Forecast of low clouds over a snow surface in the Arctic using WRF model

2021 ◽  
Author(s):  
M. Hagman ◽  
G. Svensson ◽  
W.M. Angevine
Keyword(s):  
Forecast Error ◽  
Wrf Model ◽  
Armed Forces ◽  
The Arctic ◽  
Bulk Liquid ◽  
Wave Radiation ◽  
Initial Profile ◽  
Near Surface ◽  
Low Clouds ◽  
Ice Water

AbstractThe Swedish Armed Forces configuration of the Weather Research and Forecasting Model (WRF) has problems in forecasting low clouds in stably stratified conditions when the ground is covered by snow. Reforecasts for January and February 2018, together with observations from Sodankylä in northern Finland, are analyzed to find the cause. The investigation is done iteratively between the Single Column Model (SCM), applied at Sodankylä, and the full 3D version. Our experiments show that the forecast error arises due to inadequate initialization of Stratocumulus (Sc) clouds in WRF using the ECMWF global model, Integrated Forecast System (IFS). By including bulk liquid water and bulk ice water content, from IFS in the initial profile, the downwelling long wave radiation increases and prevents the near surface temperature from dropping abnormally. This, in turn, prevents artificial clouds from forming at the first model level. When no clouds are present in the IFS initial profile, the Sc clouds can be initialized using information from the observed vertical profiles. Generally, initialization of Sc clouds in WRF improves the forecast substantially.

Examination of Errors in Near-Surface Temperature and Wind from WRF Numerical Simulations in Regions of Complex Terrain

2013 ◽  
Vol 28 (3) ◽  
pp. 893-914 ◽  
Author(s):  
Hailing Zhang ◽  
Zhaoxia Pu ◽  
Xuebo Zhang
Keyword(s):  
Complex Terrain ◽  
Forecast Error ◽  
Wrf Model ◽  
Atmospheric Temperature ◽  
Lower Atmosphere ◽  
Forecast Errors ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
System A ◽  
Synoptic Forcing

Abstract The performance of an advanced research version of the Weather Research and Forecasting Model (WRF) in predicting near-surface atmospheric temperature and wind conditions under various terrain and weather regimes is examined. Verification of 2-m temperature and 10-m wind speed and direction against surface Mesonet observations is conducted. Three individual events under strong synoptic forcings (i.e., a frontal system, a low-level jet, and a persistent inversion) are first evaluated. It is found that the WRF model is able to reproduce these weather phenomena reasonably well. Forecasts of near-surface variables in flat terrain generally agree well with observations, but errors also occur, depending on the predictability of the lower-atmospheric boundary layer. In complex terrain, forecasts not only suffer from the model's inability to reproduce accurate atmospheric conditions in the lower atmosphere but also struggle with representative issues due to mismatches between the model and the actual terrain. In addition, surface forecasts at finer resolutions do not always outperform those at coarser resolutions. Increasing the vertical resolution may not help predict the near-surface variables, although it does improve the forecasts of the structure of mesoscale weather phenomena. A statistical analysis is also performed for 120 forecasts during a 1-month period to further investigate forecast error characteristics in complex terrain. Results illustrate that forecast errors in near-surface variables depend strongly on the diurnal variation in surface conditions, especially when synoptic forcing is weak. Under strong synoptic forcing, the diurnal patterns in the errors break down, while the flow-dependent errors are clearly shown.

scholarly journals Improving the WRF model's (version 3.6.1) simulation over sea ice surface through coupling with a complex thermodynamic sea ice model (HIGHTSI)

2016 ◽  
Vol 9 (6) ◽  
pp. 2239-2254 ◽  
Author(s):  
Yao Yao ◽  
Jianbin Huang ◽  
Yong Luo ◽  
Zongci Zhao
Keyword(s):  
Sea Ice ◽  
Heat Budget ◽  
Wrf Model ◽  
The Arctic ◽  
Wave Radiation ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
The Impact ◽  
Ice Model ◽  
Snow And Ice

Abstract. Sea ice plays an important role in the air–ice–ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice scheme, which is the only option in the current Weather Research and Forecasting (WRF) model (version 3.6.1), has a problem of energy imbalance due to its simplification in snow processes and lack of ablation and accretion processes in ice. Validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations, Noah underestimates the sea ice temperature which can reach −10 °C in winter. Sensitivity tests show that this bias is mainly attributed to the simulation within the ice when a time-dependent ice thickness is specified. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) uses more realistic thermodynamics for snow and ice. Most importantly, HIGHTSI includes the ablation and accretion processes of sea ice and uses an interpolation method which can ensure the heat conservation during its integration. These allow the HIGHTSI to better resolve the energy balance in the sea ice, and the bias in sea ice temperature is reduced considerably. When HIGHTSI is coupled with the WRF model, the simulation of sea ice temperature by the original Polar WRF is greatly improved. Considering the bias with reference to SHEBA observations, WRF-HIGHTSI improves the simulation of surface temperature, 2 m air temperature and surface upward long-wave radiation flux in winter by 6, 5 °C and 20 W m−2, respectively. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information results in the best simulation among the available methods. If no observational information is available, we present a new method in which the sea ice thickness is initialized from empirical estimation and its further change is predicted by a complex thermodynamic sea ice model. The ice thickness simulated by this method depends much on the quality of the initial guess of the ice thickness and the role of the ice dynamic processes.

scholarly journals Observations and Modeling of Atmospheric Profiles in the Arctic Seasonal Ice Zone

2015 ◽  
Vol 143 (1) ◽  
pp. 39-53 ◽  
Author(s):  
Zheng Liu ◽  
Axel Schweiger ◽  
Ron Lindsay
Keyword(s):  
Boundary Layer ◽  
Relative Humidity ◽  
Wrf Model ◽  
Specific Humidity ◽  
The Arctic ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Low Level ◽  
The Mean ◽  
Seasonal Ice Zone

Abstract The authors use the Polar Weather Research and Forecasting (WRF) Model to simulate atmospheric conditions during the Seasonal Ice Zone Reconnaissance Survey (SIZRS) in the summer of 2013 over the Beaufort Sea. With the SIZRS dropsonde data, the performance of WRF simulations and two forcing datasets is evaluated: the Interim ECMWF Re-Analysis (ERA-Interim) and the Global Forecast System (GFS) analysis. General features of observed mean profiles, such as low-level temperature inversion, low-level jet (LLJ), and specific humidity inversion are reproduced by all three models. A near-surface warm bias and a low-level moist bias are found in ERA-Interim. WRF significantly improves the mean LLJ, with a lower and stronger jet and a larger turning angle than the forcing. The improvement in the mean LLJ is likely related to the lower values of the boundary layer diffusion in WRF than in ERA-Interim and GFS, which also explains the lower near-surface temperature in WRF than the forcing. The relative humidity profiles have large differences between the observations, the ERA-Interim, and the GFS. The WRF simulated relative humidity closely resembles the forcings, suggesting the need to obtain more and better-calibrated humidity data in this region. The authors find that the sea ice concentrations in the ECMWF model are sometimes significantly underestimated due to an inappropriate thresholding mechanism. This thresholding affects both ERA-Interim and the ECMWF operational model. The scale of impact of this issue on the atmospheric boundary layer in the marginal ice zone is still unknown.

The Arctic System Reanalysis, Version 2

2018 ◽  
Vol 99 (4) ◽  
pp. 805-828 ◽  
Author(s):  
D. H. Bromwich ◽  
A. B. Wilson ◽  
L. Bai ◽  
Z. Liu ◽  
M. Barlage ◽  
...  
Keyword(s):  
Sea Ice ◽  
Land Surface ◽  
Global Climate ◽  
Rapid Change ◽  
Wrf Model ◽  
Arctic Region ◽  
Horizontal Resolution ◽  
The Arctic ◽  
Near Surface ◽  
Environmental Models

AbstractThe Arctic is a vital component of the global climate, and its rapid environmental evolution is an important element of climate change around the world. To detect and diagnose the changes occurring to the coupled Arctic climate system, a state-of-the-art synthesis for assessment and monitoring is imperative. This paper presents the Arctic System Reanalysis, version 2 (ASRv2), a multiagency, university-led retrospective analysis (reanalysis) of the greater Arctic region using blends of the polar-optimized version of the Weather Research and Forecasting (Polar WRF) Model and WRF three-dimensional variational data assimilated observations for a comprehensive integration of the regional climate of the Arctic for 2000–12. New features in ASRv2 compared to version 1 (ASRv1) include 1) higher-resolution depiction in space (15-km horizontal resolution), 2) updated model physics including subgrid-scale cloud fraction interaction with radiation, and 3) a dual outer-loop routine for more accurate data assimilation. ASRv2 surface and pressure-level products are available at 3-hourly and monthly mean time scales at the National Center for Atmospheric Research (NCAR). Analysis of ASRv2 reveals superior reproduction of near-surface and tropospheric variables. Broadscale analysis of forecast precipitation and site-specific comparisons of downward radiative fluxes demonstrate significant improvement over ASRv1. The high-resolution topography and land surface, including weekly updated vegetation and realistic sea ice fraction, sea ice thickness, and snow-cover depth on sea ice, resolve finescale processes such as topographically forced winds. Thus, ASRv2 permits a reconstruction of the rapid change in the Arctic since the beginning of the twenty-first century–complementing global reanalyses. ASRv2 products will be useful for environmental models, verification of regional processes, or siting of future observation networks.

scholarly journals A warm jet in a cold ocean

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jennifer A. MacKinnon ◽  
Harper L. Simmons ◽  
John Hargrove ◽  
Jim Thomson ◽  
Thomas Peacock ◽  
...  
Keyword(s):  
The Arctic ◽  
Bering Strait ◽  
Near Surface ◽  
Ice Melt ◽  
Beaufort Gyre ◽  
The Pacific ◽  
Climate Simulations ◽  
Initial Evolution ◽  
Forecast Models

AbstractUnprecedented quantities of heat are entering the Pacific sector of the Arctic Ocean through Bering Strait, particularly during summer months. Though some heat is lost to the atmosphere during autumn cooling, a significant fraction of the incoming warm, salty water subducts (dives beneath) below a cooler fresher layer of near-surface water, subsequently extending hundreds of kilometers into the Beaufort Gyre. Upward turbulent mixing of these sub-surface pockets of heat is likely accelerating sea ice melt in the region. This Pacific-origin water brings both heat and unique biogeochemical properties, contributing to a changing Arctic ecosystem. However, our ability to understand or forecast the role of this incoming water mass has been hampered by lack of understanding of the physical processes controlling subduction and evolution of this this warm water. Crucially, the processes seen here occur at small horizontal scales not resolved by regional forecast models or climate simulations; new parameterizations must be developed that accurately represent the physics. Here we present novel high resolution observations showing the detailed process of subduction and initial evolution of warm Pacific-origin water in the southern Beaufort Gyre.

Variational Assimilation of Cloud Liquid/Ice Water Path and Its Impact on NWP

2015 ◽  
Vol 54 (8) ◽  
pp. 1809-1825 ◽  
Author(s):  
Yaodeng Chen ◽  
Hongli Wang ◽  
Jinzhong Min ◽  
Xiang-Yu Huang ◽  
Patrick Minnis ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Liquid Water ◽  
Weather Prediction ◽  
Wrf Model ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Water Path ◽  
Ice Water Path ◽  
Ice Water ◽  
The Impact

AbstractAnalysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data assimilation (DA) system for the Weather Research and Forecasting (WRF) Model (WRFDA) is further developed to assimilate satellite cloud products that will produce the cloud liquid water and ice water analysis. Observation operators for the cloud liquid water path and cloud ice water path are developed and incorporated into the WRFDA system. The updated system is tested by assimilating cloud liquid water path and cloud ice water path observations from Global Geostationary Gridded Cloud Products at NASA. To assess the impact of cloud liquid/ice water path data assimilation on short-term regional numerical weather prediction (NWP), 3-hourly cycling data assimilation and forecast experiments with and without the use of the cloud liquid/ice water paths are conducted. It is shown that assimilating cloud liquid/ice water paths increases the accuracy of temperature, humidity, and wind analyses at model levels between 300 and 150 hPa after 5 cycles (15 h). It is also shown that assimilating cloud liquid/ice water paths significantly reduces forecast errors in temperature and wind at model levels between 300 and 150 hPa. The precipitation forecast skills are improved as well. One reason that leads to the improved analysis and forecast is that the 3-hourly rapid update cycle carries over the impact of cloud information from the previous cycles spun up by the WRF Model.

scholarly journals An Evaluation of Surface Atmospheric Changes over the Arctic Ocean for 2000–09 Using Recent Reanalyses

2015 ◽  
Vol 19 (2) ◽  
pp. 1-18 ◽  
Author(s):  
Ayan H. Chaudhuri ◽  
Rui M. Ponte
Keyword(s):  
Arctic Ocean ◽  
Extreme Event ◽  
Longwave Radiation ◽  
Remotely Sensed ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Near Surface ◽  
The Arctic Ocean ◽  
Ice Retreat

Abstract The authors examine five recent reanalysis products [NCEP Climate Forecast System Reanalysis (CFSR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), Japanese 25-year Reanalysis Project (JRA-25), Interim ECMWF Re-Analysis (ERA-Interim), and Arctic System Reanalysis (ASR)] for 1) trends in near-surface radiation fluxes, air temperature, and humidity, which are important indicators of changes within the Arctic Ocean and also influence sea ice and ocean conditions, and 2) fidelity of these atmospheric fields and effects for an extreme event: namely, the 2007 ice retreat. An analysis of trends over the Arctic for the past decade (2000–09) shows that reanalysis solutions have large spreads, particularly for downwelling shortwave radiation. In many cases, the differences in significant trends between the five reanalysis products are comparable to the estimated trend within a particular product. These discrepancies make it difficult to establish a consensus on likely changes occurring in the Arctic solely based on results from reanalyses fields. Regarding the 2007 ice retreat event, comparisons with remotely sensed estimates of downwelling radiation observations against these reanalysis products present an ambiguity. Remotely sensed observations from a study cited herewith suggest a large increase in downwelling summertime shortwave radiation and decrease in downwelling summertime longwave radiation from 2006 and 2007. On the contrary, the reanalysis products show only small gains in summertime shortwave radiation, if any; however, all the products show increases in downwelling longwave radiation. Thus, agreement within reanalysis fields needs to be further checked against observations to assess possible biases common to all products.

scholarly journals Investigating the role of dust in ice nucleation within clouds and further effects on the regional weather system over East Asia – Part II: modification of the weather system

2017 ◽  
Author(s):  
Lin Su ◽  
Jimmy C.H. Fung
Keyword(s):  
Surface Temperature ◽  
East Asia ◽  
South China ◽  
Indirect Effects ◽  
Convective Precipitation ◽  
Wave Radiation ◽  
Direct And Indirect Effects ◽  
Weather System ◽  
Near Surface ◽  
Atmospheric Instability

Abstract. An updated version of the Weather Research and Forecast model coupled with Chemistry (WRF-Chem) was applied to quantify and discuss the full effects of dust on the meteorological field over East Asia during March and April 2012. The performances of the model in simulating the short-wave and long-wave radiation, surface temperature, and precipitation over East Asia are improved by incorporating the effects of dust in the simulations. The radiative forcing induced by the dust-enhanced cloud radiative effect is over one order of magnitude larger than that induced by the direct effect of dust. The semi-direct and indirect effects of dust result in a substantial increase in mid- to high clouds, and a significant reduction in low clouds, leading to a decrease of near-surface temperature and an increase of temperature at the mid- to upper troposphere over East Asia. The spatial redistribution of atmospheric water vapor and modification of the vertical temperature profile over East Asia lead to an inhibition of atmospheric instability over most land areas, but an enhancement of atmospheric instability over South China and the ocean, resulting in a significant inhibition of convective precipitation in areas from central to East China, and a substantial enhancement of convective precipitation over South China. Meanwhile, non-convective precipitation is also reduced significantly over East Asia, as cloud droplets are hindered from growing large enough to form rain droplets, due to the semi-direct and indirect effects of dust. The total precipitation can be reduced or increased by up to 20 % or more.

scholarly journals Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC<sup>4</sup>RS and DISCOVER-AQ airborne campaigns

2017 ◽  
Vol 10 (8) ◽  
pp. 3085-3104 ◽  
Author(s):  
Min Huang ◽  
Gregory R. Carmichael ◽  
James H. Crawford ◽  
Armin Wisthaler ◽  
Xiwu Zhan ◽  
...  
Keyword(s):  
Case Studies ◽  
Air Temperature ◽  
Initial Conditions ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Heat Fluxes ◽  
Aircraft Observation ◽  
Near Surface ◽  
Boundary Layer Height ◽  
Small Scales

Abstract. Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ∼ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

scholarly journals Numerical investigation of the Arctic ice-ocean boundary layer; implications for air-sea gas fluxes

2016 ◽  
Author(s):  
A. Bigdeli ◽  
B. Loose ◽  
S. T. Cole
Keyword(s):  
Sea Ice ◽  
Water Column ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
The Arctic ◽  
Layer Depth ◽  
Near Surface ◽  
Resolution Model ◽  
Simplifying Assumptions ◽  
Vertical Spacing

Abstract. In ice-covered regions it can be challenging to determine air-sea exchange – for heat and momentum, but also for gases like carbon dioxide and methane. The harsh environment and relative data scarcity make it difficult to characterize even the physical properties of the ocean surface. Here, we seek a mechanistic interpretation for the rate of air-sea gas exchange (k) derived from radon-deficits. These require an estimate of the water column history extending 30 days prior to sampling. We used coarse resolution (36 km) regional configuration of the MITgcm with fine near surface vertical spacing (2 m) to evaluate the capability of the model to reproduce conditions prior to sampling. The model is used to estimate sea-ice velocity, concentration and mixed-layer depth experienced by the water column. We then compared the model results to existing field data including satellite, moorings and Ice-tethered profilers. We found that model-derived sea-ice coverage is 88 to 98 % accurate averaged over Beaufort Gyre, sea-ice velocities have 78 % correlation which resulted in 2 km/day error in 30 day trajectory of sea-ice. The model demonstrated the capacity to capture the broad trends in the mixed layer although with a bias and model water velocities showed only 29 % correlation with actual data. Overall, we find the course resolution model to be an inadequate surrogate for sparse data, however the simulation results are a slight improvement over several of the simplifying assumptions that are often made when surface ocean geochemistry, including the use of a constant mixed layer depth and a velocity profile that is purely wind-driven.

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