Introduction to CAUSES: Description of Weather and Climate Models and Their Near‐Surface Temperature Errors in 5 day Hindcasts Near the Southern Great Plains

AbstractNewly installed stereo cameras ringing the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site in Oklahoma are providing a 4D gridded view of shallow clouds. Six digital cameras have been installed in pairs at a distance of 6 km from the site and with a spacing of 500 m between cameras in a pair. These pairs of cameras provide stereoscopic views of shallow clouds from all sides; when these data are combined, they allow for a complete stereo reconstruction. The result—the Clouds Optically Gridded by Stereo (COGS) product—is a 4D grid of cloudiness covering a 6 km × 6 km × 6 km cube at a spatial resolution of 50 m and a temporal resolution of 20 s. This provides a unique set of data on the sizes, lifetimes, and life cycles of shallow clouds. This type of information is critical for developing cloud macrophysical schemes for the next generation of weather and climate models.

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A Mechanistically Credible, Poleward Shift in Warm-Season Precipitation Projected for the U.S. Southern Great Plains?

Journal of Climate ◽

10.1175/jcli-d-16-0316.1 ◽

2017 ◽

Vol 30 (20) ◽

pp. 8275-8298 ◽

Cited By ~ 13

Author(s):

Melissa S. Bukovsky ◽

Rachel R. McCrary ◽

Anji Seth ◽

Linda O. Mearns

Keyword(s):

Great Plains ◽

Climate Models ◽

Climate Model ◽

Global Climate Model ◽

Regional Climate ◽

Warm Season ◽

Dry Season ◽

Wet Season ◽

Southern Great Plains ◽

Poleward Shift

Abstract Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.

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Land–Atmosphere Interactions: The LoCo Perspective

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-17-0001.1 ◽

2018 ◽

Vol 99 (6) ◽

pp. 1253-1272 ◽

Cited By ~ 89

Author(s):

Joseph A. Santanello ◽

Paul A. Dirmeyer ◽

Craig R. Ferguson ◽

Kirsten L. Findell ◽

Ahmed B. Tawfik ◽

...

Keyword(s):

Land Surface ◽

Climate Models ◽

Climate Modeling ◽

Global Climate ◽

Surface States ◽

Energy Budgets ◽

Near Surface ◽

Traditional Research ◽

Weather And Climate ◽

Main Driver

AbstractLand–atmosphere (L-A) interactions are a main driver of Earth’s surface water and energy budgets; as such, they modulate near-surface climate, including clouds and precipitation, and can influence the persistence of extremes such as drought. Despite their importance, the representation of L-A interactions in weather and climate models remains poorly constrained, as they involve a complex set of processes that are difficult to observe in nature. In addition, a complete understanding of L-A processes requires interdisciplinary expertise and approaches that transcend traditional research paradigms and communities. To address these issues, the international Global Energy and Water Exchanges project (GEWEX) Global Land–Atmosphere System Study (GLASS) panel has supported “L-A coupling” as one of its core themes for well over a decade. Under this initiative, several successful land surface and global climate modeling projects have identified hot spots of L-A coupling and helped quantify the role of land surface states in weather and climate predictability. GLASS formed the Local Land–Atmosphere Coupling (LoCo) project and working group to examine L-A interactions at the process level, focusing on understanding and quantifying these processes in nature and evaluating them in models. LoCo has produced an array of L-A coupling metrics for different applications and scales and has motivated a growing number of young scientists from around the world. This article provides an overview of the LoCo effort, including metric and model applications, along with scientific and programmatic developments and challenges.

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Long-Term Trends in Downwelling Spectral Infrared Radiance over the U.S. Southern Great Plains

Journal of Climate ◽

10.1175/2011jcli4210.1 ◽

2011 ◽

Vol 24 (18) ◽

pp. 4831-4843 ◽

Cited By ~ 12

Author(s):

P. Jonathan Gero ◽

David D. Turner

Keyword(s):

Great Plains ◽

Climate Models ◽

Southern Great Plains ◽

Infrared Radiance ◽

Term Change ◽

Atmospheric Radiation Measurement ◽

Long Term Trends ◽

Thin Cloud ◽

The U.S

Abstract A trend analysis was applied to a 14-yr time series of downwelling spectral infrared radiance observations from the Atmospheric Emitted Radiance Interferometer (AERI) located at the Atmospheric Radiation Measurement Program (ARM) site in the U.S. Southern Great Plains. The highly accurate calibration of the AERI instrument, performed every 10 min, ensures that any statistically significant trend in the observed data over this time can be attributed to changes in the atmospheric properties and composition, and not to changes in the sensitivity or responsivity of the instrument. The measured infrared spectra, numbering more than 800 000, were classified as clear-sky, thin cloud, and thick cloud scenes using a neural network method. The AERI data record demonstrates that the downwelling infrared radiance is decreasing over this 14-yr period in the winter, summer, and autumn seasons but it is increasing in the spring; these trends are statistically significant and are primarily due to long-term change in the cloudiness above the site. The AERI data also show many statistically significant trends on annual, seasonal, and diurnal time scales, with different trend signatures identified in the separate scene classifications. Given the decadal time span of the dataset, effects from natural variability should be considered in drawing broader conclusions. Nevertheless, this dataset has high value owing to the ability to infer possible mechanisms for any trends from the observations themselves and to test the performance of climate models.

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Improving WRF-Chem meteorological analyses and forecasts over aerosol polluted regions by incorporating NAAPS aerosol analyses

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-20-0174.1 ◽

2021 ◽

Author(s):

Brittany N. Carson-Marquis ◽

Jianglong Zhang ◽

Peng Xian ◽

Jeffrey S. Reid ◽

Jared Marquis

Keyword(s):

Boundary Conditions ◽

Surface Temperature ◽

Great Plains ◽

Transport Model ◽

Weather Prediction ◽

The United States ◽

Northern Great Plains ◽

Chemical Transport Model ◽

Near Surface ◽

Initial And Boundary Conditions

AbstractWhen unaccounted for in numerical weather prediction (NWP) models, heavy aerosol events can cause significant unrealized biases in forecasted meteorological parameters such as surface temperature. To improve near-surface forecasting accuracies during heavy aerosol loadings, we demonstrate the feasibility of incorporating aerosol fields from a global chemical transport model as initial and boundary conditions into a higher resolution NWP model with aerosol-meteorological coupling. This concept is tested for a major biomass burning smoke event over the Northern Great Plains region of the United States that occurred during summer of 2015. Aerosol analyses from the global Navy Aerosol Analysis and Prediction System (NAAPS) are used as initial and boundary conditions for Weather Research and Forecasting with Chemistry (WRF-Chem) simulations. Through incorporating more realistic aerosol direct effects into the WRF-Chem simulations, errors in WRF-Chem simulated surface downward shortwave radiative fluxes and near-surface temperature are reduced compared with surface-based observations. This study confirms the ability to decrease biases induced by the aerosol direct effect for regional NWP forecasts during high-impact aerosol episodes through the incorporation of analyses and forecasts from a global aerosol transport model.

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Low-Level Cloud Variability over the Equatorial Cold Tongue in Observations and Models

Journal of Climate ◽

10.1175/jcli4073.1 ◽

2007 ◽

Vol 20 (8) ◽

pp. 1555-1570 ◽

Cited By ~ 20

Author(s):

David K. Mansbach ◽

Joel R. Norris

Keyword(s):

Boundary Layer ◽

Surface Temperature ◽

Climate Models ◽

Cloud Amount ◽

Global Climate Models ◽

Geophysical Fluid Dynamics Laboratory ◽

Cold Tongue ◽

Multilinear Regression ◽

Near Surface ◽

Low Level

Abstract Examination of cloud and meteorological observations from satellite, surface, and reanalysis datasets indicates that monthly anomalies in low-level cloud amount and near-surface temperature advection are strongly negatively correlated on the southern side of the equatorial Pacific cold tongue. This inverse correlation occurs independently of relationships between cloud amount and sea surface temperature (SST) or lower tropospheric static stability (LTS), and the combination of advection plus SST or LTS explains significantly more interannual cloud variability in a multilinear regression than does SST or LTS alone. Warm anomalous advection occurs when the equatorial cold tongue is well defined and the southeastern Pacific trade winds bring relatively warm air over colder water. Ship meteorological reports and soundings show that the atmospheric surface layer becomes stratified under these conditions, thus inhibiting the upward mixing of moisture needed to sustain cloudiness against subsidence and entrainment drying. Cold anomalous advection primarily occurs when the equatorial cold tongue is weak or absent and the air–sea temperature difference is substantially negative. These conditions favor a more convective atmospheric boundary layer, greater cloud amount, and less frequent occurrence of clear sky. Examination of output from global climate models developed by the Geophysical Fluid Dynamics Laboratory (GFDL) and the National Center for Atmospheric Research (NCAR) indicates that both models generally fail to simulate the cloud–advection relationships observed on the northern and southern sides of the equatorial cold tongue. Although the GFDL atmosphere model does reproduce the expected signs of cloud-advection correlations when forced with prescribed historical SST variations, it does not consistently do so when coupled to an ocean model. The NCAR model has difficulty reproducing the observed correlations in both atmosphere-only and coupled versions. This suggests that boundary layer cloud parameterizations could be improved through better representation of the effects of advection over varying SST.

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