GNET in Regional Atmospheric Models David Bromwich, Marco Tedesco, Mike Bevis, and Steve Businger GNET Workshop: 25 Jan 2017

Thoughts from David Bromwich on the GPS Network (GNET) BENEFITS High temporal resolution (10-15 min. intervals) European studies for convection in summer show assimilating GPS ZTD improves the prediction of large (extreme) precipitation events How do these results translate to the Greenland environment? Greenland events of interest that may profit from GPS ZTD assimilation: synoptic-scale cyclones, fronts, hurricane remnants in late summer, lee cyclones east of Cape Farewell, cold air outbreaks…

The Greenland Environment

Greenland GPS Network (GNET) ISSUES Reliability: Precipitable Water (PW) values are very low (a few mm in cold season in N. Greenland); not much larger than the accuracy of PW from GPS ZTD. Robust Siting: Set up for geodetic purposes, not necessarily optimal for meteorology Complex flow: A challenge for this vertically integrated quantity - PW (valleys vs peaks; sheltering effects; multilevel flows) Harsh Conditions: Inaccurate during icing conditions – needs a robust quality control procedure Need Additional Information: Atmospheric motion fields of comparable detail (e.g., GC-Net) and accuracy to GNET. The dry delay is related to surface pressure thus greatly assisting the accurate definition of the motion fields. Thus, GNET is an untapped opportunity for research by graduate students – data need comprehensive evaluation. Greenland GPS Network (GNET)

Intense Barrier Wind in Denmark Strait @ 15 km – Hi. Res. is Key. Greenland Greenland North North Iceland Iceland ASR 15km ASR 30km Wind Speed m/s 03UTC Mar 03, 2007

Arctic System Reanalysis (ASR) Regional reanalysis of the Greater Arctic (2000-2012, currently) Includes major Arctic rivers and NH storm tracks Will be updated through 2016 later in 2017 for v2. Uses Polar WRF with WRFDA (3D-VAR) Two Versions ASRv1-30km & ASRv2-15 km 71 Vertical Levels (1st level – 4m) 3h output Bromwich et al. 2016 QJRMS ASRv1 30 km available online at the NCAR CISL Research Data Archive ASRv2 – 15 km Coming Very Soon!

ASRv3: The Next Generation Same domain and horizontal resolution (15 km) Vertical levels: up to 100 total Period: 1979-2020 Nested within ERA5 global reanalysis Atmospheric assimilation: Hybrid-ensemble 3D-VAR possibly 4D-Var New land surface model optimized for Greenland Assimilate GNET and GC-Net data for Greenland to improve surface mass balance Our research motivation: Pan-Arctic extreme weather and climate; Greenland SMB. Proposed to NSF late 2016

Thoughts from Marco Tedesco Surface mass balance (SMB) plays a crucial role in modulating the contribution of the Greenland ice sheet (GrIS) to sea level rise, and recent work suggests that the role of SMB is becoming increasingly important. a NASA-sponsored workshop was held at the Lamont Doherty Earth Observatory (LDEO) of Columbia University on 7-9 September 2016 to provide guidance to the scientific community and funding agencies on actions to be undertaken for reducing uncertainties of SMB estimates of the GrIS The workshop participants engaged in discussions to address key questions such as: Which parameters most affect SMB and how well can we model their current and historical evolution? Which measurements are currently available to constrain these parameters? What are the uncertainties associated with estimates of the parameters identified above and how are they spatially and temporally distributed? Which measurements are most needed and where?

Four major themes Four priorities emerged to be addressed to reduce uncertainty of GrIS SMB Processes, resolution, initialization, and feedbacks. Mention important processes for antarctica…. Modeling Ice Sheet Change Tedesco et al. (2016)

A highlight from the workshop "Interest was also expressed in formally collaborating with atmospheric modelers or cloud physics specialists to better understand and represent the processes associated with snow accumulation and albedo."

Improvements in accumulation Higher Resolution Example: annual snowfall in 1996 (units mmWE/yr) simulated by MAR at a resolution of 10 km vs MAR at 20km, 30km, 35km vs. ice core higher resolution, this bias is a lot reduced.

Thoughts from Mike Bevis on Assimilating ZTD using 4DVar The observational constraints are applied where (3DVar) and also when (4DVar) each measurements is made. 4DVar is now widely used in meteorology, also in oceanography, and is beginning to be used with ice sheet models. from Bennitt and Jupp (2012) Mon. Weath. Rev.

The quiet revolution of numerical weather prediction Peter Bauer, Alan Thorpe and Gilbert Brunet (2015) Nature Ensemble 4DVar (En4DVar) Operational implementation of 4D variational data assimilation techniques (based on optimal control theory) represents a major milestone in global NWP. The R&D preceding operational deployment was often >10 years. 4DVar was first developed in Europe: ECMWF 1997 Météo France 2000 UK Met Office 2004 Japan 2005 Envir. Canada 2005 US NRL 2009 Schematic of the ensemble analysis of forecast cycle.

Nested Grids Meteorologists use multi-scale nested grids for the modeling of weather and climate In Greenland and the Arctic, regional atmospheric models (e.g. RACMO2, MAR and HIRLAM) are embedded in an ECMWF reanalysis/global model (e.g., ERA-Interim or the operational model at ~9km horizontal grid spacing)

Example of a regional model High Resolution Limited Area Model (HIRLAM) HIRLAM is a synoptic scale (5-15 km horizontal resolution) hydrostatic grid scale model with a 4DVar data assimilation scheme (Huang et al., 2002.) HIRLAM can assimilate all conventional observations, a wide range of satellite observations, radar, wind profile and scatterometer data and GPS zenith total delay (GPS ZTD). Initial and boundary conditions are normally taken from the ECMWF model or from a larger scale HIRLAM model. The HIRLAM consortium: Météo France is an associate member of this consortium. Météo France and the UK Met Office have their own high resolution, regional atmospheric models, and they too have highly developed 4DVar modules

Demonstrated impacts of assimilating GPS delay data (usually ZTD) While GPS ZTD has long been used with regional atmospheric models for Cal/Val purposes, nearly all ZTD assimilation studies have documented a positive impact on predictive skill. Nearly all of these studies have been performed in Europe and Japan. Typically GPS ZTD data comprises only a small fraction of the data being assimilated, but adding the ZTD data has been shown to improve the regional atmospheric models’ representations of humidity and precipitation, and it often improves in addition the representation of clouds, surface radiation and surface temperature.

Steve Businger’s Agenda Steve Businger was a co-founder of ground-based GPS meteorology (along with M. Bevis and others) in the 1990s. His group runs an operational NWP program in Hawaii. Steve proposes to acquire a copy of HIRLAM from Europe, to set up a reanalysis system largely focused on Greenland from 2000-present. This will assimilate GNET ZTD time series computed by Bevis at OSU, along with all met data assimilated operationally at ECMWF that lies within the HIRLAM model domain. This will assess the possible impact of GNET ZTD data on regional atmospheric models such as MAR and RACMO2.