Pamela G. Posey

Short‐term sea ice forecasting: An assessment of ice concentration and ice drift forecasts using the U.S. Navy's Arctic Cap Nowcast/Forecast System

In this study the forecast skill of the U.S. Navy operational Arctic sea ice forecast system, the Arctic Cap Nowcast/Forecast System (ACNFS), is presented for the period Feb 2014 – June 2015. ACNFS is designed to provide short term, 1-7 day forecasts of Arctic sea ice and ocean conditions. Many quantities are forecast by ACNFS; the most commonly used include ice concentration, ice thickness, ice velocity, sea surface temperature, sea surface salinity, and sea surface velocities. Ice concentration forecast skill is compared to a persistent ice state and historical sea ice climatology. Skill scores are focused on areas where ice concentration changes by ±5% or more, and are therefore limited to primarily the marginal ice zone. We demonstrate that ACNFS forecasts are skillful compared to assuming a persistent ice state, especially beyond 24 hours. ACNFS is also shown to be particularly skillful compared to a climatologic state for forecasts up to 102 hours. Modeled ice drift velocity is compared to observed buoy data from the International Arctic Buoy Programme. A seasonal bias is shown where ACNFS is slower than IABP velocity in the summer months and faster in the winter months. In February 2015 ACNFS began to assimilate a blended ice concentration derived from Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Interactive Multisensor Snow and Ice Mapping System (IMS). Preliminary results show that assimilating AMSR2 blended with IMS improves the short-term forecast skill and ice edge location compared to the independently derived National Ice Center Ice Edge product. This article is protected by copyright. All rights reserved.

Validation of the Global Relocatable Tide/Surge Model PCTides

The Naval Research Laboratory (NRL) has developed a global, relocatable, tide/surge forecast system called PCTides. This system was designed in response to a U.S. Navy requirement to rapidly produce tidal predictions anywhere in the world. The system is composed of a two-dimensional barotropic ocean model driven by tidal forcing only or in conjunction with surface wind and pressure forcing. PCTides is unique in its ability to forecast tidal parameters for a user-specified latitude/longitude domain easily and quickly, and is especially useful in areas where observations are nonexistent. PCTides provides short-term (daily to weekly) predictions of water-level elevation and depth-averaged ocean currents. The system has been tested in numerous regions and validated against observations collected in conjunction with several navy exercises.

The operational evaluation of the Navy's globally relocatable tide model (PCTides)

The U.S. Naval Research Laboratory has developed a globally relocatable tide/surge forecast system. This system runs on a UNIX platform but was designed originally for PC-based use and is referred to as PCTides. The core of the system is a 2-dimensional barotropic ocean model. The model is forced with boundary conditions from a global tide model and uses surface winds and pressures (if available) and/or astronomical forcing. The global ocean bathymetry is a 2-minute global database developed by the Naval Research Laboratory. Atmospheric forcing from the Navys global or regional models is provided through the METCAST system and used to generate real time, wind driven forecasts. PCTides output includes time series of tidal height deviations at each grid point of the model and time series of tidal height deviations at higher frequency (usually 10-12 minutes) at specified point locations. Barotropic tidal currents are also produced by the system. PCTides has successfully completed its operational evaluation performed by the Naval operational centers located in Norfolk, Virginia and San Diego, California. PCTides was run daily in real time to forecast tidal height deviations from regions along the east and west coasts of the United States. The model forecasts were compared to real time observations from the National Oceanic and Atmospheric Administration (NOAA) coastal tide gauges. Results from these evaluations showed an average amplitude error of 15 cm and a phase error of 30 minutes. Specific examples of PCTides hindcasts and forecasts for various areas are presented and discussed.

Real-time Data Assimilation of satellite derived ice concentration into the Arctic Cap Nowcast/Forecast System (ACNFS)

Over the last decade, ice conditions in the Arctic have changed dramatically resulting in the Arctic having a minimum in ice extent during the summers of 2007, 2008 and 2010. With this rapidly changing polar environment, the need for accurate ice forecasts is essential. The Naval Research Laboratory (NRL) has developed the Arctic Cap Nowcast/Forecast System (ACNFS), a two-way coupled ice/ocean system, to forecast ice conditions in the polar regions. This system applies the Los Alamos Community Ice CodE (CICE) coupled via the Earth System Modeling Framework (ESMF) to the HYbrid Coordinate Ocean Model (HYCOM). The Navy Coupled Ocean Data Assimilation (NCODA), a 3-Dimensional VARiational analysis (3DVAR) scheme, is used to assimilate ice and ocean observations into the forecast system. Ice concentration data from two sources: the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and the Advanced Microwave Scanning Radiometer for Earth Observation System (AMSR-E) are used as observations for the ice analysis. Results from the coupled system using both concentration input datasets will be discussed.

Operational use of SSM/I ice concentration in the initialization of a coupled ice-ocean model

The Polar Ice Prediction System (PIPS), the Regional Polar Ice Prediction System - Barents (RPIPS-B) and the Regional Polar Ice Prediction System Greenland Sea (RPIPS-G) are all operational sea ice forecasting systems which have been run daily at the Fleet Numerical Meteorology and Oceanography Center (FNMOC) since September 1987, June 1989 and October 1991, respectively. The basis for all three models is the Hibler ice model. The Hibler ice model calculates ice drift, ice thickness, ice concentration, ice edge and the growth/decay of ice based on both dynamic and thermodynamic effects. The Polar Ice Prediction System 2.0 (PIPS2.O), a new version of PIPS, is presently undergoing its final test phase. PIPS2.0 has been modified into a spherical coordinate version of PIPS and coupled with an ocean model (Cox, 1984). Daily atmospheric fields from the Navy Operational Global Atmospheric Prediction System (NOGAPS) are used to produce a 24-hour forecast. PIPS forecasts over the entire Arctic basin, the Barents Sea and the Greenland/Norwegian Sea using a grid resolution of 127 km. RPIPS-B, a higher resolution version of PIPS, forecasts over the Barents Sea and the western part of the Kara Sea using a grid resolution of 2.5 km. RPIPS-G, another higher resolution version of PIPS, forecasts over the region adjacent to the Fast Greenland coast using a grid resolution of 20 km. PIPS2.0 forecasts over most of the ice-covered regions in the northern hemisphere using a variable grid resolution ranging from 17 to 33 km at the North Pole. By the end of 1994, PIPS2.0 will replace all the existing operational forecast sytems at FNMOC.<<ETX>>

Applications for ICESat-2 Data: From NASA's Early Adopter Program

NASAs Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission, scheduled to launch no later than April 2018 (and currently slated for October 2017), is being developed to continue the multiyear observations of the earths surface elevation, ice, and clouds started by ICESat. To increase the use of the satellite data after launch, the ICESat-2 mission invested in an applications program aimed at innovatively applying the data in a variety of fields. The program provides a framework for building a broad and well-defined user community during the prelaunch period to maximize the use of data products after launch and to provide early insight into the range of potential uses of the mission data. Ideas and research on how altimetry data will be used for decision making arise from the end users; therefore, the ICESat-2 mission is extending itself through its applications program.

Optimization of the High-Frequency Radar Sites in the Bering Strait Region

Monitoring surface currents by coastal high-frequency radars (HFRs) is a cost-effective observational technique with good prospects for further development. An important issue in improving the efficiency of HFR systems is the optimization of radar positions on the coastline. Besides being constrained by environmental and logisticfactors,suchoptimizationhastoaccountforpriorknowledgeoflocalcirculationandthetargetquantities (such as transports through certain key sections) with respect to which the radar positions are to be optimized. In the proposed methodology, prior information of the regional circulation is specified by the solution of the 4D variational assimilation problem, where the available climatological data in the Bering Strait (BS) region are synthesized with dynamical constraints of a numerical model. The optimal HFR placement problem is solved by maximizing the reduction of a posteriori error in the mass, heat, and salt (MHS) transports through the target sections in the region. It is shown that the MHS transports into the Arctic and their redistribution within the Chukchi Sea are best monitored by placing HFRs at Cape Prince of Wales and on Little Diomede Island. Another equally efficient configuration involves placement of the second radar at Sinuk (western Alaska) in place of Diomede. Computations show that 1) optimization of the HFR deployment yields a significant(1.3‐3times)reductionofthetransporterrorscomparedtononoptimalpositioningoftheradarsand2) error reduction provided by two HFRs is an order of magnitude better than the one obtained from three mooringspermanentlymaintainedintheregion for thelast 5yr.Thisresult showsasignificantadvantageofBS monitoringbyHFRs comparedtothemore traditional techniqueofinsitu mooredobservations.The obtained results are validated by an extensive set of observing system simulation experiments.

An evaluation of the PIPS 2.0 ice cover versus SSMI ice concentration from 1992-2000

The Polar Ice Prediction System 2.0 (PIPS 2.0) is a coupled ice-ocean model developed by the Naval Research Laboratory for the prediction of ice thickness, ice drift and ice concentration. The model has been run operationally by the U.S. Navy at the Fleet Numerical Meteorology and Oceanography Center (FNMOC) since the mid-1990s and produces a 120-hour forecast of ice conditions in the Arctic and its marginal seas. PIPS 2.0 is driven by the atmospheric forecast fields from the Navy Operational Global Atmospheric Prediction System (NOGAPS). In an operational mode, PIPS 2.0 assimilates SSMI derived ice concentration each day. In a research mode, the SSMI ice concentration data is not assimilated, rather it is used for model metrics (validation). PIPS 2.0 results are presented as a time series for the period 1992-2000. Model results are correlated to the atmospheric forcing and evaluated against SSMI ice coverage data. In addition, the atmospheric forcing is evaluated against Sheba observations taken in 1997-1998. Biases in the model-derived ice fields directly related to biases in the atmospheric forcing fields.