Boundary condition and oceanic impacts on the atmospheric water balance in limited area climate model ensembles

AbstractRegional climate models (RCMs) are indispensable in climate research, albeit often characterized by biased terrestrial precipitation and water budgets. This study identifies excess oceanic evaporation, in conjunction with the RCMs’ boundary conditions, as drivers contributing to these biases in RCMs with forced sea surface temperatures in a CORDEX RCM ensemble over Europe. The RCMs are relaxed to the prescribed lateral boundary conditions originating from a global model, effectively matching the driving model's overall atmospheric moisture flux divergence. As a consequence, excess oceanic evaporation results in positive precipitation biases over land due to forced internal recycling of moisture to maintain the overall flux divergence prescribed by the boundary conditions. This systematic behaviour is shown through an analysis of long-term atmospheric water budgets and atmospheric moisture exchange between oceanic and continental areas in a multi-model ensemble.

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The Atmospheric Water Balance over the Semiarid Murray–Darling River Basin

Journal of Hydrometeorology ◽

10.1175/2007jhm889.1 ◽

2008 ◽

Vol 9 (3) ◽

pp. 521-534 ◽

Cited By ~ 13

Author(s):

Clara Draper ◽

Graham Mills

Keyword(s):

Surface Water ◽

Water Balance ◽

River Basin ◽

Moisture Flux ◽

Limited Area ◽

Consecutive Series ◽

Atmospheric Water ◽

Flux Divergence ◽

Murray Darling Basin ◽

Moisture Flux Divergence

Abstract The atmospheric water balance over the semiarid Murray–Darling River basin in southeast Australia is analyzed based on a consecutive series of 3- to 24-h NWP forecasts from the Australian Bureau of Meteorology’s Limited Area Prediction System (LAPS). Investigation of the LAPS atmospheric water balance, including comparison of the forecast precipitation to analyzed rain gauge observations, indicates that the LAPS forecasts capture the general qualitative features of the water balance. The key features of the atmospheric water balance over the Murray–Darling Basin are small atmospheric moisture flux divergence (at daily to annual time scales) and extended periods during which the atmospheric water balance terms are largely inactive, with the exception of evaporation, which is consistent and very large in summer. These features present unique challenges for NWP modeling. For example, the small moisture fluxes in the basin can easily be obscured by the systematic errors inherent in all NWP models. For the LAPS model forecasts, there is an unrealistically large evaporation excess over precipitation (associated with a positive bias in evaporation) and unexpected behavior in the moisture flux divergence. Two global reanalysis products (the NCEP Reanalysis I and the 40-yr ECMWF Re-Analysis) also both describe (physically unrealistic) long-term negative surface water budgets over the Murray–Darling Basin, suggesting that the surface water budget cannot be sensibly diagnosed based on output from current NWP models. Despite this shortcoming, numerical models are in general the most appropriate tool for examining the atmospheric water balance over the Murray–Darling Basin, as the atmospheric sounding network in Australia has extremely low coverage.

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Continental-Scale Basin Water Storage Variation from Global and Dynamically Downscaled Atmospheric Water Budgets in Comparison with GRACE-Derived Observations

Journal of Hydrometeorology ◽

10.1175/jhm-d-11-0143.1 ◽

2012 ◽

Vol 13 (5) ◽

pp. 1589-1603 ◽

Cited By ~ 13

Author(s):

Benjamin Fersch ◽

Harald Kunstmann ◽

András Bárdossy ◽

Balaji Devaraju ◽

Nico Sneeuw

Keyword(s):

Large Scale ◽

Amazon Basin ◽

Climate Model ◽

Water Storage ◽

Terrestrial Water Storage ◽

Atmospheric Water ◽

Flux Divergence ◽

Water Budgets ◽

Continental Scale ◽

Terrestrial Water

Abstract Since 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided gravity-derived observations of variations in the terrestrial water storage. Because of the lack of suitable direct observations of large-scale water storage changes, a validation of the GRACE observations remains difficult. An approach that allows the evaluation of terrestrial water storage variations from GRACE by a comparison with those derived from aerologic water budgets using the atmospheric moisture flux divergence is presented. In addition to reanalysis products from the European Centre for Medium-Range Weather Forecasts and the National Centers for Environmental Prediction, high-resolution regional atmospheric simulations were produced with the Weather Research and Forecast modeling system (WRF) and validated against globally gridded observational data of precipitation and 2-m temperature. The study encompasses six different climatic and hydrographic regions: the Amazon basin, the catchments of Lena and Yenisei, central Australia, the Sahara, the Chad depression, and the Niger. Atmospheric-related uncertainty bounds based on the range of the ensemble of estimated terrestrial water storage variations were computed using different configurations of the regional climate model WRF and different global reanalyses. Atmospheric-related uncertainty ranges with those originating from the GRACE products of GeoForschungsZentrum Potsdam, the Center for Space Research, and the Jet Propulsion Laboratory were also compared. It is shown that dynamically downscaled atmospheric fields are able to add value to global reanalyses, depending on the geographical location of the considered catchments. Global and downscaled atmospheric water budgets are in reasonable agreement (r ≈ 0.7 − 0.9) with GRACE-derived terrestrial mass variations. However, atmospheric- and satellite-based approaches show shortcomings for regions with small storage change rates (<20–25 mm month−1).

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Impact of Lateral Boundary Errors on the Simulation of Clouds with a Nonhydrostatic Regional Climate Model

Monthly Weather Review ◽

10.1175/mwr-d-17-0158.1 ◽

2017 ◽

Vol 145 (12) ◽

pp. 5059-5082 ◽

Cited By ~ 6

Author(s):

Junya Uchida ◽

Masato Mori ◽

Masayuki Hara ◽

Masaki Satoh ◽

Daisuke Goto ◽

...

Keyword(s):

Large Scale ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Convective Precipitation ◽

Uniform Grid ◽

Lateral Boundary Condition ◽

Limited Area ◽

Lateral Boundary ◽

Precipitation Distribution

A nonhydrostatic, regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible nonhydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with horizontal grid intervals of 14, 28, and 56 km in the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to the unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extratropical cyclones and orographic precipitation are not severely affected. It was concluded that the errors of the precipitation distribution are not due to the difference of the model configurations but rather to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models.

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Evaluation of the Rossby Centre Regional Climate Model Rainfall Simulations over West Africa Using Large-Scale Spatial and Temporal Statistical Metrics

Atmosphere ◽

10.3390/atmos10120802 ◽

2019 ◽

Vol 10 (12) ◽

pp. 802 ◽

Cited By ~ 3

Author(s):

Gnim Tchalim Gnitou ◽

Tinghuai Ma ◽

Guirong Tan ◽

Brian Ayugi ◽

Isaac Kwesi Nooni ◽

...

Keyword(s):

West Africa ◽

Boundary Conditions ◽

Data Quality ◽

Regional Climate Model ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Global Climate Models ◽

Observational Uncertainty ◽

Ensemble Mean

Climate models are usually evaluated to understand how well the modeled data reproduce specific application-related features. In Africa, where multisource data quality is an issue, there is a need to assess climate data from a general perspective to motivate such specific types of assessment, but mostly to serve as a basis for data quality enhancement activities. In this study, we assessed the Rossby Centre Regional Climate Model (RCA4) over West Africa without targeting any application-specific feature, while jointly evaluating its boundary conditions and accounting for observational uncertainties. Results from this study revealed that the RCA4 signal highly modifies the boundary conditions (global climate models (GCMs) and reanalysis data), resulting in a significant reduction of their biases in the dynamically downscaled outputs. The results, with respect to the observational ensemble members, are in line with the differences between the observation datasets. Among the RCA4 simulations, the ensemble mean outperformed all individual simulations regardless of the statistical metric and the reference data used. This indicates that the RCA4 adds value to GCMs over West Africa, with no influence of observational uncertainty, and its ensemble mean reduces model-related uncertainties.

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A Methodology for the Regional-Scale-Decomposed Atmospheric Water Budget: Application to a Simulation of the Canadian Regional Climate Model Nested by NCEP–NCAR Reanalyses over North America

Monthly Weather Review ◽

10.1175/mwr3098.1 ◽

2006 ◽

Vol 134 (3) ◽

pp. 854-873 ◽

Cited By ~ 6

Author(s):

Soline Bielli ◽

René Laprise

Keyword(s):

Regional Climate Model ◽

Large Scale ◽

Climate Model ◽

Spatial Scales ◽

Regional Climate ◽

Moisture Flux ◽

Added Value ◽

Small Scale ◽

Flux Divergence ◽

Moisture Flux Divergence

Abstract The purpose of this work is to study the added value of a regional climate model with respect to the global analyses used to drive the regional simulation, with a special emphasis on the nonlinear interactions between different spatial scales, focusing on the moisture flux divergence. The atmospheric water budget is used to apply the spatial-scale decomposition approach, as it is a key factor in the energetics of the climate. A Fourier analysis is performed individually for each field on pressure levels. Each field involved in the computation of moisture flux divergence is separated into three components that represent selected scale bands, using the discrete cosine transform. The divergence of the moisture flux is computed from the filtered fields. Instantaneous and monthly mean fields from a simulation performed with the Canadian Regional Climate Model are decomposed and allowed to separate the added value of the model to the total fields. Results show that the added value resides in the nonlinear interactions between large (greater than 1000 km) and small (smaller than 600 km) scales. The main small-scale forcing of the wind is topographic, whereas the humidity tends to show more small scales over the ocean. The time-mean divergence of moisture flux is also decomposed into contributions from stationary eddies and transient eddies. Both stationary and transient eddies are decomposed into different spatial scales and show very different patterns. The time-mean divergence due to transient eddies is dominated by large-scale (synoptic scale) features with little small scales. The divergence due to stationary eddies is a combination of small- and large-scale terms, and the main small-scale contribution occurs over the topography. The same decomposition has been applied to the NCEP–NCAR reanalyses used to drive the regional simulation; the results show that the model best reproduces the time-fluctuation component of the moisture flux divergence, with a correlation between the model simulation and the NCEP–NCAR reanalyses above 0.90.

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Surface Boundary Conditions for Mesoscale Regional Climate Models

Earth Interactions ◽

10.1175/ei151.1 ◽

2005 ◽

Vol 9 (18) ◽

pp. 1-28 ◽

Cited By ~ 38

Author(s):

Xin-Zhong Liang ◽

Hyun I. Choi ◽

Kenneth E. Kunkel ◽

Yongjiu Dai ◽

Everette Joseph ◽

...

Keyword(s):

Boundary Conditions ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Clay Fraction ◽

Value Added ◽

Quality Data ◽

Surface Boundary ◽

Surface Boundary Conditions ◽

Vegetation Characteristic

Abstract This paper utilizes the best available quality data from multiple sources to develop consistent surface boundary conditions (SBCs) for mesoscale regional climate model (RCM) applications. The primary SBCs include 1) fields of soil characteristic (bedrock depth, and sand and clay fraction profiles), which for the first time have been consistently introduced to define 3D soil properties; 2) fields of vegetation characteristic fields (land-cover category, and static fractional vegetation cover and varying leaf-plus-stem-area indices) to represent spatial and temporal variations of vegetation with improved data coherence and physical realism; and 3) daily sea surface temperature variations based on the most appropriate data currently available or other value-added alternatives. For each field, multiple data sources are compared to quantify uncertainties for selecting the best one or merged to create a consistent and complete spatial and temporal coverage. The SBCs so developed can be readily incorporated into any RCM suitable for U.S. climate and hydrology modeling studies, while the data processing and validation procedures can be more generally applied to construct SBCs for any specific domain over the globe.

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Projecting Health Impacts of Future Temperature: A Comparison of Quantile-Mapping Bias-Correction Methods

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18041992 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1992

Author(s):

Weijia Qian ◽

Howard H. Chang

Keyword(s):

Bias Correction ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Warm Season ◽

Climate Science ◽

Regional Climate Models ◽

Health Impact ◽

Quantile Mapping ◽

Ed Visits

Health impact assessments of future environmental exposures are routinely conducted to quantify population burdens associated with the changing climate. It is well-recognized that simulations from climate models need to be bias-corrected against observations to estimate future exposures. Quantile mapping (QM) is a technique that has gained popularity in climate science because of its focus on bias-correcting the entire exposure distribution. Even though improved bias-correction at the extreme tails of exposure may be particularly important for estimating health burdens, the application of QM in health impact projection has been limited. In this paper we describe and apply five QM methods to estimate excess emergency department (ED) visits due to projected changes in warm-season minimum temperature in Atlanta, USA. We utilized temperature projections from an ensemble of regional climate models in the North American-Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). Across QM methods, we estimated consistent increase in ED visits across climate model ensemble under RCP 8.5 during the period 2050 to 2099. We found that QM methods can significantly reduce between-model variation in health impact projections (50–70% decreases in between-model standard deviation). Particularly, the quantile delta mapping approach had the largest reduction and is recommended also because of its ability to preserve model-projected absolute temporal changes in quantiles.

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Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽

10.3390/atmos12020174 ◽

2021 ◽

Vol 12 (2) ◽

pp. 174

Author(s):

Günther Heinemann ◽

Sascha Willmes ◽

Lukas Schefczyk ◽

Alexander Makshtas ◽

Vasilii Kustov ◽

...

Keyword(s):

Sea Ice ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Open Water ◽

The Arctic ◽

Late Winter ◽

Good Representation ◽

Hourly Temperature ◽

Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

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Antarctic ice shelf thickness change from multimission lidar mapping

The Cryosphere ◽

10.5194/tc-13-1801-2019 ◽

2019 ◽

Vol 13 (7) ◽

pp. 1801-1817 ◽

Cited By ~ 2

Author(s):

Tyler C. Sutterley ◽

Thorsten Markus ◽

Thomas A. Neumann ◽

Michiel van den Broeke ◽

J. Melchior van Wessem ◽

...

Keyword(s):

High Resolution ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Surface Velocity ◽

Ice Thickness ◽

Flux Divergence ◽

Ice Shelf ◽

Thickness Change ◽

Ice Shelves

Abstract. We calculate rates of ice thickness change and bottom melt for ice shelves in West Antarctica and the Antarctic Peninsula from a combination of elevation measurements from NASA–CECS Antarctic ice mapping campaigns and NASA Operation IceBridge corrected for oceanic processes from measurements and models, surface velocity measurements from synthetic aperture radar, and high-resolution outputs from regional climate models. The ice thickness change rates are calculated in a Lagrangian reference frame to reduce the effects from advection of sharp vertical features, such as cracks and crevasses, that can saturate Eulerian-derived estimates. We use our method over different ice shelves in Antarctica, which vary in terms of size, repeat coverage from airborne altimetry, and dominant processes governing their recent changes. We find that the Larsen-C Ice Shelf is close to steady state over our observation period with spatial variations in ice thickness largely due to the flux divergence of the shelf. Firn and surface processes are responsible for some short-term variability in ice thickness of the Larsen-C Ice Shelf over the time period. The Wilkins Ice Shelf is sensitive to short-timescale coastal and upper-ocean processes, and basal melt is the dominant contributor to the ice thickness change over the period. At the Pine Island Ice Shelf in the critical region near the grounding zone, we find that ice shelf thickness change rates exceed 40 m yr−1, with the change dominated by strong submarine melting. Regions near the grounding zones of the Dotson and Crosson ice shelves are decreasing in thickness at rates greater than 40 m yr−1, also due to intense basal melt. NASA–CECS Antarctic ice mapping and NASA Operation IceBridge campaigns provide validation datasets for floating ice shelves at moderately high resolution when coregistered using Lagrangian methods.

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Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

Bulletin of the American Meteorological Society ◽

10.1175/bams-88-3-375 ◽

2007 ◽

Vol 88 (3) ◽

pp. 375-384 ◽

Cited By ~ 39

Author(s):

E. S. Takle ◽

J. Roads ◽

B. Rockel ◽

W. J. Gutowski ◽

R. W. Arritt ◽

...

Keyword(s):

Energy Budget ◽

Climate Models ◽

Climate Model ◽

Water Cycle ◽

Regional Climate ◽

Climate Conditions ◽

Continental Scale ◽

Global Water Cycle ◽

Wide Range ◽

Global Water

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

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