Model Improvement via Systematic Investigation of Physics Tendencies

2020 ◽  
Vol 148 (2) ◽  
pp. 671-688 ◽  
Author(s):  
May Wong ◽  
Glen Romine ◽  
Chris Snyder
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Land Surface Model ◽  
Warm Season ◽  
The United States ◽  
Systematic Investigation ◽  
Surface Model ◽  
Cumulus Scheme ◽  
Model Improvement ◽  
Precipitation Cycle

Abstract Deficiencies in forecast models commonly stem from inadequate representation of physical processes; yet, improvement to any single physics component within a model may lead to degradations in other physics components or the model as a whole. In this study, a systematic investigation of physics tendencies is demonstrated to help identify and correct compensating sources of model biases. The model improvement process is illustrated by addressing a commonly known issue in warm-season rainfall forecasts from parameterized convection models: the misrepresentation of the diurnal precipitation cycle over land, especially in its timing. Recent advances in closure assumptions in mass-flux cumulus schemes have made remarkable improvements in this respect. Here, we investigate these improvements in the representation of the diurnal precipitation cycle for a spring period over the United States, and how changes to the cumulus scheme impact the model climate and the behavior of other physics schemes. The modified cumulus scheme improves both the timing of the diurnal precipitation cycle and reduces midtropospheric temperature and moisture biases. However, larger temperature and moisture biases are found in the boundary layer as compared to a predecessor scheme, along with an overamplification of the diurnal precipitation cycle, relative to observations. Guided by a tendency analysis, we find that biases in the diurnal amplitude of the precipitation cycle in our simulations, along with temperature and moisture biases in the boundary layer, originate from the land surface model.

Improvement of the Noah land surface model for warm season processes: evaluation of water and energy flux simulation

2012 ◽  
Vol 27 (2) ◽  
pp. 297-303 ◽  
Author(s):  
Helin Wei ◽  
Youlong Xia ◽  
Kenneth E. Mitchell ◽  
Michael B. Ek
Keyword(s):  
Energy Flux ◽  
Land Surface ◽  
Land Surface Model ◽  
Warm Season ◽  
Surface Model ◽  
Noah Land Surface Model

scholarly journals Diagnosing Moisture Sources for Flash Floods in the United States. Part II: Terrestrial and Oceanic Sources of Moisture

2019 ◽  
Vol 20 (8) ◽  
pp. 1511-1531 ◽  
Author(s):  
Jessica M. Erlingis ◽  
Jonathan J. Gourley ◽  
Jeffrey B. Basara
Keyword(s):  
United States ◽  
Boundary Layer ◽  
Land Surface ◽  
Flash Flood ◽  
The United States ◽  
Flash Floods ◽  
Heat Fluxes ◽  
Surface Model ◽  
Positive Anomaly ◽  
The Impact

Abstract Backward trajectories were derived from North American Regional Reanalysis data for 19 253 flash flood reports published by the National Weather Service to determine the along-path contribution of the land surface to the moisture budget for flash flood events in the conterminous United States. The impact of land surface interactions was evaluated seasonally and for six regions: the West Coast, Arizona, the Front Range, Flash Flood Alley, the Missouri Valley, and the Appalachians. Parcels were released from locations that were impacted by flash floods and traced backward in time for 120 h. The boundary layer height was used to determine whether moisture increases occurred within the boundary layer or above it. Moisture increases occurring within the boundary layer were attributed to evapotranspiration from the land surface, and surface properties were recorded from an offline run of the Noah land surface model. In general, moisture increases attributed to the land surface were associated with anomalously high surface latent heat fluxes and anomalously low sensible heat fluxes (resulting in a positive anomaly of evaporative fraction) as well as positive anomalies in top-layer soil moisture. Over the ocean, uptakes were associated with positive anomalies in sea surface temperatures, the magnitude of which varies both regionally and seasonally. Major oceanic surface-based source regions of moisture for flash floods in the United States include the Gulf of Mexico and the Gulf of California, while boundary layer moisture increases in the southern plains are attributable in part to interactions between the land surface and the atmosphere.

An investigation into the influence of high-resolution land-surface heterogeneity on atmospheric dynamics

2020 ◽  
Author(s):  
Jason Simon ◽  
Khaled Ghannam ◽  
Gabriel Katul ◽  
Paul Dirmeyer ◽  
Kirsten Findell ◽  
...  
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Planetary Boundary Layer ◽  
Land Surface ◽  
Climate Modeling ◽  
Land Surface Model ◽  
Surface Heterogeneity ◽  
Atmospheric Dynamics ◽  
Surface Model ◽  
Land Surface Heterogeneity

<p>Land-surface heterogeneity is known to play an important role in land surface hydrology and thus the boundary conditions for numerical weather prediction (NWP) and climate modeling. For this reason, there have been considerable efforts over the past two decades to improve its representation in large scale models. However, to date, the inclusion of sub-grid heterogeneity in modeling land-atmosphere interactions in regional and global models has been limited to sub-grid spatial means and thus have almost entirely disregarded its multi-scale impact on the simulated atmospheric dynamics. To begin to address this challenge, here we use large-eddy simulations (LES) coupled to a land-surface model to gain a more complete understanding of its role in the coupled land-atmosphere system. In this work, we illustrate its impact over the Southern Great Plains (SGP) site in the United States and present a path forward for using these modeling experiments to guide the development of a complementary coupling parameterization within climate models.</p><p>More specifically, over the SGP site, we use high-resolution LES to investigate the impact of SGS land heterogeneity under different atmospheric and surface conditions to inform the development of land-surface and planetary boundary layer (PBL) parameterizations for coarser, operational-scale weather and climate modeling efforts. The experiment methodology uses a high-resolution land-surface model (WRF-Hydro), spun-up over multiple years using reanalysis data, which is then coupled to the Weather Research and Forecasting (WRF) model for high-resolution LES. Cases are considered using both the fully heterogeneous land model as well as using a homogeneous surface with domain-averaged flux values at all grid points, allowing the dynamical effects of land-surface heterogeneity on the atmosphere to be isolated, and the land/atmospheric conditions under which land-surface heterogeneity plays a role to be studied. Results are evaluated primarily by the differences in the development of the planetary boundary layer and the extent, duration and intensity of developing rainfall events.</p>

scholarly journals A SMAP-Based Drought Monitoring Index for the United States

2018 ◽  
Author(s):  
Sara Sadri ◽  
Eric F. Wood ◽  
Ming Pan
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Land Surface ◽  
Surface Soil ◽  
Root Zone ◽  
Warm Season ◽  
The United States ◽  
Surface Model ◽  
Surface Soil Moisture ◽  
Near Surface

Abstract. Since April 2015, NASA's Soil Moisture Active Passive (SMAP) mission has monitored near-surface soil moisture, mapping the globe between the latitude bands of 85.044° N/S in 2–3 days depending on location. SMAP Level 3 passive radiometer product (SPL3SMP) measures the amount of water in the top 5 cm of soil except for regions of heavy vegetation (vegetation water content >4.5 kg/m2) and frozen or snow covered locations. SPL3SMP retrievals are spatially and temporally discontinuous, so the 33 months offers a short SMAP record length and poses a statistical challenge for meaningful assessment of its indices. The SMAP SPL4SMAU data product provides global surface and root zone soil moisture at 9-km resolution based on assimilating the SPL3SMP product into the NASA Catchment land surface model. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP near-surface soil moisture in terms of probability percentiles for dry and wet conditions. We describe here SMAP-based indices over the continental United States (CONUS) based on both near-surface and root zone soil moisture percentiles. The percentiles are based on fitting a Beta distribution to the retrieved moisture values. To assess the data adequacy, a statistical comparison is made between fitting the distribution to VIC soil moisture values for the days when SPL3SMP are available, versus fitting to a 1979–2017 VIC data record. For the cold season (November–April), 57 % of grids were deemed to be consistent between the periods, and 68 % in the warm season (May–October), based on a Kolmogorov–Smirnov statistical test. It is assumed that if grids passed the consistency test using VIC data, then the grid had sufficient SMAP data. Our near-surface and root zone drought index on maps are shown to be similar to those produced by the U.S. Drought Monitor (from D0-D4) and GRACE. In a similar manner, we extend the index to include pluvial conditions using indices W0-W4. This study is a step forward towards building a national and international soil moisture monitoring system, without which, quantitative measures of drought and pluvial conditions will remain difficult to judge.

scholarly journals Modeling of land-surface interactions in the PALM model system 6.0: Land surface model description, first evaluation, and sensitivity to model parameters

2020 ◽  
Author(s):  
Katrin Frieda Gehrke ◽  
Matthias Sühring ◽  
Björn Maronga
Keyword(s):  
Boundary Layer ◽  
Energy Balance ◽  
Surface Potential ◽  
Land Surface ◽  
Potential Temperature ◽  
Land Surface Model ◽  
Model System ◽  
Horizontal Wind ◽  
Surface Model ◽  
Near Surface

Abstract. In this paper the land-surface model embedded in the PALM model system is described and evaluated against in-situ measurement data in Cabauw. For this, two consecutive clear-sky days are simulated and the components of surface energy balance, as well as near-surface potential temperature, humidity and horizontal wind speed are compared against observation data. For the simulated period, components of the energy balance agree well during day- and nighttime, and also the daytime Bowen ratio agrees fairly well compared to the observations. Although the model simulates a significantly more stably-stratified nocturnal boundary layer compared to the observation, near-surface potential temperature and humidity agree fairly well during day. Moreover, we performed a sensitivity study in order to investigate how much the model results depend on land-surface and soil specifications, as well as atmospheric initial conditions. By this, we find that a false estimation of the leaf area index, the albedo, or the initial humidity causes a serious misrepresentation of the daytime turbulent sensible and latent heat fluxes. During night, the boundary-layer characteristics are mostly affected by grid size, surface roughness, and the applied radiation schemes.

Simulating the Effects of Irrigation over the United States in a Land Surface Model Based on Satellite-Derived Agricultural Data

2010 ◽  
Vol 11 (1) ◽  
pp. 171-184 ◽  
Author(s):  
Mutlu Ozdogan ◽  
Matthew Rodell ◽  
Hiroko Kato Beaudoing ◽  
David L. Toll
Keyword(s):  
United States ◽  
Heat Flux ◽  
Land Surface ◽  
Agricultural Land ◽  
Weather Prediction ◽  
Land Surface Model ◽  
The United States ◽  
Surface Model ◽  
Irrigation Scheme ◽  
Ground Heat Flux

Abstract A novel method is introduced for integrating satellite-derived irrigation data and high-resolution crop-type information into a land surface model (LSM). The objective is to improve the simulation of land surface states and fluxes through better representation of agricultural land use. Ultimately, this scheme could enable numerical weather prediction (NWP) models to capture land–atmosphere feedbacks in managed lands more accurately and thus improve forecast skill. Here, it is shown that the application of the new irrigation scheme over the continental United States significantly influences the surface water and energy balances by modulating the partitioning of water between the surface and the atmosphere. In this experiment, irrigation caused a 12% increase in evapotranspiration (QLE) and an equivalent reduction in the sensible heat flux (QH) averaged over all irrigated areas in the continental United States during the 2003 growing season. Local effects were more extreme: irrigation shifted more than 100 W m−2 from QH to QLE in many locations in California, eastern Idaho, southern Washington, and southern Colorado during peak crop growth. In these cases, the changes in ground heat flux (QG), net radiation (RNET), evapotranspiration (ET), runoff (R), and soil moisture (SM) were more than 3 W m−2, 20 W m−2, 5 mm day−1, 0.3 mm day−1, and 100 mm, respectively. These results are highly relevant to continental-to-global-scale water and energy cycle studies that, to date, have struggled to quantify the effects of agricultural management practices such as irrigation. On the basis of the results presented here, it is expected that better representation of managed lands will lead to improved weather and climate forecasting skill when the new irrigation scheme is incorporated into NWP models such as NOAA’s Global Forecast System (GFS).

scholarly journals A Spatial Pattern Analysis of Land Surface Roughness Heterogeneity and its Relationship to the Initiation of Weak Tornadoes

2019 ◽  
Vol 23 (5) ◽  
pp. 1-28 ◽  
Author(s):  
Amanda Markert ◽  
Robert Griffin ◽  
Kevin Knupp ◽  
Andrew Molthan ◽  
Tim Coleman
Keyword(s):  
Surface Roughness ◽  
Great Plains ◽  
Land Surface ◽  
Spatial Scales ◽  
Land Surface Model ◽  
The United States ◽  
Surface Model ◽  
Spatial Pattern Analysis ◽  
Horizontal Gradients ◽  
Vorticity Vector

Abstract North Alabama is among the most tornado-prone regions in the United States and is composed of more spatially variable terrain and land cover than the frequently studied North American Great Plains region. Because of the high tornado frequency observed across north Alabama, there is a need to understand how land surface roughness heterogeneity influences tornadogenesis, particularly for weak-intensity tornadoes. This study investigates whether horizontal gradients in land surface roughness exist surrounding locations of tornadogenesis for weak (EF0–EF1) tornadoes. The existence of the horizontal gradients could lead to the generation of positive values of the vertical components of the 3D vorticity vector near the surface that may aid in the tornadogenesis process. In this study, surface roughness was estimated using parameterizations from the Noah land surface model with inputs from MODIS 500-m and Landsat 30-m data. Spatial variations in the parameterized roughness lengths were assessed using GIS-based grid and quadrant pattern analyses to quantify observed variation of land surface features surrounding tornadogenesis locations across spatial scales. This analysis determined that statistically significant horizontal gradients in surface roughness exist surrounding tornadogenesis locations.

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