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NASA NTRSDate not supplied

Joint Assimilation of Surface, GEO, and LEO CO, NO2, and O3 In Situ and Partial Column/Profile Retrievals with WRF-Chem/DART

Low earth orbiting (LEO) satellites like OMI or TROPOMI and geostationary satellites like TEMPO (to be launched January 2023) provide ozone (O3) retrieval profiles that extend into the stratosphere. Regional models like WRF-Chem generally do not include the stratosphere and have vertical grids that end near the tropopause. This causes difficulties when assimilating O3 retrievals (both column and profile retrievals) because the respective observation forward operators require model O3 profiles that extend into the stratosphere. In this presentation, we look at results from assimilating O3 observation from surface (in situ measurements), multiple LEO (profile retrievals), and GEO (proxy profile retrievals) platforms in as regional model where we use a global chemical transport model (GCTM) to provide O3 upper boundary conditions (BCs) to enable application of the O3 observation forward operators. We will also present results from assimilating O3 retrievals together with carbon monoxide (CO) observations from surface (in situ measurements) and multiple LEO platforms (column and profile retrievals), and nitrogen dioxide (NO2) observations from surface (in situ measurements), multiple LEO (column retrievals), and GEO (proxy column retrievals) platforms. Our joint assimilation experiments show that sometimes the observations complement each, e.g., when assimilating surface and satellite CO or NO2 observations, and sometimes the observations conflict with each other, e.g., when assimilating observations that are biased with respect to other observations (e.g., CO retrievals), or when the assimilation increments conflict due to their chemical interaction (e.g., surface O3 and NO2 retrievals). Results from assimilation of O3 retrieval profiles in regional model are preliminary and will also be discussed in our presentation. Our expectation is that using GCTM O3 as upper BCs in the regional model for evaluation of the O3 forward operator will improve our O3 forecasts. In summary, we will present results from jointly assimilating surface, LEO, and GEO CO, NO2, and O3 in situ and satellite observations in a regional model with dynamic emissions estimation. This study uses proxy GEO observations as a prelude to actual observations because the GEO platform will not be launched until after our presentation.

WRF-Chem/DART↗
NASA NTRS2008

A Three-Dimensional Variational Data Assimilation Scheme for the Regional Ocean Modeling System: Implementation and Basic Experiments

A three-dimensional variational data assimilation scheme for the Regional Ocean Modeling System (ROMS), named ROMS3DVAR, has been described in the work of Li et al. (2008). In this paper, ROMS3DVAR is applied to the central California coastal region, an area characterized by inhomogeneity and anisotropy, as well as by dynamically unbalanced flows. A method for estimating the model error variances from limited observations is presented, and the construction of the inhomogeneous and anisotropic error correlations based on the Kronecker product is demonstrated. A set of single observation experiments illustrates the inhomogeneous and anisotropic error correlations and weak dynamic constraints used. Results are presented from the assimilation of data gathered during the Autonomous Ocean Sampling Network (AOSN) experiment during August 2003. The results show that ROMS3DVAR is capable of reproducing complex flows associated with upwelling and relaxation, as well as the rapid transitions between them. Some difficulties encountered during the experiment are also discussed.

California coastal ocean↗
NASA NTRS2023

Sensitivity of the MAR Regional Climate Model Snowpack to the Parameterization of the Assimilation of Satellite-Derived Wet-Snow Masks on the Antarctic Peninsula

Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production (+66.7 % on average, or +95 Gt), along with a small decrease in surface mass balance (SMB) (−4.5 % on average, or −20 Gt) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will enable the identification of potential issues in modeling near-surface snowpack processes, paving the way for more accurate simulations of snow processes in model projections.

regional climate models↗
DOE OSTI2025

Data-informed grid refinement to improve traveltime accuracy in the regional seismic traveltime (RSTT) model

The regional seismic traveltime (RSTT) model predicts traveltimes of regional seismic phases accounting for 3-D structure of the crust and the upper mantle on a global scale. Previous versions of the RSTT model have been implemented using nodes separated by ∼1° spacing across the globe. A regional-scale study using regional Pn and Pg traveltimes across Israel and the Middle East demonstrated that data driven, systematic grid refinement reduces traveltime residuals and enhances resolution of smaller tectonic features in regions having dense ray coverage. High density Pn ray coverage in the western US, Europe, Middle East and East Asia can likewise provide the resolution that allows systematic global grid refinement of the RSTT model. In this study, we use a large number of Pn ray paths originating from events located with an epicentral location uncertainty of 25 km (GT25) or better. We conduct targeted grid refinements at 1.0°, 0.5°, 0.25° and 0.125° on a global scale, producing a refined RSTT model that yields a 21.6 per cent reduction in median event location error in Europe and the Middle East, when compared with the original global RSTT model presented in Begnaud et al. The new model also resolves finer tectonic structures in regions with high Pn ray density.

58 GEOSCIENCES↗
NASA NTRS2002

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional scale model (with grid size of 20 km) and Goddard Cumulus Ensemble (GCE) model (with 1 km grid size) are used to perform multi-day integration to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during SCSMEX Sensitivity tests on various land surface models, sea surface temperature (SST) variations, and cloud processes are performed to understand the precipitation processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. Cloud processes can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. The GCE-model results captured many observed precipitation characteristics because it used a fine grid size. For example, the model simulated rainfall temporal variation compared quite well to the sounding-estimated rainfall. The results show there are more latent heat fluxes prior to the onset of the monsoon. However, more rainfall was simulated after the onset of the monsoon. This modeling study indicates the latent heat fluxes (or evaporation) have more of an impact on precipitation processes and rainfall in the regional climate model simulations than in the cloud-resolving model simulations. Research is underway to determine if the difference in the grid sizes or the moist processes used in these two models is responsible for the differing influence of surface fluxes an precipitation processes.

Tao, W.-K.↗
NASA NTRS1984

Region-based modeling algorithms for remotely-sensed data

Five algorithms being developed for performing region-based modeling operations on classified remotely-sensed images are described. The first algorithm converts images from standard grid structure into topological grid structure, while the remaining algorithms act upon topologically grid-structured images to perform region-based relabelling, overlaying, distance searching, and neighborhood scanning operations. The use of precomputed topological information, through the use of topological grid structure, makes region-based algorithms highly accessible to earth scientists.

Goldberg, M.↗
NASA NTRS1993

Time-dependent modulation of galactic cosmic rays by merged interaction regions

Models that solve the one-dimensional, solar modulation equation have reproduced the 11-year galactic cosmic ray using functional representations of global merged interaction regions (MIRs). This study extends those results to the solution of the modulation equation with explicit time dependence. The magnetometers on Voyagers 1 and 2 provide local magnetic field intensities at regular intervals, from which one calculates the ratio of the field intensity to the average local field. These ratios in turn are inverted to form diffusion coefficients. Strung together in radius and time, these coefficents then fall and rise with the strength of the interplanetary magnetic field, becoming representations of MIRs. These diffusion coefficients, calculated locally, propagate unchanged from approx. 10 AU to the outer boundary (120 AU). Inside 10 AU, all parameters, including the diffusion coefficient are assumed constant in time and space. The model reproduces the time-intensity profiles of Voyager 2 and Pioneer 10. Radial gradient data from 1982-1990 between Pioneer 10 and Voyager 2 are about the same magnitude as those calculated in the model. It is also shows agreement in rough magnitude with the radial gradient between Pioneer 10 and 1 AU. When coupled with enhanced, time-dependent solar wind speed at the probe's high latitude, as measured by independent observers, the model also follows Voyager 1's time-intensity profile reasonably well, providing a natural source the model also follows Voyager 1's time-intensity profile reasonably well, providing a natural source for the observed negative latitudinal gradients. The model exhibits the 11-year cyclical cosmic ray intensity behavior at all radii, including 1 AU, not just at the location of the spacecraft where the magnetic fields are measured. In addition, the model's point of cosmic ray maximum correctly travels at the solar wind speed, illustrating the well-known propagation of modulation. Finally, at least in the inner heliosphere this model accounts for the delay experienced by lower-rigidity protons in reaching their time-intensity peak. The actual delays in this model, however, are somewhat smaller than the data. In the outer heliosphere the models sees no delays, and the data are ambiguous as to their existence. It appears that strong magnetic field compression regions (merged interaction regions) that are 3-4 times the average field strength can, at least in a helioequatorial band, disrupt effects, such as drifts, that could dominate in quieter magnetic fields. The question remains: Is the heliosphere ever quiet enough to allow such effects to be unambiguously measured, at least in the midlatitudes?

Perko, J. S.↗
DOE OSTI2023

Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model: RegCM

Mitigation of carbonaceous aerosol emissions is expected to provide climate and health co-benefits. The accurate representation of carbonaceous aerosols in climate models is critical for reducing uncertainties in their climate feedback. In this regard, emission fluxes and aerosol life cycle processes are the two primary sources of uncertainties. Here, we demonstrate that the incorporation of a dynamic ageing scheme and emission estimates that are updated for the local sources improves the representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model, RegCM, compared with its default configuration. The respective mean black carbon (BC) and organic carbon (OC) surface concentrations in 2010 are estimated to be 4.25 and 10.35 µg m -3 over the Indo-Gangetic Plain (IGP) in the augmented model. The BC column burden over the polluted IGP is found to be 2.47 mg m -2 , 69.95 % higher than in the default model configuration and much closer to available observations. The anthropogenic aerosol optical depth (AOD) increases by more than 19 % over the IGP due to the model enhancement, also leading to a better agreement with observed AOD. The respective top-of-the-atmosphere, surface, and atmospheric anthropogenic aerosol short-wave radiative forcing are estimated at -0.3, -9.3, and 9.0 W m -2 over the IGP and -0.89, -5.33, and 4.44 W m -2 over Peninsular India (PI). Our results suggest that the combined effect of two modifications leads to maximum improvements in the model performance in regions where emissions play a dominant role.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Climate projections over the Great Lakes Region: using two-way coupling of a regional climate model with a 3-D lake model

Abstract. Warming trends in the Laurentian Great Lakes and surrounding areas have been observed in recent decades, and concerns continue to rise about the pace and pattern of future climate change over the world's largest freshwater system. To date, most regional climate models used for Great Lakes projections either neglected the lake-atmosphere interactions or are only coupled with a 1-D column lake model to represent the lake hydrodynamics. This study presents a Great Lakes climate change projection that has employed the two-way coupling of a regional climate model with a 3-D lake model (GLARM) to resolve 3-D hydrodynamics essential for large lakes. Using the three carefully selected Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs), we show that the GLARM ensemble average substantially reduces surface air temperature and precipitation biases of the driving GCM ensemble average in present-day climate simulations. The improvements are not only displayed from an atmospheric perspective but are also evident in the accurate simulations of lake temperature and ice coverage. We further present the GLARM projected climate change for the mid-21st century (2030–2049) and the late 21st century (2080–2099) in the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. Under RCP 8.5, the Great Lakes basin is projected to warm by 1.3–2.1 ∘C by the mid-21st century and 4.1–5.0 ∘C by the end of the century relative to the early century (2000–2019). Moderate mitigation (RCP 4.5) reduces the mid-century warming to 0.8–1.8 ∘C and late-century warming to 1.8–2.7 ∘C. Annual precipitation in GLARM is projected to increase for the entire basin, varying from 0 % to 13 % during the mid-century and from 9 % to 32 % during the late century in different scenarios and simulations. The most significant increases are projected in spring and fall when current precipitation is highest and a minimal increase in winter when it is lowest. Lake surface temperatures (LSTs) are also projected to increase across the five lakes in all of the simulations, but with strong seasonal and spatial variability. The most significant LST increases occur in Lakes Superior and Ontario. The strongest warming is projected in spring that persists into the summer, resulting from earlier and more intense stratification in the future. In addition, diminishing winter stratification in the future suggests the transition from dimictic lakes to monomictic lakes by the end of the century. In contrast, a relatively smaller increase in LSTs during fall and winter is projected with heat transfer to the deep water due to the strong mixing and energy required for ice melting. Correspondingly, the highest monthly mean ice cover is projected to reduce to 3 %–15 % and 10 %–40 % across the lakes by the end of the century in RCP 8.5 and RCP 4.5, respectively. In the coastal regions, ice duration is projected to decrease by up to 60 d.

Xue, Pengfei (ORCID:000000025702421X)↗
NASA NTRS2001

The Evaluation of the Regional Atmospheric Modeling System in the Eastern Range Dispersion Assessment System

The Applied Meteorology Unit (AMU) evaluated the Regional Atmospheric Modeling System (RAMS) contained within the Eastern Range Dispersion Assessment System (ERDAS). ERDAS provides emergency response guidance for Cape Canaveral Air Force Station and Kennedy Space Center operations in the event of an accidental hazardous material release or aborted vehicle launch. The RAMS prognostic data are available to ERDAS for display and are used to initialize the 45th Space Wing/Range Safety dispersion model. Thus, the accuracy of the dispersion predictions is dependent upon the accuracy of RAMS forecasts. The RAMS evaluation consisted of an objective and subjective component for the 1999 and 2000 Florida warm seasons, and the 1999-2000 cool season. In the objective evaluation, the AMU generated model error statistics at surface and upper-level observational sites, compared RAMS errors to a coarser RAMS grid configuration, and benchmarked RAMS against the nationally-used Eta model. In the subjective evaluation, the AMU compared forecast cold fronts, low-level temperature inversions, and precipitation to observations during the 1999-2000 cool season, verified the development of the RAMS forecast east coast sea breeze during both warm seasons, and examined the RAMS daily thunderstorm initiation and precipitation patterns during the 2000 warm season. This report summarizes the objective and subjective verification for all three seasons.

Case, Jonathan↗
NASA NTRSDate not supplied

Climate Information and Lessons Learned from the NASA Earth eXchange (NEX), Short-term Prediction Research and Transition Center (NASA SPoRT), and the NASA Regional Climate Model Evaluation System (RCMES)

Climate resilience can emerge from a combination of (1) climate projections that enable future-oriented planning and (2) contemporary observations that can be used for adaptation in the face of realized climate. NASA is uniquely positioned to provide global climate projections and satellite-based observations to users who must take a global perspective on climate risk (e.g., supply chain managers). Here, we will share the capabilities and experiences of three NASA projects. The first project, the NASA Earth eXchange (NEX) provides two downscaled climate projections, NEX-GDDP-CMIP6, a global 25 km resolution product, and NEX-DCP30-CMIP6, an 800 m resolution product covering the coterminous U.S. specifically designed for U.S. National Climate Assessment (NCA). NEX also offers land surface products that mirror the twice-daily products provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) but are derived from operational geostationary weather satellite data collected at 5-10 minutes intervals. The second project, the Short-term Prediction Research and Transition Center (SPoRT), was established in 2002 to transition unique NASA satellite products and capabilities to stakeholders to improve decision-making that benefits society. SPoRT provides products and capabilities derived from NASA observations and models to end users in government, academia, and the private sector. SPoRT translates NASA Earth science into actionable solutions reaching over 400 stakeholders across 80 organizations. Finally, the Regional Climate Model Evaluation System (RCMES) is designed to facilitate regional-scale evaluations of climate models by providing standardized access to a vast and comprehensive set of observations, such as satellite, in-situ, and reanalyses, and modeling resources such as CMIP & CORDEX. These three projects form part of the core capabilities at the NASA Centers deliver climate information under the new NASA Earth Science to Action (ES2A) strategy.

NEX↗
DOE OSTI2020

A new spatially distributed added value index for regional climate models: the EURO-CORDEX and the CORDEX-CORE highest resolution ensembles

The added value of using regional climate models (RCMs) to downscale data from general circulation models (GCMs) has often been questioned and researched. Although several studies have used different methods to identify (and in some cases quantify) the added value, there is still a need to find a general metric that quantifies the added value of any variable. This paper builds on past studies to propose a new metric of added value in the simulation of present-day climate which measures the difference in the probability density functions (PDFs) at each grid-cell between a model and an observation source, and then compares the results of the RCM and GCM in order to spatially compute the added value index. The same method is also adapted to quantify the climate change downscaling signal in a way that is consistent with the present-day metric. These new metrics are tested on the daily precipitation output from the EURO-CORDEX and CORDEX-CORE projection ensembles and reveal an overall positive added value of RCMs, especially at the tail-end of the distribution. Higher added value is obtained in areas of complex topography and coast-lines, as well as in tropical regions. Areas with large added value in present-day climate are consistent with areas of significant climate change downscaling signal in the RCP 8.5 far future simulations, and when the analysis is repeated at a low-resolution. The use of different resolution observations shows that the added value tends to decrease when models are compared to low-resolution observation datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida

Abstract The present work evaluates historical precipitation and its indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in suites of dynamically and statistically downscaled regional climate models (RCMs) against NOAA’s Global Historical Climatology Network Daily (GHCN-Daily) dataset over Florida. The models examined here are: (1) nested RCMs involved in the North American CORDEX (NA-CORDEX) program, (2) variable resolution Community Earth System Models (VR-CESM), (3) Coupled Model Intercomparison Project phase 5 (CMIP5) models statistically downscaled using localized constructed analogs (LOCA) technique. To quantify observational uncertainty, three in situ-based (PRISM, Livneh, CPC) and three reanalysis (ERA5, MERRA2, NARR) datasets are also evaluated against the station data. The reanalyses and dynamically downscaled RCMs generally underestimate the magnitude of the monthly precipitation and the frequency of the extreme rainfall in summer. The models forced with CanESM2 miss the phase of the seasonality of extreme precipitation. All models and reanalyses severely underestimate both the mean and interannual variability of mean wet-day precipitation (SDII), consecutive dry days (CDD), and overestimate consecutive wet days (CWD). Metric analysis suggests large uncertainty across NA-CORDEX models. Both the LOCA and VR-CESM models perform better than the majority of models. Overall, RegCM4 and WRF models perform poorer than the median model performance. The performance uncertainty across models is comparable to that in the reanalyses. Specifically, NARR performs poorer than the median model performance in simulating the mean indices and MERRA2 performs worse than the majority of models in capturing the interannual variability of the indices.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Evaluation of the Regional Atmospheric Modeling System in the Eastern Range Dispersion Assessment System

The Applied Meteorology Unit is conducting an evaluation of the Regional Atmospheric Modeling System (RAMS) contained within the Eastern Range Dispersion Assessment System (ERDAS). ERDAS provides emergency response guidance for operations at the Cape Canaveral Air Force Station and the Kennedy Space Center in the event of an accidental hazardous material release or aborted vehicle launch. The prognostic data from RAMS is available to ERDAS for display and is used to initialize the 45th Range Safety (45 SW/SE) dispersion model. Thus, the accuracy of the 45 SW/SE dispersion model is dependent upon the accuracy of RAMS forecasts. The RAMS evaluation task consists of an objective and subjective component for the Florida warm and cool seasons of 1999-2000. The objective evaluation includes gridded and point error statistics at surface and upper-level observational sites, a comparison of the model errors to a coarser grid configuration of RAMS, and a benchmark of RAMS against the widely accepted Eta model. The warm-season subjective evaluation involves a verification of the onset and movement of the Florida east coast sea breeze and RAMS forecast precipitation. This interim report provides a summary of the RAMS objective and subjective evaluation for the 1999 Florida warm season only.

Case, Jonathan↗
DOE OSTI2023

Evaluation of a preliminary regional Earth model through comparison of synthetic and observed waveform data

In this report, we document the process related to developing a regional geologic model of a 605 x 1334 km area centered around Utah and encompassing surrounding states. This model is developed to test the effect that composition of a model has on the generation of synthetic data with the intent of using this information to improve upon full waveform moment tensor inversions. We compare observed data from three seismic events and five stations to the synthetic data generated by a preliminary model derived from a geologic framework model (GFM) developed by the USGS. The synthetic data and observed data comparisons indicate that our preliminary model performs well at smaller offset distances in the northern and central sections of the model. However, the southern stations consistently display synthetic data P- and S-wave arrival times that do not match the observed data arrival times, indicating that the velocity structure of the southern part of the model especially is inaccurate.

58 GEOSCIENCES↗
NASA NTRS1985

Photodissociation regions. I - Basic model. II - A model for the Orion photodissociation region

A theoretical parameter study of the temperature and chemical structure of dense photodissociation regions and their resultant spectrum is presented. Models are discussed which are relevant not only to the dust and gas between molecular clouds and H II regions, but also apply to any neutral cloud illuminated by intense FUV fluxes. The models relate observed line and continuum emission from these regions to physical parameters such as the gas density and temperature, the elemental and chemical abundances, the local radiation field, and the grain properties. The results are applied to observational data from the OMC-1 region. The model shows that the observed high brightness temperature of the C I 609 microns line can be explained by emission from the C(+)/C/CO transition region. This difference with previous chemical models is due to a higher gas phase elemental abundance of carbon, to the charge exchange reactions of C(+) with S and SiO, and to carbon self-shielding.

Tielens, A. G. G. M.↗
NASA NTRS2019

A New Regional Climate Model for POLAR‐CORDEX: Evaluation of a 30‐Year Hindcast with COSMO‐CLM^2 Over Antarctica

Continent‐wide climate information over the Antarctic Ice Sheet (AIS) is important to obtain accurate information of present climate and reduce uncertainties of the ice sheet mass balance response and resulting global sea level rise to future climate change. In this study, the COSMO‐CLM^2 Regional Climate Model is applied over the AIS and adapted for the specific meteorological and climatological conditions of the region. A 30‐year hindcast was performed and evaluated against observational records consisting of long‐term ground‐based meteorological observations, automatic weather stations, radiosoundings, satellite records, stake measurements and ice cores. Reasonable agreement regarding the surface and upper‐air climate is achieved by the COSMO‐CLM^2 model, comparable to the performance of other state‐of‐the‐art climate models over the AIS. Meteorological variability of the surface climate is adequately simulated, and biases in the radiation and surface mass balance are small. The presented model therefore contributes as a new member to the COordinated Regional Downscaling EXperiment project over the AIS (POLAR‐CORDEX) and the CORDEX‐CORE initiative.

Antarctica↗
DOE OSTI2022

Evaluation of simulations of near-surface variables using the regional climate model CCLM for the MOSAiC winter period

The ship-based experiment MOSAiC 2019/2020 was carried out during a full year in the Arctic and yielded an excellent data set to test the parameterizations of ocean/sea-ice/atmosphere interaction processes in regional climate models (RCMs). In the present paper, near-surface data during MOSAiC are used for the verification of the RCM COnsortium for Small-scale MOdel–Climate Limited area Mode (COSMO-CLM or CCLM). CCLM is used in a forecast mode (nested in ERA5) for the whole Arctic with 15 km resolution and is run with different configurations of sea ice data. These include the standard sea ice concentration taken from passive microwave data with around 6 km resolution, sea ice concentration from Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data and MODIS sea ice lead fraction data for the winter period. CCLM simulations show a good agreement with the measurements. Relatively large negative biases for temperature occur for November and December, which are likely associated with a too large ice thickness used by CCLM. The consideration of sea ice leads in the sub-grid parameterization in CCLM yields improved results for the near-surface temperature. ERA5 data show a large warm bias of about 2.5°C and an underestimation of the temperature variability.

54 ENVIRONMENTAL SCIENCES↗