growingseason temperature in the Midwest are projected to be the largest contributing factor to declines in the productivity of U.S. agriculture. Increases in humidity in spring through mid-century are expected to increase rainfall, which will increase the potential for soil erosion and further reduce planting-season workdays due to waterlogged soil

Improving the lake scheme within a coupled WRF‐lake model in the Laurentian Great Lakes

In this study, a one‐dimensional (1‐D) thermal diffusion lake model within the Weather Research and Forecasting (WRF) model was investigated for the Laurentian Great Lakes. In the default 10‐layer lake model, the albedos of water and ice are specified with constant values, 0.08 and 0.6, respectively, ignoring shortwave partitioning and zenith angle, ice melting, and snow effect. Some modifications, including a dynamic lake surface albedo, tuned vertical diffusivities, and a sophisticated treatment of snow cover over lake ice, have been added to the lake model. A set of comparison experiments have been carried out to evaluate the performances of different lake schemes in the coupled WRF‐lake modeling system. Results show that the 1‐D lake model is able to capture the seasonal variability of lake surface temperature (LST) and lake ice coverage (LIC). However, it produces an early warming and quick cooling of LST in deep lakes, and excessive and early persistent LIC in all lakes. Increasing vertical diffusivity can reduce the bias in the 1‐D lake but only in a limited way. After incorporating a sophisticated treatment of lake surface albedo, the new lake model produces a more reasonable LST and LIC than the default lake model, indicating that the processes of ice melting and snow accumulation are important to simulate lake ice in the Great Lakes. Even though substantial efforts have been devoted to improving the 1‐D lake model, it still remains considerably challenging to adequately capture the full dynamics and thermodynamics in deep lakes.Key PointsA dynamic lake surface albedo scheme is added to the lake modelThe new lake model produces a more reasonable LST and LIC than the default lake modelIce melting and snow accumulation are important to simulating lake ice in the Great LakesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135995/1/jame20346_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135995/2/jame20346.pd

Desert Research and Technology Studies (DRATS) 2010 Science Operations: Operational Approaches and Lessons Learned for Managing Science during Human Planetary Surface Missions

Desert Research and Technology Studies (Desert RATS) is a multi-year series of hardware and operations tests carried out annually in the high desert of Arizona on the San Francisco Volcanic Field. These activities are designed to exercise planetary surface hardware and operations in conditions where long-distance, multi-day roving is achievable, and they allow NASA to evaluate different mission concepts and approaches in an environment less costly and more forgiving than space.The results from the RATS tests allows election of potential operational approaches to planetary surface exploration prior to making commitments to specific flight and mission hardware development. In previous RATS operations, the Science Support Room has operated largely in an advisory role, an approach that was driven by the need to provide a loose science mission framework that would underpin the engineering tests. However, the extensive nature of the traverse operations for 2010 expanded the role of the science operations and tested specific operational approaches. Science mission operations approaches from the Apollo and Mars-Phoenix missions were merged to become the baseline for this test. Six days of traverse operations were conducted during each week of the 2-week test, with three traverse days each week conducted with voice and data communications continuously available, and three traverse days conducted with only two 1-hour communications periods per day. Within this framework, the team evaluated integrated science operations management using real-time, tactical science operations to oversee daily crew activities, and strategic level evaluations of science data and daily traverse results during a post-traverse planning shift. During continuous communications, both tactical and strategic teams were employed. On days when communications were reduced to only two communications periods per day, only a strategic team was employed. The Science Operations Team found that, if communications are good and down-linking of science data is ensured, high quality science returns is possible regardless of communications. What is absent from reduced communications is the scientific interaction between the crew on the planet and the scientists on the ground. These scientific interactions were a critical part of the science process and significantly improved mission science return over reduced communications conditions. The test also showed that the quality of science return is not measurable by simple numerical quantities but is, in fact, based on strongly non-quantifiable factors, such as the interactions between the crew and the Science Operations Teams. Although the metric evaluation data suggested some trends, there was not sufficient granularity in the data or specificity in the metrics to allow those trends to be understood on numerical data alone

Comment on Hicham Bahi, et al. Effects of Urbanization and Seasonal Cycle on the Surface Urban Heat Island Patterns in the Coastal Growing Cities: A Case Study of Casablanca, Morocco. Remote Sens. 2016, 8, 829

A statement in this recently published paper makes a point that is largely at odds with the main point of the paper that is cited. Stating that higher air temperatures lead to greater evapotranspiration is an oversimplification; the true story is more complex. Although this is by no means central to the conclusions of the paper being commented on, we have demonstrated the danger in taking too literally the idea that air temperature determines potential evapotranspiration

Temporal and Spatial Variability of Great Lakes Ice Cover, 1973–2010

In this study, temporal and spatial variability of ice cover in the Great Lakes are investigated using historical satellite measurements from 1973 to 2010. The seasonal cycle of ice cover was constructed for all the lakes, including Lake St. Clair. A unique feature found in the seasonal cycle is that the standard deviations (i.e., variability) of ice cover are larger than the climatological means for each lake. This indicates that Great Lakes ice cover experiences large variability in response to predominant natural climate forcing and has poor predictability. Spectral analysis shows that lake ice has both quasi-decadal and interannual periodicities of;8 and ~4 yr. There was a significant downward trend in ice coverage from 1973 to the present for all of the lakes, with Lake Ontario having the largest, and Lakes Erie and St. Clair having the smallest. The translated total loss in lake ice over the entire 38-yr record varies from 37% in Lake St. Clair (least) to 88% in Lake Ontario (most). The total loss for overall Great Lakes ice coverage is 71%, while Lake Superior places second with a 79% loss. An empirical orthogonal function analysis indicates that a major response of ice cover to atmospheric forcing is in phase in all six lakes, accounting for 80.8% of the total variance. The second mode shows an out-of-phase spatial variability between the upper and lower lakes, accounting for 10.7% of the total variance. The regression of the first EOF-mode time series to sea level pressure, surface air temperature, and surface wind shows that lake ice mainly responds to the combined Arctic Oscillation and El Nin˜ o–Southern Oscillation patterns

Energy budget considerations for hydro-climatic impact assessment in Great Lakes watersheds

© 2014 Elsevier B.V. Given the large share of the water budget contributed by evapotranspiration (ET), accurately estimating ET is critical for hydro-climate change studies. Routinely, hydrologic models use temperature proxy relationships to estimate potential evapotranspiration (PET) when forced using GCM/RCM projections of precipitation and temperature. A limitation of this approach is that the temperature proxy relationships do not account for the conservation of energy needed to estimate ET consistently in climate change scenarios. In particular, PET methods using temperature as a proxy fail to account for the negative feedback of ET on surface temperature. Using several GCM projections and a hydrologic model developed for the Great Lakes basin watersheds, the NOAA Large Basin Runoff Model (LBRM), the importance of maintaining a consistent energy budget in hydrologic and climate models is demonstrated by comparing runoff projections from temperature proxy and energy conservation methods. Differences in hydrologic responses are related to watershed characteristics, hydrologic model parameters and climate variables. It is shown that the temperature proxy approach consistently leads to prediction of relatively large and potentially unrealistic reductions in runoff. Therefore, hydrologic projections adhering to energy conservation principles are recommended for use in climate change impact studies

Methodological approaches to projecting the hydrologic impacts of climate change

Climate change due to anthropogenic greenhouse gases (GHG) is expected to have important impacts on water resources, with a variety of societal impacts. Recent research has shown that applying different methodologies to assess hydrologic impacts can lead to widely diverging projections of water resources. The authors classify methods of projecting hydrologic impacts of climate change into those that estimate potential evapotranspiration (PET) based on air temperature and those that estimate PET based on components of the surface energy budget. In general, air temperature-based methods more frequently show reductions in measures of water resources (e.g., water yield or soil moisture) and greater sensitivity than those using energy budget-based methods. There are significant trade-offs between these two methods in terms of ease of use, input data required, applicability to specific locales, and adherence to fundamental physical constraints: namely, conservation of energy at the surface. Issues of uncertainty in climate projections, stemming from imperfectly known future atmospheric GHG concentrations and disagreement in projections of the resultant climate, are compounded by questions of methodology and input data availability for models that connect climate change to accompanying changes in hydrology. In the joint atmospheric-hydrologic research community investigating climate change, methods need to be developed in which the energy and moisture budgets remain consistent when considering their interaction with both the atmosphere and water resources. This approach should yield better results for both atmospheric and hydrologic processes. © 2013

Turbulent Heat Fluxes during an Extreme Lake-Effect Snow Event

Proper modeling of the turbulent heat fluxes over lakes is critical for accurate predictions of lake-effect snowfall (LES). However, model evaluation of such a process has not been possible because of the lack of direct flux measurements over lakes. The authors conducted the first-ever comparison of the turbulent latent and sensible heat fluxes between state-of-the-art numerical models and direct flux measurements over Lake Erie, focusing on a record LES event in southwest New York in November 2014. The model suite consisted of numerical models that were operationally and experimentally used to provide nowcasts and forecasts of weather and lake conditions. The models captured the rise of the observed turbulent heat fluxes, while the peak values varied significantly. This variation resulted in an increased spread of simulated lake temperature and cumulative evaporation as the representation of the model uncertainty. The water budget analysis of the atmospheric model results showed that the majority of the moisture during this event came from lake evaporation rather than a larger synoptic system. The unstructured-grid Finite-Volume Community Ocean Model (FVCOM) simulations, especially those using the Coupled Ocean–Atmosphere Response Experiment (COARE)-Met Flux algorithm, presented better agreement with the observed fluxes likely due to the model’s capability in representing the detailed spatial patterns of the turbulent heat fluxes and the COARE algorithm’s more realistic treatment of the surface boundary layer than those in the other models.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/192644/1/hydr-jhm-d-17-0062_1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/192644/2/10_1175_jhm-d-17-0062_s1.docxDescription of hydr-jhm-d-17-0062_1.pdf : Main article in PDF formDescription of 10_1175_jhm-d-17-0062_s1.docx : Supplemental Materia