Polar WRF V4.1.1 simulation and evaluation for the Antarctic and Southern Ocean

Jianjun XUE , Ziniu XIAO , David H. BROMWICH , Lesheng BAI

Front. Earth Sci. ›› 2022, Vol. 16 ›› Issue (4) : 1005 -1024.

PDF (12613KB)
Front. Earth Sci. ›› 2022, Vol. 16 ›› Issue (4) : 1005 -1024. DOI: 10.1007/s11707-022-0971-8
RESEARCH ARTICLE
RESEARCH ARTICLE

Polar WRF V4.1.1 simulation and evaluation for the Antarctic and Southern Ocean

Author information +
History +
PDF (12613KB)

Abstract

A recent version of the Polar Weather Research and Forecasting model (Polar WRF) has been upgraded to the version 4.X era with an improved NoahMP Land Surface Model (LSM). To assess the model performance over the Antarctic and Southern Ocean, downscaling simulations with different LSM (NoahMP, Noah), WRF versions (Polar WRF 4.1.1 and earlier version 4.0.3, WRF 4.1.1), and driving data (ERA-Interim, ERA5) are examined with two simulation modes: the short-term that consists of a series of 48 h segments initialized daily at 0000 UTC with the first 24 h selected for model spin-up, whereas the long-term component used to evaluate long-term prediction consists of a series of 38−41 day segments initialized using the first 10 days for spin-up of the hydrological cycle and planetary boundary layer structure. Simulations using short-term mode driven by ERA-Interim with NoahMP and Noah are selected for benchmark experiments. The results show that Polar WRF 4.1.1 has good skills over the Antarctic and Southern Ocean and better performance than earlier simulations. The reduced downward shortwave radiation bias released with WRF 4.1.1 performed well with PWRF411. Although NoahMP and Noah led to very similar conclusions, NoahMP is slightly better than Noah, particularly for the 2 m temperature and surface radiation because the minimum albedo is set at 0.8 over the ice sheet. Moreover, a suitable nudging setting plays an important role in long-term forecasts, such as reducing the surface temperature diurnal cycle near the coast. The characteristics investigated in this study provide a benchmark to improve the model and guidance for further application of Polar WRF in the Antarctic.

Keywords

Polar WRF / downscaling simulation / performance evaluation / the Antarctic and Southern Ocean

Cite this article

Download citation ▾
Jianjun XUE, Ziniu XIAO, David H. BROMWICH, Lesheng BAI. Polar WRF V4.1.1 simulation and evaluation for the Antarctic and Southern Ocean. Front. Earth Sci., 2022, 16(4): 1005-1024 DOI:10.1007/s11707-022-0971-8

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

AlleyR B, EmanuelK A, ZhangF. ( 2019). Advances in weather prediction. Science, 363( 6425): 342– 344

[2]

BauerP, ThorpeA, BrunetG. ( 2015). The quiet revolution of numerical weather prediction. Nature, 525( 7567): 47– 55

[3]

BerrisfordP DeeD P PoliP BruggeR FieldingM FuentesM KållbergP W KobayashiS UppalaS SimmonsA ( 2011). The ERA-Interim archive Version 2.0. ECMWF

[4]

BracegirdleT J, MarshallG J. ( 2012). The reliability of antarctic tropospheric pressure and temperature in the latest global reanalyses. J Clim, 25( 20): 7138– 7146

[5]

BromwichD H, BaiL, BjarnasonG G. ( 2005). High-resolution regional climate simulations over iceland using Polar MM5*. Mon Weather Rev, 133( 12): 3527– 3547

[6]

BromwichD H, HinesK M, BaiL. ( 2009). Development and testing of polar weather research and forecasting model: 2. Arctic Ocean. J Geophys Res, 114( D8): D08122

[7]

BromwichD H, NicolasJ P, HinesK M, KayJ E, KeyE L, LazzaraM A, LubinD, McFarquharG M, GorodetskayaI V, GrosvenorD P, Lachlan-CopeT, van LipzigN P M. ( 2012). Tropospheric clouds in Antarctica. Rev Geophys, 50( 1): RG1004

[8]

BromwichD H, NicolasJ P, MonaghanA J, LazzaraM A, KellerL M, WeidnerG A, WilsonA B. ( 2013a). Central West Antarctica among the most rapidly warming regions on Earth. Nat Geosci, 6( 2): 139– 145

[9]

BromwichD H, NicolasJ P, MonaghanA J, LazzaraM A, KellerL M, WeidnerG A, WilsonA B. ( 2014). Erratum: corrigendum: Central West Antarctica among the most rapidly warming regions on Earth. Nat Geosci, 7( 1): 76

[10]

BromwichD H OtienoF O HinesK M ManningK W ShiloE ( 2013b). Comprehensive evaluation of polar weather research and forecasting model performance in the Antarctic J Geophys Res D Atmospheres, 118( 2): 274− 292

[11]

BromwichD H, WilsonA B, BaiL, LiuZ, BarlageM, ShihC F, MaldonadoS, HinesK M, WangS H, WoollenJ, KuoB, LinH C, WeeT K, SerrezeM C, WalshJ E. ( 2018). The arctic system reanalysis, Version 2. Bull Am Meteorol Soc, 99( 4): 805– 828

[12]

CassanoJ J, HigginsM E, SeefeldtM W. ( 2011). Performance of the weather research and forecasting model for month-long Pan-Arctic simulations. Mon Weather Rev, 139( 11): 3469– 3488

[13]

ChenS Y, WeeT K, KuoY H, BromwichD H. ( 2014). An impact assessment of GPS radio occultation data on prediction of a rapidly developing cyclone over the Southern Ocean. Mon Weather Rev, 142( 11): 4187– 4206

[14]

DeContoR M, PollardD. ( 2016). Contribution of Antarctica to past and future sea-level rise. Nature, 531( 7596): 591– 597

[15]

GlisanJ M, GutowskiW J Jr, CassanoJ J, HigginsM E. ( 2013). Effects of spectral nudging in WRF on Arctic temperature and precipitation simulations. J Clim, 26( 12): 3985– 3999

[16]

GuoZ, BromwichD H, CassanoJ J. ( 2003). Evaluation of Polar MM5 simulations of antarctic atmospheric circulation. Mon Weather Rev, 131( 2): 384– 411

[17]

HinesK M, BromwichD H. ( 2008). Development and testing of Polar Weather Research and Forecasting (WRF) Model. Part I: Greenland ice sheet meteorology. Mon Weather Rev, 136( 6): 1971– 1989

[18]

HinesK M, BromwichD H. ( 2017). Simulation of late summer Arctic clouds during ASCOS with Polar WRF. Mon Weather Rev, 145( 2): 521– 541

[19]

HinesK M, BromwichD H, BaiL, BitzC M, PowersJ G, ManningK W. ( 2015). Sea ice enhancements to Polar WRF. Mon Weather Rev, 143( 6): 2363– 2385

[20]

HinesK M, BromwichD H, BaiL S, BarlageM, SlaterA G. ( 2011). Development and testing of Polar WRF. Part III: Arctic land. J Clim, 24( 1): 26– 48

[21]

HinesK M BromwichD H WangS H SilberI VerlindeJ LubinD( 2019). Microphysics of summer clouds in central west Antarctica simulated by Polar WRF and AMPS. Atmos Chem Phys Discuss,

[22]

IaconoM J, DelamereJ S, MlawerE J, ShephardM W, CloughS A, CollinsW D. ( 2008). Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J Geophys Res, 113( D13): D13103

[23]

JonesP D, ListerD H. ( 2015). Antarctic near-surface air temperatures compared with ERA-Interim values since 1979. Int J Climatol, 35( 7): 1354– 1366

[24]

JungT BauerP GoesslingH GordonN KlebeS BromwichD Doblas-ReyesF DayJ Fairall C HollandM IversenT LemkeP MillsB NurmiP PerovichD ReidP RenfrewI SmithG SvenssonG TolstykhM. ( 2015). The WWRP Polar Prediction Project (PPP). In: Seamless Prediction of The Earth System: From Minutes to Months, WMO-No. 1156, Geneva, WMO

[25]

KainJ S. ( 2004). The Kain-Fritsch convective parameterization: an update. J Appl Meteorol, 43( 1): 170– 181

[26]

KennicuttM C 2nd, ChownS L, CassanoJ J, LiggettD, MassomR, PeckL S, RintoulS R, StoreyJ W V, VaughanD G, WilsonT J, SutherlandW J. ( 2014). Polar research: six priorities for Antarctic science. Nature, 512( 7512): 23– 25

[27]

KennicuttM C II, ChownS L, CassanoJ J, LiggettD, PeckL S, MassomR, RintoulS R, StoreyJ, VaughanD G, WilsonT J, AllisonI, AytonJ, BadheR, BaesemanJ, BarrettP J, BellR E, BertlerN, BoS, BrandtA, BromwichD, CaryS C, ClarkM S, ConveyP, CostaE S, CowanD, DecontoR, DunbarR, ElfringC, EscutiaC, FrancisJ, FrickerH A, FukuchiM, GilbertN, GuttJ, HavermansC, HikD, HosieG, JonesC, KimY D, LeMaho Y, LeeS H, LeppeM, LeitchenkovG, LiX, LipenkovV, LochteK, López-MartínezJ, LüdeckeC, LyonsW, MarenssiS, MillerH, MorozovaP, NaishT, NayakS, RavindraR, RetamalesJ, RicciC A, Rogan-FinnemoreM, Ropert-CoudertY, SamahA A, SansonL, ScambosT, SchlossI R, ShiraishiK, SiegertM J, SimõesJ C, StoreyB, SparrowM D, WallD H, WalshJ C, WilsonG, WintherJ G, XavierJ C, YangH, SutherlandW J. ( 2015). A roadmap for Antarctic and Southern Ocean science for the next two decades and beyond. Antarct Sci, 27( 1): 3– 18

[28]

KennicuttM C II, KimY D, Rogan-FinnemoreM, AnandakrishnanS, ChownS L, ColwellS, CowanD, EscutiaC, FrenotY, HallJ, LiggettD, McdonaldA J, NixdorfU, SiegertM J, StoreyJ, WåhlinA, WeatherwaxA, WilsonG S, WilsonT, WoodingR, AckleyS, BiebowN, BlankenshipD, BoS, BaesemanJ, CárdenasC A, CassanoJ, DanhongC, DañobeitiaJ, FrancisJ, GuldahlJ, HashidaG, CorbalánL J, KlepikovA, LeeJ, LeppeM, LijunF, López-MartinezJ, MemolliM, MotoyoshiY, BuenoR M, NegreteJ, CárdenesM A O, SilvaM P, Ramos-GarciaS, SalaH, ShinH, ShijieX, ShiraishiK, StockingsT, TrotterS, VaughanD G, DeMenezes J V D U, VlasichV, WeijiaQ, WintherJ G, MillerH, RintoulS, YangH. ( 2016). Delivering 21st century Antarctic and Southern Ocean science. Antarct Sci, 28( 6): 407– 423

[29]

MayewskiP A, MeredithM P, SummerhayesC P, TurnerJ, WorbyA, BarrettP J, CasassaG, BertlerN A N, BracegirdleT, Naveira GarabatoA C, BromwichD, CampbellH, HamiltonG S, LyonsW B, MaaschK A, AokiS, XiaoC, van OmmenT. ( 2009). State of the Antarctic and Southern Ocean climate system. Rev Geophys, 47( 1): RG1003

[30]

Miguez-MachoG, StenchikovG L, RobockA. ( 2004). Spectral nudging to eliminate the effects of domain position and geometry in regional climate model simulations. J Geophys Res D Atmosph, 109: D13104

[31]

MonaghanA, BromwichD. ( 2008). Global warming at the poles. Nat Geosci, 1( 11): 728– 729

[32]

NakanishiM, NiinoH. ( 2009). Development of an improved turbulence closure model for the atmospheric boundary layer. J Meteorol Soc Jpn, 87( 5): 895– 912

[33]

NiuG Y, YangZ L, MitchellK E, ChenF, EkM B, BarlageM, KumarA, ManningK, NiyogiD, RoseroE, TewariM, XiaY. ( 2011). The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J Geophys Res D Atmospheres, 116( D12): D12109

[34]

OlsonJ B KenyonJ S AngevineW A BrownJ M PagowskiM SušeljK ( 2019). A description of the MYNN-EDMF scheme and the coupling to other components in WRF–ARW

[35]

PowersJ G, KlempJ B, SkamarockW C, DavisC A, DudhiaJ, GillD O, CoenJ L, GochisD J, AhmadovR, PeckhamS E, GrellG A, MichalakesJ, TrahanS, BenjaminS G, AlexanderC R, DimegoG J, WangW, SchwartzC S, RomineG S, LiuZ, SnyderC, ChenF, BarlageM J, YuW, DudaM G. ( 2017). The weather research and forecasting model: overview, system efforts, and future directions. Bull Am Meteorol Soc, 98( 8): 1717– 1737

[36]

PowersJ G, ManningK W, BromwichD H, CassanoJ J, CayetteA M. ( 2012). A decade of Antarctic science support through AMPS. Bull Am Meteorol Soc, 93( 11): 1699– 1712

[37]

ScambosT A, BellR E, AlleyR B, AnandakrishnanS, BromwichD H, BruntK, ChristiansonK, CreytsT, DasS B, DeContoR, DutrieuxP, FrickerH A, HollandD, MacGregorJ, MedleyB, NicolasJ P, PollardD, SiegfriedM R, SmithA M, SteigE J, TruselL D, VaughanD G, YagerP L. ( 2017). How much, how fast? A science review and outlook for research on the instability of Antarctica’s Thwaites Glacier in the 21st century. Global Planet Change, 153: 16– 34

[38]

ScottR C, NicolasJ P, BromwichD H, NorrisJ R, LubinD. ( 2019). Meteorological drivers and large-scale climate forcing of West Antarctic surface melt. J Clim, 32( 3): 665– 684

[39]

UrbanM C, BocediG, HendryA P, MihoubJ B, Pe’erG, SingerA, BridleJ R, CrozierL G, DeMeester L, GodsoeW, GonzalezA, HellmannJ J, HoltR D, HuthA, JohstK, KrugC B, LeadleyP W, PalmerS C F, PantelJ H, SchmitzA, ZollnerP A, TravisJ M. ( 2016). Improving the forecast for biodiversity under climate change. Science, 353( 6304): aad8466

[40]

WilsonA B, BromwichD H, HinesK M. ( 2011). Evaluation of Polar WRF forecasts on the Arctic system reanalysis domain: surface and upper air analysis. J Geophys Res, 116( D11): D11112

[41]

WilsonA B, BromwichD H, HinesK M. ( 2012). Evaluation of Polar WRF forecasts on the Arctic System Reanalysis Domain: 2. atmospheric hydrologic cycle. J Geophys Res D Atmosph, 117: D04107

[42]

XueJ, BromwichD H, XiaoZ, BaiL. ( 2021). Impacts of initial conditions and model configuration on simulations of polar lows near Svalbard using Polar WRF with 3DVAR. Q J R Meteorol Soc, 147( 740): 3806– 3834

[43]

ZouX, BromwichD H, NicolasJ P, MontenegroA, WangS H. ( 2019). West Antarctic surface melt event of January 2016 facilitated by föhn warming. Q J R Meteorol Soc, 145( 719): 687– 704

RIGHTS & PERMISSIONS

Higher Education Press

AI Summary AI Mindmap
PDF (12613KB)

2008

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/