Gina R. Henderson
United States Naval Academy
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Featured researches published by Gina R. Henderson.
Journal of Climate | 2015
J. M. English; Andrew Gettelman; Gina R. Henderson
AbstractRadiative fluxes are critical for understanding the energy budget of the Arctic region, where the climate has been changing rapidly and is projected to continue to change. This work investigates causes of present-day biases and future projections of top-of-atmosphere (TOA) Arctic radiative fluxes in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Compared to Clouds and the Earth’s Radiant Energy System Energy Balanced and Filled (CERES-EBAF), CMIP5 net TOA downward shortwave (SW) flux biases are larger than outgoing longwave radiation (OLR) biases. The primary contributions to modeled TOA SW flux biases are biases in cloud amount and snow cover extent compared to the GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP) and the newly developed Making Earth System Data Records for Use in Research Environments (MEaSUREs) dataset, respectively (with most models predicting insufficient cloud amount and snow cover in the Arctic), and biases with sea ice albedo. Future projections (2081–90) w...
Journal of Climate | 2015
Donald M. Lafleur; Bradford S. Barrett; Gina R. Henderson
AbstractOne of the most commonly used metrics for both locating the Madden–Julian oscillation (MJO) geographically and defining the intensity of MJO convective activity is the real-time multivariate MJO (RMM) index. However, a climatology of the MJO, particularly with respect to the frequency of activity levels or of consecutive days at certain activity thresholds, does not yet exist. Thus, several climatological aspects of the MJO were developed in this study: 1) annual and 2) seasonal variability in MJO intensity, quantified using four defined activity categories (inactive, active, very active, and extremely active); 3) persistence in the above-defined four categories; 4) cycle length; and 5) low-frequency (decadal) variability.On an annual basis, MJO phases 1 and 2 occurred more often, and phase 8 occurred less often, than the other phases throughout the year. Notable seasonality was also found, particularly in the frequency of extremely active MJO in March–May (8% of days) compared with June–August (o...
Climate Dynamics | 2014
Gina R. Henderson; Bradford S. Barrett; Donald M. Lafleur
Arctic sea ice responds to atmospheric forcing in primarily a top-down manner, whereby near-surface air circulation and temperature govern motion, formation, melting, and accretion. As a result, concentrations of sea ice vary with phases of many of the major modes of atmospheric variability, including the North Atlantic Oscillation, the Arctic Oscillation, and the El Niño-Southern Oscillation. However, until this present study, variability of sea ice by phase of the leading mode of atmospheric intraseasonal variability, the Madden–Julian Oscillation (MJO), which has been found to modify Arctic circulation and temperature, remained largely unstudied. Anomalies in daily change in sea ice concentration were isolated for all phases of the real-time multivariate MJO index during both summer (May–July) and winter (November–January) months. The three principal findings of the current study were as follows. (1) The MJO projects onto the Arctic atmosphere, as evidenced by statistically significant wavy patterns and consistent anomaly sign changes in composites of surface and mid-tropospheric atmospheric fields. (2) The MJO modulates Arctic sea ice in both summer and winter seasons, with the region of greatest variability shifting with the migration of the ice margin poleward (equatorward) during the summer (winter) period. Active regions of coherent ice concentration variability were identified in the Atlantic sector on days when the MJO was in phases 4 and 7 and the Pacific sector on days when the MJO was in phases 2 and 6, all supported by corresponding anomalies in surface wind and temperature. During July, similar variability in sea ice concentration was found in the North Atlantic sector during MJO phases 2 and 6 and Siberian sector during MJO phases 1 and 5, also supported by corresponding anomalies in surface wind. (3) The MJO modulates Arctic sea ice regionally, often resulting in dipole-shaped patterns of variability between anomaly centers. These results provide an important first look at intraseasonal variability of sea ice in the Arctic.
Journal of Climate | 2013
Gina R. Henderson; Daniel J. Leathers; Brian Hanson
AbstractThe difference between snow-covered and snow-free conditions is the most climatically significant natural seasonal change the land surface can experience. Most GCM studies investigating snow–atmosphere interactions have focused on impacts of Eurasian snow anomalies caused by the magnitude of snow mass, while North American snow has been shown to have a weaker relationship with downstream climate. Experiment design of recent snow–atmosphere interactions studies has been limited to atmosphere-only models, with sea surface temperature (SST) and sea ice extent represented as boundary conditions. The authors explore the circulation response to anomalous snow scenarios, for both North America and Eurasia, using a slab ocean model. Surface response include significant SST cooling directly downstream of each individual forcing region in addition to upstream centers of remote cooling under maximum snow conditions. Atmospheric response to anomalous snow conditions is consistent through multiple levels in th...
Journal of Climate | 2015
Bradford S. Barrett; Gina R. Henderson; Joshua S. Werling
AbstractIntraseasonal variability in springtime Northern Hemisphere daily snow depth change (ΔSD) by phase of the MJO was explored in this study. Principal findings of the relationship between ΔSD and the MJO included the following: 1) Statistically significant regions of lagged ΔSD anomalies for multiple phases of the MJO were found in March, April, and May in both North America and Eurasia. 2) In each month, lagged ΔSD anomalies were physically supported by corresponding lagged anomalies of 500-hPa height (Z500) and surface air temperature (SAT). Spearman rank correlation coefficients indicated a moderate to strong relationship between both Z500 and ΔSD and SAT and ΔSD in both Eurasia and North America for phases 5 and 7 in March. In April, a moderately strong relationship between Z500 and ΔSD was found over Eurasia for phase 5, but the relationship between SAT and ΔSD was weak. In May, correlations between ΔSD and both Z500 and SAT over a hemisphere-wide latitude band from 60° to 75°N were close to −0....
Journal of Atmospheric and Oceanic Technology | 2016
Daria Kluver; Tom Mote; Daniel J. Leathers; Gina R. Henderson; Weihan Chan; David A. Robinson
AbstractThis study details the creation of a gridded snowfall dataset for North America, with focus on the quality of the interpolated product. Daily snowfall amounts from National Weather Service Cooperative Observer Program stations and Meteorological Service of Canada surface stations are interpolated to 1° by 1° grids from 1900 to 2009 and examined for data record length and quality. The interpolation is validated spatially and temporally through the use of stratified sampling and k-fold cross-validation analyses. Interpolation errors average around 0.5 cm and range from less than 0.01 to greater than 2.5 cm. For most locations, this is within the measurement sensitivity. Grid cells with large variations in elevation experience higher errors and should be used with caution. A new gridded snowfall climatology is presented based on in situ observations that capture seasonal and interannual variability in monthly snowfall over most of the North American land area from 1949 to 2009. The Community Collabor...
Journal of Coastal Research | 2015
David L. Kriebel; Joseph D. Geiman; Gina R. Henderson
ABSTRACT Kriebel, D.L.; Geiman, J.D., and Henderson, G.R., 2015. Future flood frequency under sea-level rise scenarios. The effect of sea-level rise (SLR) on exceedance probabilities for annual flooding at coastal locations is explored in this paper. We assess four future SLR scenarios given by the U.S. Army Corps of Engineers and how these SLR scenarios affect monthly flooding statistics. Focusing on one case site, Annapolis, Maryland, we fit the probability density function of the monthly maximum tide gauge record with a Pareto-tail distribution. Random sampling from this distribution is then performed on top of the various future SLR scenarios. Exceedance probabilities for a storm tide to exceed the coastal flood stage, the elevation of which has already been established in a previous paper, are then calculated from the interpolated Pareto cumulative distribution. We illustrate that even mild increases in mean sea level acceleration lead to drastically higher exceedance probabilities of coastal flooding.
Monthly Weather Review | 2018
Gina R. Henderson; Bradford S. Barrett; Ashley Lois; Haadi Elsaawy
ABSTRACTIntraseasonal tropical variability has important implications for the mid- and high-latitude atmosphere, and in recent studies has been shown to modulate a number of weather processes in th...
International Journal of Climatology | 2009
Gina R. Henderson; Daniel J. Leathers
International Journal of Climatology | 2008
Daniel J. Leathers; Melissa L. Malin; Daria Kluver; Gina R. Henderson; Tianna Bogart