Search Results

You are looking at 1 - 8 of 8 items for

  • Author or Editor: Robert Tardif x
  • Refine by Access: All Content x
Clear All Modify Search
Robert Tardif
and
Roy M. Rasmussen

Abstract

An analysis of the environmental conditions associated with precipitation fog events is presented using 20 yr of historical observations taken in a region centered on New York, New York. The objective is to determine the preferred weather scenarios and identify physical processes influencing the formation of fog during precipitation. Salient synoptic-scale features are identified using NCEP–NCAR reanalyses. Local environmental parameters, such as wind speed and direction, temperature, and humidity, are analyzed using surface observations, while the vertical structure of the lower atmosphere is examined using available rawinsonde data. The analysis reveals that precipitation fog mostly occurs as a result of the gradual lowering of cloud bases as continuous light rain or light drizzle is observed. Such scenarios occur under various synoptic weather patterns in areas characterized by large-scale uplift, differential temperature advection, and positive moisture advection. Precipitation fog onset typically occurs with winds from the northeast at inland locations and onshore flow at coastal locations, with flows from the south to southwest aloft. A majority of the cases showed the presence of a sharp low-level temperature inversion resulting from differential temperature advection or through the interaction of warm air flowing over a cold surface in onshore flow conditions. This suggests a common scenario of fog formation under moistening conditions resulting from precipitation evaporating into colder air near the surface. A smaller number of events formed with cooling of the near-saturated or saturated air. Evidence is also presented of the possible role of shear-induced turbulent mixing in the production of supersaturation and fog formation during precipitation.

Full access
Robert Tardif
and
Roy M. Rasmussen

Abstract

To gain insights into the poorly understood phenomenon of precipitation fog, this study assesses the evaporation of freely falling drops departing from equilibrium as a possible contributing factor to fog formation in rainy conditions. The study is based on simulations performed with a microphysical column model describing the evolution of the temperature and mass of evaporating raindrops within a Lagrangian reference frame. Equilibrium defines a state where the latent heat loss of an evaporating drop is balanced by the sensible heat flux from the ambient air, hence defining a steady-state drop temperature. Model results show that the assumption of equilibrium leads to small but significant errors in calculated precipitation evaporation rates for drops falling in continuously varying ambient near-saturated or saturated conditions. Departure from equilibrium depends on the magnitude of the vertical gradients of the ambient temperature and moisture as well as the drop-size-dependent terminal velocity. Contrasting patterns of behavior occur depending on the stratification of the atmosphere. Raindrops falling in inversion layers remain warmer than the equilibrium temperature and lead to enhanced moistening, with supersaturation achieved when evaporation proceeds in saturated inversions. Dehydration occurs in layers with temperature and water vapor increasing with height due to the vapor flux from the environment to the colder drops. These contrasts are not represented when equilibrium is assumed. The role of nonequilibrium raindrop evaporation in fog occurrences is further emphasized with simulations of a case study characterized by fog forming under light rain falling in a developing frontal inversion. Good agreement is obtained between fog water content observations and simulations representing only the effects of rainfall evaporation. This study demonstrates the need to take into account the nonequilibrium state of falling raindrops for a proper representation of an important mechanism contributing to precipitation fog occurrences.

Full access
Robert Tardif
and
Roy M. Rasmussen

Abstract

The character of fog in a region centered on New York City, New York, is investigated using 20 yr of historical data. Hourly surface observations are used to identify fog events at 17 locations under the influence of various physiographic features, such as land–water contrasts, land surface character (urban, suburban, and rural), and terrain. Fog events at each location are classified by fog types using an objective algorithm derived after extensive examination of fog formation processes. Events are characterized according to frequency, duration, and intensity. A quantitative assessment of the likelihood with which mechanisms leading to fog formation are occurring in various parts of the region is obtained. The spatial, seasonal, and diurnal variability of fog occurrences are examined and results are related to regional and local influences. The results show that the likelihood of fog occurrence is influenced negatively by the presence of the urban heat island of New York City, whereas it is enhanced at locations under the direct influence of the marine environment. Inland suburban and rural locations also experience a considerable amount of fog. As in other areas throughout the world, the overall fog phenomenon is a superposition of various types. Precipitation fog, which occurs predominantly in winter, is the most common type. Fog resulting from cloud-base lowering also occurs frequently across the region, with an enhanced likelihood in winter and spring. A considerable number of advection fog events occur in coastal areas, mostly during spring, whereas radiation fog occurs predominantly at suburban and rural locations during late summer and early autumn but also occurs during the warm season in the coastal plain of New Jersey as advection–radiation events.

Full access
Caren Marzban
,
Robert Tardif
, and
Scott Sandgathe

Abstract

A sensitivity analysis methodology recently developed by the authors is applied to COAMPS and WRF. The method involves varying model parameters according to Latin Hypercube Sampling, and developing multivariate multiple regression models that map the model parameters to forecasts over a spatial domain. The regression coefficients and p values testing whether the coefficients are zero serve as measures of sensitivity of forecasts with respect to model parameters. Nine model parameters are selected from COAMPS and WRF, and their impact is examined on nine forecast quantities (water vapor, convective and gridscale precipitation, and air temperature and wind speed at three altitudes). Although the conclusions depend on the model parameters and specific forecast quantities, it is shown that sensitivity to model parameters is often accompanied by nontrivial spatial structure, which itself depends on the underlying forecast model (i.e., COAMPS vs WRF). One specific difference between these models is in their sensitivity with respect to a parameter that controls temperature increments in the Kain–Fritsch trigger function; whereas this parameter has a distinct spatial structure in COAMPS, that structure is completely absent in WRF. The differences between COAMPS and WRF also extend to the quality of the statistical models used to assess sensitivity; specifically, the differences are largest over the waters off the southeastern coast of the United States. The implication of these findings is twofold: not only is the spatial structure of sensitivities different between COAMPS and WRF, the underlying relationship between the model parameters and the forecasts is also different between the two models.

Free access
Caren Marzban
,
Robert Tardif
, and
Scott Sandgathe

Abstract

In a recent work, a sensitivity analysis methodology was described that allows for a visual display of forecast sensitivity, with respect to model parameters, across a gridded forecast field. In that approach, sensitivity was assessed with respect to model parameters that are continuous in nature. Here, the analogous methodology is developed for situations involving noncontinuous (discrete or categorical) model parameters. The method is variance based, and the variances are estimated via a random-effects model based on 2 kp fractional factorial designs and Graeco-Latin square designs. The development is guided by its application to model parameters in the stochastic kinetic energy backscatter scheme (SKEBS), which control perturbations at unresolved, subgrid scales. In addition to the SKEBS parameters, the effect of daily variability and replication (both, discrete factors) are also examined. The forecasts examined are for precipitation, temperature, and wind speed. In this particular application, it is found that the model parameters have a much weaker effect on the forecasts as compared to the effect of daily variability and replication, and that sensitivities, weak or strong, often have a distinctive spatial structure that reflects underlying topography and/or weather patterns. These findings caution against fine-tuning methods that disregard 1) sources of variability other than those due to model parameters, and 2) spatial structure in the forecasts.

Free access
Stevie Roquelaure
,
Robert Tardif
,
Samuel Remy
, and
Thierry Bergot

Abstract

A specific event, called a low-visibility procedure (LVP), has been defined when visibility is under 600 m and/or the ceiling is under 60 m at Paris-Charles de Gaulle Airport, Paris, France, to ensure air traffic safety and to reduce the economic issues related to poor visibility conditions. The Local Ensemble Prediction System (LEPS) has been designed to estimate LVP likelihood in order to help forecasters in their tasks. This work evaluates the skill of LEPS for each type of LVP that takes place at the airport area during five winter seasons from 2002 to 2007. An event-based classification reveals that stratus base lowering, advection, and radiation fogs make up for 78% of the LVP cases that occurred near the airport during this period. This study also demonstrates that LEPS is skillful on these types of event for short-term forecasts. When the ensemble runs start with initialized LVP events, the prediction of advection fogs is as skillful as the prediction of radiation fog events and stratus base lowering. At 3 and 6 h before the runs where LVP events were initialized, LEPS still shows positive skill for radiation fog events and stratus base lowering cases.

Full access
Gregory J. Hakim
,
Karin A. Bumbaco
,
Robert Tardif
, and
Jordan G. Powers

Abstract

As harsh weather conditions in Antarctica make it difficult to support a dense weather observing network there, it is critical to place new weather stations in locations that are optimal for a given monitoring goal. Here we demonstrate a network design algorithm that uses ensemble sensitivity to identify optimal locations for new automatic weather stations in Antarctica. We define the optimal location as one that maximizes the reduction in total variance of a given spatial field. Using WRF Model forecast output from the Antarctic Mesoscale Prediction System (AMPS), we identify the best locations for observations across the continent by considering two spatial fields: (i) the daily 0000 UTC 2-m temperature analysis field and (ii) the daily 0000 UTC 2-m air temperature 24-h forecast field. We explore the impact of spatial localization on the results, finding that a covariance length scale of 3000 km is appropriate for these metrics. We find optimal locations assuming that no stations exist on the continent (blank slate) and conditional on existing stations (CD90). In the “blank slate” scenario, the Megadunes region emerges as the most important location to both monitor temperature and reduce temperature forecast errors, with the Ronne Coast and the Siple Coast following. Results for the monitoring and forecasting metrics are similar for the CD90 subset as well, indicating that additional stations could benefit multiple performance goals. Considering the CD90 subset, Wilkes Land–Adelie Coast, Ellsworth Land, and Queen Maud Land–Interior are identified as regions to consider installing new stations for optimizing network performance.

Free access
Xiaofang Feng
,
Qinghua Ding
,
Liguang Wu
,
Charles Jones
,
Ian Baxter
,
Robert Tardif
,
Samantha Stevenson
,
Julien Emile-Geay
,
Jonathan Mitchell
,
Leila M. V. Carvalho
,
Huijun Wang
, and
Eric J. Steig

Abstract

In the past 40 years, the global annual mean surface temperature has experienced a nonuniform warming, differing from the spatially uniform warming simulated by the forced responses of large multimodel ensembles to anthropogenic forcing. Rather, it exhibits significant asymmetry between the Arctic and Antarctic, with intermittent and spatially varying warming trends along the Northern Hemisphere (NH) midlatitudes and a slight cooling in the tropical eastern Pacific. In particular, this “wavy” pattern of temperature changes over the NH midlatitudes features strong cooling over Eurasia in boreal winter. Here, we show that these nonuniform features of surface temperature changes are likely tied together by tropical eastern Pacific sea surface temperatures (SSTs), via a global atmospheric teleconnection. Using six reanalyses, we find that this teleconnection can be consistently obtained as a leading circulation mode in the past century. This tropically driven teleconnection is associated with a Pacific SST pattern resembling the interdecadal Pacific oscillation (IPO), and hereafter referred to as the IPO-related bipolar teleconnection (IPO-BT). Further, two paleo-reanalysis reconstruction datasets show that the IPO-BT is a robust recurrent mode over the past 400 and 2000 years. The IPO-BT mode may thus serve as an important internal mode that regulates high-latitude climate variability on multidecadal time scales, favoring a warming (cooling) episode in the Arctic accompanied by cooling (warming) over Eurasia and the Southern Ocean (SO). Thus, the spatial nonuniformity of recent surface temperature trends may be partially explained by the enhanced appearance of the IPO-BT mode by a transition of the IPO toward a cooling phase in the eastern Pacific in the past decades.

Full access