Quantifying rainfall in Greenland: a combined observational and modelling approach

AbstractThis paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in-situ precipitation gauge measurements to seven different precipitation phase schemes to separate rain- and snowfall amounts. To correct the resulting snow/rain fractions for undercatch, we subsequently use a Dynamic Correction Model (DCM) for Automatic Weather Stations (AWS, Pluvio gauges) and a regression analysis correction method for staffed stations (Hellmann gauges). With observations ranging from 5% to 57% for cumulative totals, rainfall accounts for a considerable fraction of total annual precipitation over Greenland’s coastal regions, with the highest rain fraction in the south (Narsarsuaq). Monthly precipitation and rainfall totals are used to evaluate the regional climate model RACMO2.3. The model realistically captures monthly rainfall and total precipitation (R=0.3-0.9), with generally higher correlations for rainfall for which the undercatch correction factors (1.02-1.40) are smaller than those for snowfall (1.27-2.80), and hence the observations more robust. With a horizontal resolution of 5.5 km and simulation period from 1958-present, RACMO2.3 therefore is a useful tool to study spatial and temporal variability of rainfall in Greenland, although further statistical downscaling may be required to resolve the steep rainfall gradients.

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Evaluation of a regional climate model using in situ temperature observations over the Balkan Peninsula

Tellus A Dynamic Meteorology and Oceanography ◽

10.3402/tellusa.v61i3.15556 ◽

2009 ◽

Author(s):

E. Kostopoulou ◽

K. Tolika ◽

I. Tegoulias ◽

C. Giannakopoulos ◽

S. Somot ◽

...

Keyword(s):

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Balkan Peninsula ◽

Temperature Observations

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Validation of the HIRHAM-Simulated Indian Summer Monsoon Circulation

Advances in Meteorology ◽

10.1155/2010/415632 ◽

2010 ◽

Vol 2010 ◽

pp. 1-14 ◽

Cited By ~ 15

Author(s):

Stefan Polanski ◽

Annette Rinke ◽

Klaus Dethloff

Keyword(s):

Summer Monsoon ◽

Climate Model ◽

Regional Climate ◽

Horizontal Resolution ◽

Monsoon Circulation ◽

Data Sets ◽

Data Set ◽

Topographic Features ◽

Temperature And Precipitation ◽

Simulated Precipitation

The regional climate model HIRHAM has been applied over the Asian continent to simulate the Indian monsoon circulation under present-day conditions. The model is driven at the lateral and lower boundaries by European reanalysis (ERA40) data for the period from 1958 to 2001. Simulations with a horizontal resolution of 50 km are carried out to analyze the regional monsoon patterns. The focus in this paper is on the validation of the long-term summer monsoon climatology and its variability concerning circulation, temperature, and precipitation. Additionally, the monsoonal behavior in simulations for wet and dry years has been investigated and compared against several observational data sets. The results successfully reproduce the observations due to a realistic reproduction of topographic features. The simulated precipitation shows a better agreement with a high-resolution gridded precipitation data set over the central land areas of India and in the higher elevated Tibetan and Himalayan regions than ERA40.

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An Assessment of Observed and Simulated Temperature Variability in Sierra de Guadarrama (Spain)

10.5194/egusphere-egu21-6358 ◽

2021 ◽

Author(s):

Cristina Vegas Cañas ◽

J. Fidel González Rouco ◽

Jorge Navarro Montesinos ◽

Elena García Bustamante ◽

Etor E. Lucio Eceiza ◽

...

Keyword(s):

Western Europe ◽

Climate Model ◽

Regional Climate ◽

Monitoring Network ◽

Horizontal Resolution ◽

Temperature Variability ◽

Added Value ◽

Seasonal Temperature ◽

Temperature Trends ◽

Highly Correlated

This work provides a first assessment of temperature variability from interannual to multidecadal timescales in Sierra de Guadarrama, located in central Spain, from observations and regional climate model (RCM) simulations. Observational data are provided by the Guadarrama Monitoring Network (GuMNet; www.ucm.es/gumnet) at higher altitudes, up to 2225 masl, and by the Spanish Meteorological Agency (AEMet) at lower sites. An experiment at high horizontal resolution of 1 km using the Weather Research and Forecasting (WRF) RCM, feeding from ERA Interim inputs, is used. Through model-data comparison, it is shown that the simulations are annually and seasonally highly representative of the observations, although there is a tendency in the model to underestimate observational temperatures, mostly at high altitudes. Results show that WRF provides an added value in relation to the reanalysis, with improved correlation and error metrics relative to observations.The analysis of temperature trends shows a warming in the area during the last 20 years, very significant in autumn. When spanning the analysis to the whole observational period, back to the beginning of the 20th century at some sites, significant annual and seasonal temperature increases of 1&#8451;/decade develop, most of them happening during de 1970s, although not as intense as during the last 20 years.The temporal variability of temperature anomalies in the Sierra de Guadarrama is highly correlated with the temperatures in the interior of the Iberian Peninsula. This relationship can be extended broadly over south-western Europe.

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Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

Atmosphere ◽

10.3390/atmos9070262 ◽

2018 ◽

Vol 9 (7) ◽

pp. 262 ◽

Cited By ~ 4

Author(s):

Coraline Wyard ◽

Sébastien Doutreloup ◽

Alexandre Belleflamme ◽

Martin Wild ◽

Xavier Fettweis

Keyword(s):

Cloud Cover ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Regional Climate Models ◽

Horizontal Resolution ◽

Radiative Flux ◽

Added Value ◽

Historical Trends ◽

The Mean

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

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Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽

10.3390/atmos12121543 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1543

Author(s):

Reinhardt Pinzón ◽

Noriko N. Ishizaki ◽

Hidetaka Sasaki ◽

Tosiyuki Nakaegawa

Keyword(s):

Regional Climate Model ◽

Air Temperature ◽

General Circulation ◽

Climate Model ◽

Regional Climate ◽

Surface Air Temperature ◽

Circulation Model ◽

Horizontal Resolution ◽

Temperature And Precipitation ◽

Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

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Assessing the Effects of Spatial Resolution on Regional Climate Model Simulated Summer Temperature and Precipitation in China: A Case Study

Advances in Meteorology ◽

10.1155/2016/7639567 ◽

2016 ◽

Vol 2016 ◽

pp. 1-12 ◽

Cited By ~ 4

Author(s):

Xin-Min Zeng ◽

Ming Wang ◽

Yujian Zhang ◽

Yang Wang ◽

Yiqun Zheng

Keyword(s):

Regional Climate Model ◽

South China ◽

Climate Model ◽

Regional Climate ◽

Surface Air Temperature ◽

Northern China ◽

Horizontal Resolution ◽

Vertical Resolution ◽

Humid Climate ◽

Entire Area

The regional climate model, RegCM3, is used to simulate the 2004 summer surface air temperature (SAT) and precipitation at different horizontal (i.e., 30, 60, and 90 km) and vertical resolutions (i.e., 14, 18, and 23 layers). Results showed that increasing resolution evidently changes simulated SATs with regional characteristics. For example, simulated SATs are apparently better produced when horizontal resolution increases from 60 to 30 km under the 23 layers. Meanwhile, the SATs over the entire area are more sensitive to vertical resolution than horizontal resolution. The subareas present higher sensitivities than the total area, with larger horizontal resolution effects than those of vertical resolution. For precipitation, increasing resolution shows higher impact compared to SAT, with higher sensitivity induced by vertical resolution than by horizontal resolution, especially in rainy South China. The best SAT/precipitation can be produced only when the horizontal and vertical resolutions are reasonably configured. This indicates that different resolutions lead to different atmospheric thermodynamic states. Because of the dry climate and low soil heat capacity in Northern China, resolution changes easily modify surface energy fluxes, hence the SAT; due to the rainy and humid climate in South China, resolution changes likely strongly influence grid-scale structure of clouds and therefore precipitation.

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PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5

10.5194/gmd-2021-315 ◽

2021 ◽

Author(s):

Charles Pelletier ◽

Thierry Fichefet ◽

Hugues Goosse ◽

Konstanze Haubner ◽

Samuel Helsen ◽

...

Keyword(s):

Sea Ice ◽

Climate Model ◽

Regional Climate ◽

Ice Sheet ◽

Horizontal Resolution ◽

Fine Tuning ◽

Polar Regions ◽

Surface Mass ◽

The Impact ◽

Fully Coupled

Abstract. We introduce PARASO, a novel five-component fully-coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are here run at an horizontal resolution close to 1/4°. One key-feature of this tool resides in a novel two-way coupling interface for representing ocean – ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM – f.ETISh surface mass exchanges. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO – f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled two-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

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Sensitivity of an Arctic regional climate model to the horizontal resolution during winter: implications for aerosol simulation

International Journal of Climatology ◽

10.1002/joc.1205 ◽

2005 ◽

Vol 25 (11) ◽

pp. 1455-1471 ◽

Cited By ~ 6

Author(s):

Eric Girard ◽

Biljana Bekcic

Keyword(s):

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Horizontal Resolution

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Climate model bias correction for nonstationary conditions

Canadian Journal of Civil Engineering ◽

10.1139/cjce-2018-0692 ◽

2020 ◽

Vol 47 (3) ◽

pp. 326-336

Author(s):

Mohammad Madani ◽

Vinod Chilkoti ◽

Tirupati Bolisetti ◽

Rajesh Seth

Keyword(s):

Bias Correction ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Bias Reduction ◽

Historical Period ◽

Monthly Precipitation ◽

Model Bias ◽

New Methods ◽

Climate Model Bias

In most of the climate change impact assessment studies, climate model bias is considered to be stationary between the control and scenario periods. Few methods are found in the literature that addresses the issue of nonstationarity in correcting the bias. To overcome the shortcomings reported in these approaches, three new methods of bias correction (NBC_μ, NBC_σ, and NBC_bs) are presented. The methods are improvised versions of previous techniques relying on distribution mapping. The methods are tested using split sample approach over 50-year historical period for nine climate stations in Ontario, using six regional climate models. The average bias reduction improvement by new methods, in mean daily and monthly precipitation, was found to be 73.9%, 74.3%, and 77.4%, respectively, higher than that obtained by the previous methods (eQM 67.7% and CNCDFm_NP 64.1%). Thus, the methods are found to be more effective in accounting for nonstationarity in the model bias.

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Large-Scale Atmospheric Drivers of Snowfall on Thwaites Glacier

10.5194/egusphere-egu2020-12441 ◽

2020 ◽

Author(s):

Michelle Maclennan ◽

Jan Lenaerts

Keyword(s):

Temporal Variability ◽

Large Scale ◽

Climate Model ◽

Southern Oscillation ◽

Regional Climate ◽

Southern Annular Mode ◽

Spatial And Temporal Variability ◽

Atmospheric Conditions ◽

Amundsen Sea ◽

Weather Patterns

High snowfall events on Thwaites Glacier are a key influencer of its ice mass change. In this study, we diagnose the mechanisms for orographic precipitation on Thwaites Glacier by analyzing the atmospheric conditions that lead to high snowfall events. A high-resolution regional climate model, RACMO2, is used in conjunction with MERRA-2 and ERA5 reanalysis to map snowfall and associated atmospheric conditions over the Amundsen Sea Embayment. We examine these conditions during high snowfall events over Thwaites Glacier to characterize the drivers of the precipitation and their spatial and temporal variability. Then we examine the seasonal differences in the associated weather patterns and their correlations with El Nino Southern Oscillation and the Southern Annular Mode. Understanding the large-scale atmospheric drivers of snowfall events allows us to recognize how these atmospheric drivers and consequent snowfall climatology will change in the future, which will ultimately improve predictions of accumulation on Thwaites Glacier.

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