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TIDAL HUDSON RIVER ICE COVER

CLIMATOLOGY

Prepared for:

The Hudson River Sustainable Shorelines Project

NYSDEC Hudson River National Estuarine Research Reserve

Prepared by:

Nickitas Georgas, Jon Miller, Yifan Wang, Yu Jiang, and David D’Agostino

Davidson Laboratory, Stevens Institute of Technology

June 2015

http://www.linkedin.com/search?search=&title=Estuary+Training+Program+Coordinator&sortCriteria=R&keepFacets=true&currentTitle=C

ACKNOWLEDGEMENTS

This report was prepared by the Davidson Laboratory at Stevens Institute of Technology for the Hudson

River Sustainable Shorelines Project.

The authors would like to thank the ice officers and ice breaker personnel of the United States Coast

Guard Sector New York, without whom the present effort would not have been accomplished. We would

especially like to thank LCDR Anne Morrissey (former Sector NY commander), LCDR Edward Munoz

(former Chief, Waterways Management Division, Sector NY), and CWO Kary Moss (former Sector NY ice

officer) for their assistance and provision of the ice report data and for useful correspondence throughout

multiple ice seasons. The author would also like to acknowledge the members of the Hudson River

Sustainable Shorelines Project for their guidance and support, especially Emilie Hauser and Ben Ganon of

the Hudson River National Estuarine Research Reserve (HRNERR), also thank you to John Ladd of the

NYSDEC Hudson River Estuary Program for making the data publically available.

About the Hudson River Sustainable Shorelines Project

The Hudson River Sustainable Shorelines Project is a multi-year effort lead by

the New York State Department of Environmental Conservation Hudson River National Estuarine

Research Reserve, in cooperation with the Greenway Conservancy for the Hudson River Valley. Partners

in the Project include Cary Institute for Ecosystem Studies, NYSDEC Hudson River Estuary Program and

Stevens Institute of Technology. The Project is facilitated by The Consensus Building Institute. The Project

fulfills aspects of Goal 2 of the Action Agenda of the Hudson River Estuary Program.

The Project is supported by the National Estuarine Research Reserve System (NERRS) Science

Collaborative, a partnership of the National Oceanic and Atmospheric Administration and the University

of New Hampshire. The Science Collaborative puts Reserve-based science to work for coastal

communities coping with the impacts of land use change, pollution, and habitat degradation in the

context of a changing climate.

Disclaimer

The opinions expressed in this report are those of the authors and do not necessarily reflect those of the

New York State Department of Environmental Conservation, the Greenway Conservancy for the Hudson

River Valley or our funders. Reference to any specific product, service, process, or method does not

constitute an implied or expressed recommendation or endorsement of it.

Suggested Citation

Georgas, N., Miller, J. K., Wang, Y., Jiang, Y. and D. D’Agostino (2015). Tidal Hudson River Ice Cover

Climatology. Stevens Institute of Technology, TR- 2949; in association with and published by the Hudson

River Sustainable Shorelines Project, Staatsburg, NY 12580, http://hrnerr.org.

http://hrnerr.org/

Tidal Hudson River Ice Cover Climatology Page 1

TABLE OF CONTENTS

SECTION PAGE

Executive Summary .................................................................................................................................................... 2

Introduction ................................................................................................................................................................. 3

Importance of This Study .......................................................................................................................................... 3

Data Source and Profile ..................................................................................................................................... 4

Methods ....................................................................................................................................................................... 6

Statistical Analysis .............................................................................................................................................. 6

Climatology Analysis ......................................................................................................................................... 6

Results .......................................................................................................................................................................... 9

Discussion .................................................................................................................................................................. 10

References .................................................................................................................................................................. 17

Appendix A—Methodology ................................................................................................................................... 18

Statistics and Confidence Intervals ................................................................................................................ 18

Appendix B—Statistics and Tables ........................................................................................................................ 21

Region ID and Name ........................................................................................................................................ 21

Ice Occurrence ................................................................................................................................................... 22

Ice Types for Every River Region ................................................................................................................... 22

CDF Analysis results ........................................................................................................................................ 24

Spatial Variation of Cumulative Probability ................................................................................................. 25

Color of Different Ice Type .............................................................................................................................. 26

Appendix C—Plots ................................................................................................................................................... 27

Statistical analysis Plots ................................................................................................................................... 27

Climatology Analysis Plots ............................................................................................................................. 44

Appendix D—Ice Types, definitions and photographs ...................................................................................... 60


EXECUTIVE SUMMARY

The winter ice season (mid-December to late March each year) brings many significant changes to the

water circulation and tides in the Hudson River Estuary. Ice cover thickness is also an important

engineering and design parameter for Hudson River Sustainable Shorelines. To describe ice conditions in

the Hudson, Stevens Institute of Technology has collected and processed US Coast Guard (USCG) daily

ice reports from the tidal Hudson River for the past 11 winter seasons [2004-2015] at 16 different stretches

and ice choke points spanning some 140 miles along the river from the George Washington Bridge in

Manhattan on the south, to Troy, NY on the north.

In association with the NERRS Science Collaborative, this report describes the methodology and results of

climatological and statistical analyses for ice distributions along the Hudson, based on the USCG dataset.

Given the scarcity of ice data in the tidal Hudson, the statistical distributions of ice thickness and ice

cover area (in the form of cumulative probability density functions when ice is present) as well as ice type

information, are meant to provide some guidance on engineering planning studies along the Hudson

River. The tabulated climatological conditions, although based only on 11 years of USCG observations

from the decks of the ice breakers that maintain traffic flow of the Hudson during winter, can form the

beginning of an understanding of how ice grows and finally rots in the tidal Hudson’s regions during a

season, and provide a baseline to compare future years by. It is found for example that the latest ice

season, 2014-2015 broke ice thickness records for the months of February and March for most regions of

the tidal Hudson.

The statistics that are presented in this report have been published as georeferenced datasets in the NYS

GIS clearinghouse: http://gis.ny.gov/gisdata/metadata/nysdec.hudson_ice_meta.xml.

Use Limitation

This dataset is based on a compilation of USCG ice reports, which have a limited scope and are empirical.

The scope of the presented datasets are therefore to provide a general picture of the regional ice

climatology in the Tidal Hudson River, and is by no means an accurate description of ice conditions at

any given year. Use at your own risk.

http://gis.ny.gov/gisdata/metadata/nysdec.hudson_ice_meta.xml


INTRODUCTION

Importance of This Study

The United States Coast Guard defines the winter ice season in Sector New York’s tidal waters as the

period beginning December 15 to the end of March each year. During winter ice seasons, a seasonal ice

field grows on the surface waters of the Hudson River Estuary, which, during colder years, can cover the

Hudson’s surface from bank to bank. Though the ice cover may vary significantly in extent and thickness

from year to year, Georgas (2012), showed that it can bring many significant changes to the water

circulation and water levels along the Tidal Hudson River and Estuary. When the ice concentration

increases and the cover becomes fast from shore to shore, under-keel ice friction can greatly reduce tidal

currents under the ice cover through frictional dumping, leading to much smaller current magnitudes

and tidal circulation than during warmer winters that ice concentration is more limited. Near Troy, New

York, the reduced tidal flows become smaller relative to the river’s stream flow discharge coming over

the Federal Dam, leading to increased ebb predominance and constantly-downstream flows down to the

port of Albany, NY; In other words, as tides can slow down due to ice friction when ice is fast to the

shore, the geographic extent of “the river that flows both ways” – Mahicantuck in the local Native

American language – decreases, and the non-tidal Hudson River may push downstream past Albany.

The frictional tidal dumping from the ice cover can also raise low waters by a couple of feet and reduce

tidal ranges (the difference between tidal high and low waters) by as much as 50% in the northern parts

of the tidal river near Albany and Troy. On the contrary, tidal ranges increase near the southern edge of

the ice field and on Manhattan’s western shores, currents increase because of tidal wave reflection from

the shore-fast ice cover upstream. These amplified currents can also create stronger vertical mixing

leading to a less stratified lower Estuary and decreasing salt front intrusion.

These ice effects on hydrodynamics, water circulation, salinity intrusion, and local residence times,

increase with ice concentration and ice thickness (Georgas 2012) and can have significant implications to

life and trade within the Hudson’s waters and along the Hudson’s shores. Commercial navigation and

route scheduling rely on careful timing for the passage of cargo-carriers through tidal waters so that ships

have enough under-keel clearance not to run aground and enough over-head clearance to pass under the

Hudson’s bridges, while maximizing tonnage to ensure profitability. The dynamic variations in water

levels caused by the ice explained above and in Georgas (2012) are uncertainty factors that need to be

considered for safe navigation. Habitat and fish (especially through early life stages) can be affected by

hydrodynamics, thus they may be affected by the seasonal ice effects on hydrodynamics, especially in

view of ongoing climate change and predictions for a much warmer climate by the end of this century.

Shoreline engineers planning either hard or soft engineering projects need to also consider the effect

seasonal ice has on exposed structures. Usually, the most critical types of dynamic forces imposed by ice

are horizontal loads on vertical and sloping structures. The magnitude of this type of loading is

dependent on the point where the ice fails by crushing or splitting, which is dependent on its thickness

(USACE 2011). This type of horizontal loading is typically experienced on vertical structures, such as

walls, because their vertical face and height prevent ice from overtopping the structure before breaking

apart. The force imposed by ice riding up over a structure, such as a revetment, is therefore much less than

direct horizontal loading on the face of the revetment. Vertical ice forces include the weight of ice piling


up on a structure and the cyclic stresses of the freeze and thaw cycles; they have small impact on

established vegetated shorelines. Adfreeze loads are pressure forces applied to a structure that has become

encased and frozen in ice (Miller and Georgas 2015).

Ice jams (resulting when ice passage in a river section is blocked and the ice piles up upstream) are an

important consideration for in-stream structures in the Hudson River; the USACE ice jam database

(USACE, 2009) lists ice jams having occurred in the tidal Hudson River as recently as 2007 and 1996 at

Catskill, NY and Troy, NY, respectively. Total ice loads are site-specific and very little general guidance

exists for its impacts on sustainable shoreline treatments; however, a good rule of thumb to prevent the

movement of individual stones in stone structures impacted by horizontal ice loads is to size the median

stone diameter (Dn50) to be two to three times greater than the expected maximum winter ice thickness

(Tuthill, 2008). Once a shoreline stabilization project is designed, it is suggested that a maintenance plan

be included to ensure that it maintains stability after significant ice events in the Hudson.

However, quantifiable information on the thickness, distribution, type and the growth-rot cycle of ice on

the Hudson is extremely limited. It was the present study’s objective to work on filling in this knowledge

gap, based on statistical and climatological analyses of observations collected from United States Coast

Guard / Sector NY ice reports.

Data Source and Profile

To describe ice conditions on the Hudson, we collected and processed US Coast Guard daily ice reports

from the tidal Hudson River for the past 11 winter ice seasons (datasets a and b below). The ice season

starts on December 15th and ends on March 31st of each year. Out of these 11 ice seasons, only the last 8

winter seasons (dataset b) include data from USCG for the 7 listed ice choke points (areas of river-ice

congestion) in the Hudson (Figure 1).

a) 2004-2005 2005-2006 2006-2007

b) 2007-2008 2008-2009 2009-2010 2010-2011 2011-2012 2012-2013 2013-2014 2014-2015

Stevens Institute of Technology obtained the USCG daily ice reports either directly from USCG/Sector

NY by mail in print form, for the period December 15 2009 to February 10 2011, post-marked February 11

2011; by downloading daily from the USCG Sector NY ice portal: https://homeport.uscg.mil, for the rest

of February 2011 to March 2015 and; by downloading from the Moran Shipping online archives of daily

USCG port of New York and New Jersey updates: http://nynj.ports.moranshipping.com, for dates prior

to April 2009.

The daily USCG reports divide the Tidal Hudson River into 16 regions (Figure 1). The reports record the

ICE TYPE, ICE THICKNESS RANGE, and PERCENT COVERAGE for each region and day. The ICE

TYPE report entry denotes the type(s) of ice that was present on that river region on that day. Pictures

and definition for each ice type can be found in Appendix D. Based on the USCG definition (USCG, 2015),

ICE THICKNESS is measured in inches as accurately as possible, and in as many places as the varying

thickness warrants. This variation is then tabulated for each region as an ice thickness RANGE.

PERCENT COVERAGE is defined by USCG as the percentage of water surface covered by ice to the total

surface area at a specific location or over a defined area.

https://homeport.uscg.mil/

http://nynj.ports.moranshipping.com/


Figure 1: The sketch map of 16 Hudson River ice regions based on the USCG Sector NY definitions.


METHODS

In order to describe ice condition on the Hudson, two approaches were used: a) statistical analysis that focused on the use of an extreme value distribution to probabilistically describe the observed ice thickness and ice concentration during times that ice is present on the river, with the coastal engineer in mind, and b) ice climatology analysis, for a more general audience. In this section, we briefly explain our methodology and provide an example. Details on the statistical approach, especially for ice thickness ranges, can be found in Appendix A.

Statistical Analysis

For each of the 16 Hudson River regions defined by USCG (Figure 1) we computed the number of days

that ice was present in the Hudson within each winter ice season. We report the number of days with ice

as a percent of all winter ice season days with USCG observations, and call this “recorded ice

occurrence.”

We then created empirical cumulative probability density functions (CDF) based on all daily ice thickness

and %-ice-cover data from the days that had ice on that region. A Generalized Extreme Value

Distribution (GEV) was then used to fit the empirical CDF for both ice thickness and percent ice cover,

and provide tabulated probability percentiles at 50%, 75%, 90%, and 95% probabilities. Statistical

confidence intervals were also calculated for each percentile, as well as the corresponding actual regional

daily variations for these percentiles, which were then plotted. Finally, the occurrence of each ice type

reported during ice days was summarized and plotted as a bar chart. An example for Region 1 (River

Stretch from George Washington Bridge to Tappan Zee Bridge) is seen in Figure 2.

Climatology Analysis

A climatology analysis was carried out for both thickness range and coverage. The winter ice season was

divided into 7 stages by splitting each month in half:

Stages:

1) Late December

2) Early January

3) Late January

4) Early February

5) Late February

6) Early March

7) Late March

Daily values within each stage were then considered, and averaged across all 8 (for choke points) to 11

(for river stretches) winter ice seasons. In this case, all observations were considered in the averages,

including days with no ice reported. For ice thickness range, the lows and highs of the daily ranges were

considered independently, creating a “climatology low” and “climatology high” range estimate for each

stage. The means for each stage were tabulated, and plots comparing each of the past 11 ice seasons to the

average climatology were created. Figure 3 is an example of the climatology analysis for Region 1.

http://dict.youdao.com/search?q=February&keyfrom=E2Ctranslation


Figure 2: Top panel: Reported ice thickness (inches) and percent ice cover (%) from 2005-2015. Middle

panel: CDF (Cumulative Distribution Function; empirical and GEV-fit) for ice thickness and percent

cover. For ice thickness, dotted lines show the 50% and 95% percentile ice thickness calculated for that

region during days with ice, while horizontal bars show the expected ice thickness ranges for these

percentiles. Bottom panel: Bar chart shows the probability of occurrence, in percent form, for each kind of

ice type, based on the reports when ice was present.


Climatology Late Dec Early Jan Late Jan Early Feb Late Feb Early Mar Late Mar

Mean Low (in) 0.0 0.1 0.5 0.4 0.2 0.2 0.0

Mean High (in) 0.0 0.2 0.9 0.8 0.5 0.4 0.0

Record High (in)

Year record occurred

3.0

(2010)

3.0

(2014)

8.0

(2009)

6.0

(2005/2015)

6.0

(2015)

6.0

(2015)

0.0

a Mean Coverage (%) 0.1 2.8 11.1 10.7 6.3 2.1 0.0

Figure 3: Top panel: Climatology analysis for Thickness. Light green bars show the climatological

Records per stage: The maximum ice thickness recorded over the whole 11 year period for each stage.

Actual recorded maximum thicknesses observed within each stage and year are also shown (yellow thick

bars). The black lines show the climatologically Average Ice Thickness Range while the red lines show the

Actual Mean Range recorded during that stage and ice season. Bottom panel: Climatology analysis for

Coverage. The heights of the thick light green bars represent the Climatologically Average Coverage. The

heights of the narrower bars show the Actual Average Coverage recorded during that stage and ice

season. The color of bar represent the prevalent ice type recorded during that stage and ice season (the

type that had the higher percent occurrence during that stage and season). Tables shows the values of the

climatological averages and the record highs.


RESULTS

An important parameter we wanted to quantify with this work is the 95% cumulative probability for ice

thickness, which can inform an engineer on the thickness of ice cover that would be expected to be

surpassed only 5 out of 100 ice days. Using the statistical analysis described in the Methods section and,

in more detail, in Appendix A, we were able to calculate both the 95th percentile cumulative probability of

the representative ice thickness for a given region, as well as a representative ice thickness range for that

percentile across that region. For example, for region 1 (River Stretch: George Washington Bridge to

Tappan Zee), the 95% region-wide representative ice thickness is around 5.7 inches and, within that

region, the 95% thickness is expected to vary between 4.2 inches and 7.2 inches (Figure 4). Ice thickness in

that southern-most Region 1 is the least one of all 16 river regions, which is to be expected. There are 12

regions where the 95-percent region-wide representative ice thickness is greater than 10 inches. At region

9 (Choke Point: Esopus Meadows), the 95th percentile representative ice thickness reaches a maximum of

12.1 inches, with an expected within-region variation from 11.1 inches to 13.1 inches.

Figure 4: 95% Cumulative Probability of regional ice thickness and its within-region expected variation.

See Figure 1 for location of regions.

With regard to Ice Type, the most prevalent in the southern regions 1 to 7 is Drift Ice, in regions 8 to 15 is

Brash Ice, and for the last northernmost region of the Tidal Hudson River it is Fast Ice (Table 3).

All statistical analysis results are shown in Appendix-B. The results of the climatology analysis are

included in Appendix-C.


DISCUSSION

Figure 5: Ice Occurrence (% of winter ice season days during which ice was present in the river) for each

of the 16 USCG River Regions. See Figure 1 for location of regions.

Figure 5 shows the distribution of ice occurrence in the 16 regions based on the 11 past ice seasons (8 past

ice seasons at choke points). It shows the regional variation for the presence of ice on the river. There is a

general increase of ice occurrence from the southern-most regions of the Hudson to the north where ice

occurs more days in the season. The most ice appear in region 12 (River Stretch: Kingston to Catskill).

Interestingly, in the northernmost regions from Catskill (region 14) to Troy (region 16) ice occurs slightly

less, except at the Stuyvesant anchorage choke point (region 15).

Figure 6: Ice thickness percentiles in the 16 regions, in inches. See Figure 1 for location of regions.

Figure 6 shows that the Cumulative Probability of Ice Thickness varies with location too, especially at the

boundaries of the estuarine and freshwater regions of the tidal Hudson, and especially near West Point

where the river’s width decreases dramatically and its sinuosity increases (see region 3, Jones Point to

West Point, and regions 4 and 5, at and north of West Point; Figure 6). Region 4 (Choke Point: West Point),

region 5 (River Stretch: West Point to Newburgh), and region 9 (Choke Point: Esopus Meadows) tend to

have thicker ice compared to other regions. A drop in thickness occurs at region 6 which includes the


wider Newburgh Bay. Except for the first three regions and region 6, the 95% Cumulative Probability for

the rest of the 12 regions are all above 10 inches.

Figure 7: Ice Coverage Distribution within each of the 16 Regions. See Figure 1 for location of regions.

Figure 7 shows that, generally, ice coverage within a given region increases from south to north, which is

reasonable because not only the temperature is decreasing but also the salinity is decreasing. The figure

shows that from region 4 (Choke Point: West Point) and upstream, 70% or more of each region’s area is

expected to be covered for at least half of the winter ice season’s duration. On the contrary, shore to shore

ice cover is extremely unlikely in the southern, wider and saltier regions; Only 5 out of 100 days are

expected to have over 80-90% areal ice coverage there.

The above-mentioned spatial patterns are also visible in the maps shown on Figure 8.

Figures 9 and 10 show maps of the progression of regional ice coverage within each stage of the winter

season based on the climatological averages calculated here. Figures 11 and 12 show the same

progression for thickness growth and rot/break-up. As time goes by, results show that ice typically

grows until sometime in February when it starts breaking up.


Figure 8: This figure shows maps from the tidal Hudson River ice statistics GIS layer. It shows the spatial variation of statistically-derived ice

quantities. Generally, ice occurrence at the northern part is larger than that at the southern part of the river. However, both occurrence and ice

thickness peak at the central part of the river. Downstream, the most prevalent ice type tends to be Drift Ice while upstream it is Brash Ice and

finally Fast Ice near Troy. In terms of areal ice coverage, the narrower northern parts can fill with ice from shore to shore more days than the wider

southern parts of the river.


Figure 9: This figure shows maps from the tidal Hudson River Ice Climatology GIS layer on Ice Coverage %. Shown from left to right are the

seven stages of the winter ice season (late Dec, early Jan, late Jan, early Feb, late Feb, early Mar, late Mar). Here, different colors represent the ice

coverage of each region: the whiter the more ice coverage; dark blue is open waters. The upstream regions within the red box can be better seen in

Figure 10.


Figure 10: This figure shows maps from the upstream regions mentioned in Figure 9 from the tidal Hudson River Ice Climatology GIS layer on Ice

Coverage %. Shown from left to right are the seven stages of the winter ice season (late Dec, early Jan, late Jan, early Feb, late Feb, early Mar, late

Mar). Comparison of the later stages between Figures 9 and 10 reveals that these northern tidal Hudson Regions have less ice coverage during

March than the southern part. It is likely that river flow pushes the broken ice from these regions down to the south.


Figure 11: This figure shows maps from the tidal Hudson River Ice Climatology GIS layer on Ice Thickness (inches). It shows ice thickness (values

increase from blue to white color) during each of the seven stages of the winter ice season (late Dec, Early Jan, Late Jan, Early Feb, Late Feb, Early

Mar, Late Mar), from left to right. Ice thickness typically increases from Late Dec to Late Jan and then decreases. Some regions in center part of

tidal Hudson River have ice thickness that is still growing, but most decrease, and this decrease shows up with a time lag as a decrease in spatial

ice coverage (Figure 9). The upstream regions within the red box can be better seen in Figure 12.


Figure 12: This figure shows maps from the upstream regions mentioned in Figure 11 from the tidal Hudson River Ice Climatology GIS layer on

Ice Thickness (inches). It shows ice thickness (values increase from blue to white color) during each of the seven stages of the winter ice season

(late Dec, Early Jan, Late Jan, Early Feb, Late Feb, Early Mar, Late Mar), from left to right.


REFERENCES

Georgas, N., 2012. Large Seasonal Modulation of Tides due to Ice Cover Friction in a Mid-Latitude Estuary,

Journal of Physical Oceanography. 42(3), 352-369.

Miller, J.K., and N. Georgas, 2015. Hudson River Physical Forces Analysis: Data Sources and Methods. Stevens

Institute of Technology, TR- 2946; in association with and published by the Hudson River Sustainable

Shorelines Project, Staatsburg, NY 12580, http://hrnerr.org

Rubin, D., 1978. Multiple Imputations in Sample Surveys – A phenomenological Bayesian approach to

nonresponse. Educational Testing Service, 28pp.

Tuthill, A., 2008. Ice Considerations in the Design of River Restoration Structures, ERDC/CRREL TR-08-2.

US Army Corps of Engineers, 2009. CRREL Ice Jam Database, CRREL TR-99-2.

US Army Corps of Engineers, 2011. Coastal Engineering Manual: Fundamentals of Design, EM 1110-2-1100.

US Coast Guard, 2015. Ice Definitions. Homeport NY Icebreaking Operations. Accessed online, 2015:

https://homeport.uscg.mil/mycg/portal/ep/portDirectory.do?tabId=1&cotpId=2

http://hrnerr.org/


APPENDIX A--METHODOLOGY

Statistics and Confidence Intervals

The goal of CDF analysis is to figure out the likelihood of how thick the ice in one river region will be. In

this aspect, we have to face two problems. One is the limited number of samples from 11 ice seasons and

the second is that we do not have enough information about what the daily thickness ranges in the USCG

reports really say about the distribution of ice within a given region that day.

We addressed both problems simultaneously using a non-parametric statistical imputation approach

(Rubin 1978). We first generated 50 random numbers inside of each daily thickness range in each region

to expand the number of samples [500 were also tested and the results were nearly identical]. Without

knowledge of a statistical distribution within each range, we considered these 50 random numbers as 50

independent thickness samples within that different region. This random imputation technique is more

reasonable in terms of sampling the distribution of ice thickness than using, say, the mid-point of each

daily range. Next, we performed CDF analysis of all these ice thickness samples (50 samples per

observation day for all ice seasons) in order to find the 50%, 75%, 90% and 95% percentiles, among which

the 95% percentile can be a really useful parameter for engineering planning. We then calculated the 95%

confidence intervals of the GEV fit for each of these four percentiles using Rubin’s formula (Rubin 1978,

equation 1-1). In Eq. 1-1, the first term represents the mean level of the variate and the second term

represents the variation of variate within each imputation. Here, the variate is the confidence interval.

)50

11(

50

1 50

1

bias

b

brubin CIciCI (1-1)

In which,

50

1

250

1

)50

1(

b b

bbbias ciciCI

(1-2)

For instance, in one river region, say we had a thickness range in one day which was 2-4 inches. We

generated 50 random numbers (thicknesses) in the range of 2-4 inches. We did the same thing for each

thickness range we had for that region. If we choose the first random thickness sample of every range,

and do CDF analysis for these chosen thicknesses, we can get a confidence interval. This confidence

interval is cib in Equation 1-1, while b=1. And so on, for the rest of the 50 random drawings. After using

Rubin’s formula we get a variational confidence interval for all samples (Figure 13).


Figure 13: The difference between two Confidence Intervals (C.I.) for the Generalized Extreme Value

(GEV) distribution fit can be seen in this figure. The blue C.I. is the variation confidence interval after

using Rubin’s equation to account for the variation of each imputation’s C.I. compared to the overall

grand mean C.I. (which considers all imputations together).

By doing the CDF analysis based on imputation we calculated robust confidence intervals through

Rubin’s non-parametric formula for the GEV fit of the four percentiles of representative region-wide ice

thickness. Within each region however, we also want to consider the possible spatial variation of ice

thickness. To do that, sub-sampled CDF analyses were completed for each ice sample within each

percentile’s confidence interval. For example, if a day’s range was 2-4 inches, the length of within-region

spatial range for that day was 2 inches. For the subsampled CDFs, we chose those daily thickness ranges

whose mid-points were located within Rubin’s confidence interval for a specific percentile. We then

retrieved the median of the length of those thickness ranges for that percentile; and so on for the other

percentiles. We regard this median as a representative range for the spatial variation of ice thickness for

each percentile (Table 5).

For instance, after doing the imputed CDF, we get a result that there are 95% possibility that thickness

will be less than 10 inches, and Rubin’s 95% variational confidence interval for that percentile is from 9 in

to 11 in. Then we find those thickness range whose mid-point was located between 9-11 inches and find

out the length of these thickness ranges. They may be, for example, [2 in, 4 in, 4 in, 5 in, 9 in]. The median

Variational

C.I. from

Rubin Grand

Mean

C.I.


is 4 in. I.e., we have 95% confidence that the representative thickness for that region as a whole will not

exceed 11 inches (the upper limit of the confidence interval) more than 5 winter days in 100. Since this

thickness however may further vary spatially within that region an extra 4 inches, one could say with 95%

confidence that ice thickness will not exceed 15 inches more than 5 winter days in 100 anywhere within

that region. In other words, a conservative value for the 95% percentile would be:

[Upper-95%-C.I. of the 95-percentile] + median 95-percentile range.


APPENDIX B--STATISTICS AND TABLES

Region ID and Name

Table 1: Region ID information. This table lists the stretch of the river corresponding to the Region ID.

This information is displayed in a map in Figure 1.

REGIONID NAME

1 River Stretch: George Washington Bridge to

Tappan Zee Bridge

2 River Stretch: Tappan Zee Bridge to Jones Point

3 River Stretch: Jones Point to West Point

4 Choke Point: West Point

5 River Stretch: West Point to Newburgh

6 River Stretch: Newburgh to Poughkeepsie

7 Choke Point: Crum Elbow

8 Choke Point: Hyde Park Anchorage

9 Choke Point: Esopus Meadows

10 River Stretch: Poughkeepsie to Kingston

11 Choke Point: Silver Point

12 River Stretch: Kingston to Catskill

13 Choke Point: Hudson Anchorage

14 Choke Point: Stuyvesant Anchorage

15 River Stretch: Catskill to Albany

16 River Stretch: Albany to Troy


Ice Occurrence

Table 2: The ice occurrence of different river region. The occurrence based on ice data of 11 ice seasons.

REGION ID OCCURENCE(%)

1 14.5

2 34.5

3 34.9

4 53.7

5 54.8

6 60.9

7 63.9

8 63.6

9 66.3

10 69.2

11 63.7

12 70.8

13 61.5

14 53.7

15 63.8

16 49.6


Ice Types for Every River Region

Table 3: Ice Types of every river region with their respective percent occurrence.

REGION

Drift

(%)

Brash

(%)

Fast

(%)

Plate

(%)

Floe

(%)

Grease

(%)

Frazil

(%)

Slush

(%)

Pancake

(%)

Hummocked

(%)

Rafted

(%)

Skim

(%)

1 92.0 77.4 6.5 11.3 3.2 1.6 1.6 0 0 0 0 0

2 86.2 72.5 15.0 8.5 1.3 2.0 2.0 2.0 2.6 0 0 0

3 88.4 72.9 12.9 8.4 1.9 1.9 1.9 1.9 0.6 0 0 0

4 80.2 73.7 19.4 14.2 2.8 0 0.4 2.0 0.8 0 0 0.4

5 77.4 76.0 23.7 10.8 2.8 0 0.4 2.5 0 0.7 0.4 0

6 82.7 80.8 18.9 8.7 3.3 0 0 1.6 0 0 0.7 0.3

7 79.0 75.4 19.0 11.8 2.0 0.3 2.0 1.3 0.7 0 0 2.0

8 72.1 73.7 24.6 13.8 2.0 0.3 0 1.0 0.7 0 0 1.0

9 64.4 72.8 29.0 17.3 1.2 0 0.3 1.2 0.3 0 0 0.9

10 73.6 73.9 25.0 13.6 2.6 0 0.3 1.4 0.3 0.3 0.3 0

11 63.9 67.9 39.4 18.1 1.1 0 0.4 1.1 0 0 0 1.1

12 65.3 74.1 36.9 12.7 3.3 0 0 0.8 1.1 0 0.3 0.6

13 58.5 71.3 43.8 15.1 2.3 0 0 1.1 0.4 0.4 0 0

14 58.0 73.2 42.4 15.6 1.0 0 0 1.0 0.5 0.5 0 0.5

15 61.6 69.9 39.4 13.0 1.4 0.3 0 0.3 0.3 0 0.7 0.3

16 42.0 44.9 61.4 24.4 0.6 1.1 0 0 0.6 0 0.6 0


Cumulative Distribution Function (CDF) Analysis Result

Table 4: CDF Analysis result for both ice thickness and coverage.

REGION_ID

THICK_50P

(inches)

THICK_75P

(inches)

THICK_90P

(inches)

THICK_95P

(inches)

AREA_50P

(%)

AREA_75P

(%)

AREA_90P

(%)

AREA_95P

(%)

1 2.1 3.1 4.5 5.7 32.5 48.5 65.8 78.6

2 2.6 3.7 5.3 6.5 35 52.8 72.4 86.8

3 2.5 3.7 5.2 6.5 35.4 53.4 73.2 88.6

4 4.0 6.0 8.8 11.1 71.3 94.8 100 100

5 4.1 6.3 9.4 11.9 70.7 86.5 100 100

6 3.7 5.5 7.8 9.8 70.0 84.2 93.5 100

7 3.5 5.5 8.4 11.1 78.1 92.1 100 100

8 3.8 5.9 8.7 11.1 74.1 92.5 100 100

9 4.1 6.3 9.4 12.1 82.6 100 100 100

10 4.1 6.3 9.1 11.5 81.5 92.3 100 100

11 4.3 6.3 8.7 10.4 87.6 100 100 100

12 4.3 6.4 8.9 10.7 80.9 100 100 100

13 4.9 7.1 9.5 11.2 87.8 100 100 100

14 4.1 6.0 8.3 10.0 87.0 100 100 100

15 4.3 6.4 8.8 10.6 78.3 94.8 100 100

16 4.5 6.6 8.8 10.4 100 100 100 100


Spatial Variation of Cumulative Probability

Table 5: Spatial (Within-Region) Variation of Each Cumulative Probability.

REGION ID

RANGE_50

(inches)

RANGE_75

(inches)

RANGE_90

(inches)

RANGE_95

(inches)

1 1.0 2.0 3.0 3.0

2 1.0 2.0 3.0 2.0

3 1.0 2.0 3.5 2.5

4 2.0 4.0 4.0 2.0

5 2.5 4.0 4.0 2.0

6 1.0 4.0 4.0 4.0

7 1.0 4.0 2.0 1.0

8 2.0 4.0 2.0 2.0

9 3.0 3.5 2.0 2.0

10 3.0 4.0 4.0 2.0

11 3.0 4.0 2.0 4.0

12 3.0 3.0 2.0 4.0

13 3.0 2.0 2.5 4.0

14 3.0 3.5 3.0 2.0

15 3.0 3.0 2.0 4.0

16 3.0 2.0 2.5 4.0


Color of Different Ice Type

Table 6: Color of different ice Type.

Ice Type Color

Drift Dark Green

Brash Brown

Fast Orange

Plate Red

Floe Purple


APPENDIX C--PLOTS

Statistical Analysis Plots

Brief explanation of the plots that follow per Hudson Region is given below:

Top panels: Reported ice thickness (inches) and percent ice cover (%) from 2005-2015. Medium panels:

CDF (Cumulative Distribution Function; empirical and GEV-fit) for ice thickness and percent cover. For

ice thickness, dotted lines show the 50% and 95% percentile ice thickness calculated for that region during

days with ice, while horizontal bars show the expected ice thickness ranges for these percentiles. Bottom

panel: Bar chart shows the probability of occurrence for each kind of ice type, based on the reports when

ice was present.


Figure 14: Statistical Analysis for Region 1, George Washington Bridge to Tappan Zee Bridge. In this

region, ice has historically occurred 14.5% of days during the analyzed winter ice seasons. The most

prevalent ice type for this region has been Drift. Based on the statistical analysis described in this report,

conditions with ice thicker than 5.7” (4.2” to 7.2” at the 95% confidence level), and areal ice coverage

greater than 78.6%, are only expected during 5% of days with ice on that river stretch during the winter

ice season, or, equivalently, during only 1 day of an ice season.


Figure 15: Statistical Analysis for Region 2, Tappan Zee-Jones Point. In this region, ice has historically

occurred 34.5% of days during the analyzed winter ice seasons. The most prevalent ice type for this

region has been Drift. Based on the statistical analysis described in this report, conditions with ice thicker

than 6.5” (5.5” to 7.5” at the 95% confidence level), and areal ice coverage greater than 86.8%, are only

expected during 5% of days with ice on that river stretch during the winter ice season, or, equivalently,

during only 2 days of an ice season.


Figure 16: Statistical Analysis for Region 3, Jones Point-West Point. In this region, ice has historically


region has been Drift. Based on the statistical analysis described in this report, conditions with ice thicker

than 6.5” (5.25” to 7.75” at the 95% confidence level), and areal ice coverage greater than 88.6%, are only

expected during 5% of days with ice on that river stretch during the winter ice season, or, equivalently,

during only 2 days of an ice season.


Figure 17: Statistical Analysis for Region 4, Choke Point: West Point. In this region, ice has historically

occurred 53.7% of days during the analyzed winter ice seasons (Note: data were only available after

December 2007). The most prevalent ice type for this region has been Drift, though Brash ice has also

occurred with similar frequency. Based on the statistical analysis described in this report, conditions with

ice thicker than 11.1” (10.1” to 12.1” at the 95% confidence level), are only expected during 5% of days

with ice on that river stretch during the winter ice season, or, equivalently, during only 3 days of an ice

season. When ice is present, it may fill that region from bank to bank, (100% ice cover), 23.5% of the time

on average, or, equivalently, during 14 days of an ice season.


Figure 18: Statistical Analysis for Region 5, West Point-Newburgh. In this region, ice has historically


region has been Drift, though Brash ice has also occurred with similar frequency. Based on the statistical

analysis described in this report, conditions with ice thicker than 11.9” (10.9” to 12.9” at the 95%

confidence level), are only expected during 5% of days with ice on that river stretch during the winter ice

season, or, equivalently, during only 3 days of an ice season. When ice is present, it may fill that region

from bank to bank, (100% ice cover), 13% of the time on average, or, equivalently, during 8 days of an ice

season.


Figure 19: Statistical Analysis for Region 6, Newburgh-Poughkeepsie. In this region, ice has historically


region has been Drift, though Brash ice has also occurred with similar frequency. Based on the statistical

analysis described in this report, conditions with ice thicker than 9.8” (7.8” to 11.8” at the 95% confidence

level), are only expected during 5% of days with ice on that river stretch during the winter ice season, or,

equivalently, during only 3 days of an ice season. When ice is present, it may fill that region from bank to

bank, (100% ice cover), 8% of the time on average, or, equivalently, during 5 days of an ice season.


Figure 20: Statistical Analysis for Region 7, Choke Point: Crum Elbow. In this region, ice has historically


December 2005). The most prevalent ice type for this region has been Drift, though Brash ice has also


ice thicker than 11.1” (10.6” to 11.6” at the 95% confidence level), are only expected during 5% of days

with ice on that river stretch during the winter ice season, or, equivalently, during only 3 days of an ice

season. When ice is present, it may fill that region from bank to bank, (100% ice cover), 19% of the time on

average, or, equivalently, during 13 days of an ice season.


Figure 21: Statistical Analysis for Region 8, Choke Point: Hyde Park Anchorage. In this region, ice has

historically occurred 63.6% of days during the analyzed winter ice seasons (Note: data were only

available after December 2005). The most prevalent ice type for this region has been Brash, though Drift

ice has also occurred with similar frequency. Based on the statistical analysis described in this report,

conditions with ice thicker than 11.1” (10.1” to 12.1” at the 95% confidence level), are only expected

during 5% of days with ice on that river stretch during the winter ice season, or, equivalently, during only

3 days of an ice season. When ice is present, it may fill that region from bank to bank, (100% ice cover),

20% of the time on average, or, equivalently, during 14 days of an ice season.


Figure 22: Statistical Analysis for Region 9, Choke Point: Esopus Meadows. In this region, ice has


available after December 2005). The most prevalent ice type for this region has been Brash, though Drift

ice has also occurred with similar frequency. Based on the statistical analysis described in this report,

conditions with ice thicker than 12.1” (11.1” to 13.1” at the 95% confidence level), are only expected

during 5% of days with ice on that river stretch during the winter ice season, or, equivalently, during only

4 days of an ice season. When ice is present, it may fill that region from bank to bank, (100% ice cover),

26% of the time on average, or, equivalently, during 18 days of an ice season.


Figure 23: Statistical Analysis for Region 10, Poughkeepsie-Kingston. In this region, ice has historically


region has been Brash, though Drift ice has also occurred with similar frequency. Based on the statistical

analysis described in this report, conditions with ice thicker than 11.5” (10.5” to 12.5” at the 95%




season.


Figure 24: Statistical Analysis for Region 11, Choke Point: Silver Point. In this region, ice has historically


December 2005). The most prevalent ice type for this region has been Brash, though Drift ice has also


ice thicker than 10.4” (8.4” to 12.4” at the 95% confidence level), are only expected during 5% of days with

ice on that river stretch during the winter ice season, or, equivalently, during only 3 days of an ice season.

When ice is present, it may fill that region from bank to bank, (100% ice cover), 35% of the time on

average, or, equivalently, during 24 days of an ice season.


Figure 25: Statistical Analysis for Region 12, Kingston-Catskill. In this region, ice has historically


region has been Brash. Based on the statistical analysis described in this report, conditions with ice thicker

than 10.7” (8.7” to 12.7” at the 95% confidence level), are only expected during 5% of days with ice on that

river stretch during the winter ice season, or, equivalently, during only 4 days of an ice season. When ice

is present, it may fill that region from bank to bank, (100% ice cover), 28% of the time on average, or,

equivalently, during 21 days of an ice season.


Figure 26: Statistical Analysis for Region 13, Choke Point: Hudson Anchorage. In this region, ice has


available after December 2005). The most prevalent ice type for this region has been Brash. Based on the

statistical analysis described in this report, conditions with ice thicker than 11.2” (9.2” to 13.2” at the 95%




season.


Figure 27: Statistical Analysis for Region 14, Choke Point: Stuyvesant Anchorage. In this region, ice has


available after December 2005). The most prevalent ice type for this region has been Brash. Based on the

statistical analysis described in this report, conditions with ice thicker than 10.0” (9.0” to 11.0” at the 95%




season.


Figure 28: Statistical Analysis for Region 15, Catskill-Albany. In this region, ice has historically occurred

63.8% of days during the analyzed winter ice seasons. The most prevalent ice type for this region has

been Brash, though Drift ice has also occurred with similar frequency. Based on the statistical analysis

described in this report, conditions with ice thicker than 10.6” (8.6” to 12.6” at the 95% confidence level),

are only expected during 5% of days with ice on that river stretch during the winter ice season, or,

equivalently, during only 3 days of an ice season. When ice is present, it may fill that region from bank to

bank, (100% ice cover), 23% of the time on average, or, equivalently, during 16 days of an ice season.


Figure 29: Statistical Analysis for Region 16, Albany-Troy. In this region, ice has historically occurred

49.6% of days during the analyzed winter ice seasons. The most prevalent ice type for this region has

been Fast Ice. Based on the statistical analysis described in this report, conditions with ice thicker than

10.4” (8.4” to 12.4” at the 95% confidence level), are only expected during 5% of days with ice on that

river stretch during the winter ice season, or, equivalently, during only 3 days of an ice season. When ice

is present, it may fill that region from bank to bank, (100% ice cover), 50% of the time on average, or,

equivalently, during 27 days of an ice season.


Climatology Analysis Plots


Mean Low (in) 0.0 0.1 0.5 0.4 0.2 0.2 0.0

Mean High (in) 0.0 0.2 0.9 0.8 0.5 0.4 0.0

Record High (in)


3.0

(2010)

3.0

(2014)

8.0

(2009)

6.0

(2005/2015)

6.0

(2015)

6.0

(2015)

0.0

Mean Coverage (%) 0.1 2.8 11.1 10.7 6.3 2.1 0.0

Figure 30: Region 1 in general has the lowest ice thickness and coverage of any of the 16 analyzed Tidal

Hudson River regions, as it is further south near the New York / New Jersey Harbor and has saline

estuarine waters.



Mean Low (in) 0.1 0.8 1.0 1.1 0.6 0.5 0.2

Mean High (in) 0.1 1.2 2.0 2.2 1.1 1.0 0.3

Record High (in)


3.0

(2010)

18.0

(2010)

8.0

(2011)

8.0

(2011)

8.0

(2005/2015)

8.0

(2015)

2.0

(2014)

Mean Coverage (%) 0.3 19.3 25.1 22.1 7.9 6.4 1.6

Figure 31: For region 2, the thickest ice appears in Early January. On average, the ice has been thicker in

Late January and Early February. In terms of coverage, the most ice coverage appears in Late January.

Mean ice prevalent types are Drift and Brash.



Mean Low (in) 0.1 0.9 1.1 1.0 0.6 0.5 0.2

Mean High (in) 0.1 1.3 2.1 2.1 1.0 1.0 0.3

Record High (in)


3.0

(2010)

18.0

(2010)

8.0

(2009)

8.0

(2011)

8.0

(2005 /2015)

8.0

(2015)

2.0

(2014)

Mean Coverage (%) 0.3 20.6 25.0 22.7 8.3 6.4 1.6


Late January and Early February. In terms of coverage, the most ice coverage appears in Late January.

Mean ice prevalent types are Drift and Brash.



Mean Low (in) 0.1 1.7 2.3 3.2 1.8 2.1 0.6

Mean High (in) 0.2 2.5 3.8 4.9 3.3 3.7 1.0

Record High (in)


5.0

(2010)

12.0

(2010/2011)

12.0

(09/11 /15)

24.0

(2015)

12.0

(2011 /2015)

14.0

(2015)

4.0

(2014)

Mean Coverage (%) 2.7 39.9 48.3 52.8 36.1 32.3 11.8

Figure 33: For region 4, the thickest ice appears in Early February. On average, the ice has been thicker in

Early February. In terms of coverage, the most ice coverage appears in Early February. Mean ice

prevalent types are Drift and Brash.



Mean Low (in) 0.1 1.4 2.7 3.3 2.2 2.1 0.9

Mean High (in) 0.2 2.1 5.0 5.4 3.4 3.4 1.4

Record High (in)


5.0

(2010)

10.0

(2009 /2010)

30.0

(2005)

24.0

(2015)

18.0

(2015)

18.0

(2015)

5.0

(2015)

Mean Coverage (%) 1.8 34.1 52.4 55.7 37.6 28.5 14.7

Figure 34: For region 5, the thickest ice appears in Late January. On average, the ice has been thicker in

Late January and Early February. In terms of coverage, the most ice coverage appears in Early February.

Mean ice prevalent types are Drift, Brash, and Fast.



Mean Low (in) 0.3 1.2 2.8 2.8 2.3 2.5 1.2

Mean High (in) 0.5 2.0 4.9 4.5 3.8 4.2 2.1

Record High (in)


5.0

(2010)

10.0

(2009)

18.0

(2011)

12.0

(2011 /2015)

12.0

(2015)

24.0

(2015)

6.0

(2015)

Mean Coverage (%) 7.3 33.8 55.1 56.7 51.2 34.5 25.0

Figure 35: For region 6, the thickest ice appears in Early March. On average, the ice has been thicker in

Late January. In terms of coverage, the most ice coverage appears in Early February. Mean ice prevalent

types are Drift and Brash.



Mean Low (in) 0.5 2.0 3.0 2.5 2.3 3.5 1.7

Mean High (in) 0.7 2.8 4.9 3.8 3.6 4.8 3.1

Record High (in)


5.0

(2009)

12.0

(2010 /2011)

18.0

(2011)

12.0

(2009 /2015)

12.0

(2009 /2015)

24.0

(2015)

6.0

(2014 /2015)

Mean Coverage (%) 19.4 42.5 64.8 51.1 45.6 43.0 34.0


Late January. In terms of coverage, the most ice coverage appears in Late January. Mean ice prevalent

types are Drift, Brash, and Fast.



Mean Low (in) 0.4 1.9 3.0 3.3 2.2 3.2 1.5

Mean High (in) 0.6 2.7 4.8 5.0 3.7 4.4 3.1

Record High (in)


5.0

(2009/2010)

12.0

(2011)

12.0

(2011)

18.0

(2015)

12.0

(2015)

24.0

(2015)

6.0

(2015)

Mean Coverage (%) 17.4 37.0 64.2 62.6 43.9 39.1 32.4


Early February. In terms of coverage, the most ice coverage appears in Late January. Mean ice prevalent




Mean Low (in) 0.6 2.0 3.4 3.9 2.5 3.6 1.9

Mean High (in) 0.8 2.9 5.2 5.8 3.9 4.8 3.7

Record High (in)


8.0

(2009)

12.0

(2010 /2011)

18.0

(2010 /2011)

24.0

(2013)

14.0

(2009)

20.0

(2015)

6.0

(2015)

Mean Coverage (%) 21.5 45.6 68.5 69.3 52.5 45.5 46.1

Figure 38: For region 9, the thickest ice appears in Early February. On average, the ice has been thicker in


prevalent types are Drift, Brash, Fast, and Plate.



Mean Low (in) 0.6 2.1 3.1 3.8 2.6 3.5 1.8

Mean High (in) 0.9 3.2 5.4 5.6 4.4 5.5 3.8

Record High (in)


8.0

(2009)

16.0

(2010)

13.0

(2010)

12.0

(09/11/15)

12.0

(2009/2015)

24.0

(2015)

6.0

(2015)

Mean Coverage (%) 20.0 43.8 68.6 66.2 57.3 49.6 40.2


Early February. In terms of coverage, the most ice coverage appears in Late January. Mean ice prevalent



Climatology Late Dec Early Jan Late Jan Early Feb Late

Feb Early Mar Late Mar

Mean Low (in) 0.5 1.7 2.7 3.5 2.8 3.1 1.8

Mean High (in) 0.8 2.4 4.5 5.0 4.4 5.0 3.7

Record High (in)


4.0

(2010)

10.0

(2010)

10.0

(09/10/11/15)

12.0

(10/11/15)

12.0

(2015)

16.0

(2015)

6.0

(2015)

Mean Coverage (%) 22.1 43.8 61.7 63.4 53.8 52.1 50.0


Early February and Early March. In terms of coverage, the most ice coverage appears in Early February.




Mean Low (in) 0.5 1.8 3.2 4.0 3.3 2.6 1.7

Mean High (in) 0.9 2.8 5.4 5.8 5.4 4.8 4.3

Record High (in)


5.0

(2010)

10.0

(2010)

24.0

(2011)

12.0

(09/11/15)

18.0

(2011/2015)

16.0

(2015)

8.0

(2015)

Mean Coverage (%) 22.8 49.2 65.3 69.6 60.7 51.8 52.3

Figure 41: For region 12, the thickest ice appears in Late January. On average, the ice has been thicker in





Mean Low (in) 0.5 1.7 2.8 4.1 3.8 2.9 1.7

Mean High (in) 0.6 2.4 4.6 5.9 5.5 4.7 3.0

Record High (in)


4.0

(2010)

10.0

(2010)

13.0

(2010)

16.0

(2010)

12.0

(2009/2015)

16.0

(2015)

7.0

(2014)

Mean Coverage (%) 23.0 39.4 62.4 62.6 57.7 46.6 42.5

Figure 42: For region 13, the thickest ice appears in Early February and Early March. On average, the ice

has been thicker in Early February. In terms of coverage, the most ice coverage appears in Late January

and Early February. Mean ice prevalent types are Drift, Brash, and Fast.



Mean Low (in) 0.5 1.3 1.8 3.3 2.7 2.0 0.8

Mean High (in) 0.5 1.9 3.4 4.7 4.6 3.3 1.4

Record High (in)


3.0

(2010/2013)

8.0

(2009 /2015)

8.0

(09/14/15)

12.0

(10/11/15)

12.0

(2014 /2015)

10.0

(2015)

4.0

(2014 /2015)

Mean Coverage (%) 19.2 36.5 55.1 60.0 47.8 36.4 25.6

Figure 43: For region 14, the thickest ice appears in February. On average, the ice has been thicker in





Mean Low (in) 0.5 1.6 2.6 3.7 2.8 2.3 1.2

Mean High (in) 0.6 2.5 5.1 5.5 4.7 4.4 2.6

Record High (in)


4.0

(2010)

18.0

(2009)

16.0

(2009)

12.0

(2011 /2015)

18.0

(2015)

16.0

(2015)

8.0

(2014)

Mean Coverage (%) 20.7 38.5 60.5 63.3 50.1 38.9 34.3

Figure 44: For region 15, the thickest ice appears in Early January and Late February. On average, the ice

has been thicker in Early February. In terms of coverage, the most ice coverage appears in Early February.




Mean Low (in) 0.2 1.4 1.9 2.5 2.8 1.6 0.6

Mean High (in) 0.4 2.1 3.4 3.9 3.6 2.2 0.8

Record High (in)


4.0

(2010)

18.0

(2009)

16.0

(2009)

12.0

(2015)

10.0

(2005/2009)

12.0

(2015)

6.0

(2014)

Mean Coverage (%) 15.6 46.7 51.1 60.8 46.5 31.8 2.7





APPENDIX D. USCG ICE TYPES, DEFINITIONS AND

PHOTOGRAPHS (PROVIDED BY USCG)

BRASH ICE - Conglomerates of small ice cakes and chunks that have been broken off from other ice

formations. These conglomerations coalesce an<l refreeze into irregularly shaped masses, one to six fed in

diameter, usually with sharp projections Brash ice can extend all the way to the bottom of an ice-congested

waterway.


DRIFT ICE- Any unattached ice formation . Any area of ices other than fast ice.

FAST ICE - Immobilized ice formations. Ice so firmly frozen into place (along the shore or held by islands)

that winds and water currents cannot dislodge the formation.


FLOE - Detached segments of floating ice sheets. The following shows the recognized categories of floe

measurement. Only cake to medium floe ice sheets are found in the Hudson.

Cake Floe (0-20 meters across)

Small Floe (20- l 00 meters across)

Medium Floe (100- 5 00 meters across)

Big Floe (500- 20 00 meters across)


FRAZIL ICE – Fine spicules or ice crystals that float freely and individually in the water.

GREASE ICE - Where the water surface is completely covered by frazil but the ice crystals have not yet

begun to freeze together. The surface has a greasy, matte appearance and may look like an oil slick.


HUMMOCKED - Pressure-formed piles of ice usually jagged in appearance.

ICE EDGE -The boundary, at any given time, of the open sea and ice of any kind, whether drifting or fast.


PLATE ICE - Flat ice with approximately uniform thickness and without ridges/windrows.

PANCAKE ICE - Predominantly circular pieces of ice. Pieces are one to eight feet across with raised rims

resulting from the pieces striking against one another.


PRESSURE RIDGE - A line or wall of broken ice forced upward and downward by pressure. This is

usually formed when two floes collide with each other.

RAFTED ICE - A type of ice formed by one floe overriding another. Some parts of the overlap will trap

water, which may freeze and cement the two floes together. Other parts will trap air and take on

characteristic white appearance.

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