A Stochastic Parameter Perturbation Method to Represent Uncertainty in a Microphysics Scheme

2021 ◽  
Author(s):  
Gregory Thompson ◽  
Judith Berner ◽  
Maria Frediani ◽  
Jason A. Otkin ◽  
Sarah M. Griffin
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Random Perturbation ◽  
Longwave Radiation ◽  
Parameter Uncertainties ◽  
Microphysics Scheme ◽  
Convective Systems ◽  
Temporal Correlations ◽  
Precipitation Characteristics ◽  
The Impact

AbstractCurrent state-of-the art regional numerical weather forecasts are run at horizontal grid spacings of a few kilometers, which permits medium to large-scale convective systems to be represented explicitly in the model. With the convection parameterization no longer active, much uncertainty in the formulation of subgrid-scale processes moves to other areas such as the cloud microphysical, turbulence, and land-surface parameterizations. The goal of this study is to investigate experiments with stochastically-perturbed parameters (SPP) within a microphysics parameterization and the model’s horizontal diffusion coefficients. To estimate the “true” uncertainty due to parameter uncertainty, the magnitudes of the perturbations are chosen as realistic as possible and not with purposeful intent of maximal forecast impact as some prior work has done. Spatial inhomogeneities and temporal persistence are represented using a random perturbation pattern with spatial and temporal correlations. The impact on the distributions of various hydrometeors, precipitation characteristics, and solar/longwave radiation are quantified for a winter and summer case. In terms of upscale error growth, the impact is relatively small and consists primarily of triggering atmospheric instabilities in convectively unstable regions. In addition, small in situ changes with potentially large socio-economic impacts are observed in the precipitation characteristics such as maximum hail size. Albeit the impact of introducing physically-based parameter uncertainties within the bounds of aerosol uncertainties is small, their influence on the solar and longwave radiation balances may still have important implications for global model simulations of future climate scenarios.

scholarly journals The impact of MM5 and WRF meteorology over complex terrain on CHIMERE model calculations

2009 ◽  
Vol 9 (17) ◽  
pp. 6611-6632 ◽  
Author(s):  
A. de Meij ◽  
A. Gzella ◽  
C. Cuvelier ◽  
P. Thunis ◽  
B. Bessagnet ◽  
...  
Keyword(s):  
Land Surface ◽  
Transport Model ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Microphysics Scheme ◽  
Model Calculations ◽  
Temporal Correlations ◽  
The Difference ◽  
The Impact

Abstract. The objective of this study is to evaluate the impact of meteorological input data on calculated gas and aerosol concentrations. We use two different meteorological models (MM5 and WRF) together with the chemistry transport model CHIMERE. We focus on the Po valley area (Italy) for January and June 2005. Firstly we evaluate the meteorological parameters with observations. The analysis shows that the performance of both models in calculating surface parameters is similar, however differences are still observed. Secondly, we analyze the impact of using MM5 and WRF on calculated PM10 and O3 concentrations. In general CHIMERE/MM5 and CHIMERE/WRF underestimate the PMv concentrations for January. The difference in PM10 concentrations for January between CHIMERE/MM5 and CHIMERE/WRF is around a factor 1.6 (PM10 higher for CHIMERE/MM5). This difference and the larger underestimation in PM10 concentrations by CHIMERE/WRF are related to the differences in heat fluxes and the resulting PBL heights calculated by WRF. In general the PBL height by WRF meteorology is a factor 2.8 higher at noon in January than calculated by MM5. This study showed that the difference in microphysics scheme has an impact on the profile of cloud liquid water (CLW) calculated by the meteorological driver and therefore on the production of SO4 aerosol. A sensitivity analysis shows that changing the Noah Land Surface Model (LSM) in our WRF pre-processing for the 5-layer soil temperature model, calculated monthly mean PMv concentrations increase by 30%, due to the change in the heat fluxes and the resulting PBL heights. For June, PM10 calculated concentrations by CHIMERE/MM5 and CHIMERE/WRF are similar and agree with the observations. Calculated O3 values for June are in general overestimated by a factor 1.3 by CHIMERE/MM5 and CHIMERE/WRF. High temporal correlations are found between modeled and observed O3 concentrations.

scholarly journals Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

2021 ◽  
Vol 13 (5) ◽  
pp. 874
Author(s):  
Yu Chen ◽  
Mohamed Ahmed ◽  
Natthachet Tangdamrongsub ◽  
Dorina Murgulet
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Surface Deformation ◽  
Vertical Displacement ◽  
Nile River ◽  
Reservoir Volume ◽  
Novel Approach ◽  
Land Deformation ◽  
Large Scale Land ◽  
The Impact

The Nile River stretches from south to north throughout the Nile River Basin (NRB) in Northeast Africa. Ethiopia, where the Blue Nile originates, has begun the construction of the Grand Ethiopian Renaissance Dam (GERD), which will be used to generate electricity. However, the impact of the GERD on land deformation caused by significant water relocation has not been rigorously considered in the scientific research. In this study, we develop a novel approach for predicting large-scale land deformation induced by the construction of the GERD reservoir. We also investigate the limitations of using the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) mission to detect GERD-induced land deformation. We simulated three land deformation scenarios related to filling the expected reservoir volume, 70 km3, using 5-, 10-, and 15-year filling scenarios. The results indicated: (i) trends in downward vertical displacement estimated at −17.79 ± 0.02, −8.90 ± 0.09, and −5.94 ± 0.05 mm/year, for the 5-, 10-, and 15-year filling scenarios, respectively; (ii) the western (eastern) parts of the GERD reservoir are estimated to move toward the reservoir’s center by +0.98 ± 0.01 (−0.98 ± 0.01), +0.48 ± 0.00 (−0.48 ± 0.00), and +0.33 ± 0.00 (−0.33 ± 0.00) mm/year, under the 5-, 10- and 15-year filling strategies, respectively; (iii) the northern part of the GERD reservoir is moving southward by +1.28 ± 0.02, +0.64 ± 0.01, and +0.43 ± 0.00 mm/year, while the southern part is moving northward by −3.75 ± 0.04, −1.87 ± 0.02, and −1.25 ± 0.01 mm/year, during the three examined scenarios, respectively; and (iv) the GRACE-FO mission can only detect 15% of the large-scale land deformation produced by the GERD reservoir. Methods and results demonstrated in this study provide insights into possible impacts of reservoir impoundment on land surface deformation, which can be adopted into the GERD project or similar future dam construction plans.

scholarly journals The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis

2015 ◽  
Vol 8 (1) ◽  
pp. 421-434 ◽  
Author(s):  
M. P. Jensen ◽  
T. Toto ◽  
D. Troyan ◽  
P. E. Ciesielski ◽  
D. Holdridge ◽  
...  
Keyword(s):  
Large Scale ◽  
Scale Model ◽  
Data Sets ◽  
Central Plains ◽  
Data Set ◽  
Convective Systems ◽  
Convective Clouds ◽  
Quality Checks ◽  
Network Operations ◽  
The Impact

Abstract. The Midlatitude Continental Convective Clouds Experiment (MC3E) took place during the spring of 2011 centered in north-central Oklahoma, USA. The main goal of this field campaign was to capture the dynamical and microphysical characteristics of precipitating convective systems in the US Central Plains. A major component of the campaign was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state with the intent of deriving model forcing data sets. Over the course of the 46-day MC3E campaign, a total of 1362 radiosondes were launched from the enhanced sonde network. This manuscript provides details on the instrumentation used as part of the sounding array, the data processing activities including quality checks and humidity bias corrections and an analysis of the impacts of bias correction and algorithm assumptions on the determination of convective levels and indices. It is found that corrections for known radiosonde humidity biases and assumptions regarding the characteristics of the surface convective parcel result in significant differences in the derived values of convective levels and indices in many soundings. In addition, the impact of including the humidity corrections and quality controls on the thermodynamic profiles that are used in the derivation of a large-scale model forcing data set are investigated. The results show a significant impact on the derived large-scale vertical velocity field illustrating the importance of addressing these humidity biases.

scholarly journals Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

2017 ◽  
Vol 10 (5) ◽  
pp. 2031-2055 ◽  
Author(s):  
Thomas Schwitalla ◽  
Hans-Stefan Bauer ◽  
Volker Wulfmeyer ◽  
Kirsten Warrach-Sagi
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Temperature Fields ◽  
Surface Model ◽  
Limited Area ◽  
Data Set ◽  
Latitude Belt ◽  
Simulated Precipitation ◽  
The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

Warm Cloud Evolution, Precipitation, and Their Weak Linkage in HadGEM3: New Process-Level Diagnostics using A-Train Observations

2021 ◽  
Author(s):  
Hanii Takahashi ◽  
Alejandro Bodas-Salcedo ◽  
Graeme Stephens
Keyword(s):  
Large Scale ◽  
Cloud Droplet ◽  
Formation Processes ◽  
Evaluation Tool ◽  
Liquid Water Path ◽  
Microphysics Scheme ◽  
Warm Rain ◽  
Weak Linkage ◽  
The Impact ◽  
Rain Formation

AbstractThe latest configuration of the Hadley Centre Global Environmental Model version 3 (HadGEM3) contains significant changes in the formulation of warm rain processes and aerosols. We evaluate the impacts of these changes in the simulation of warm rain formation processes using A-Train observations. We introduce a new model evaluation tool, quartile-based Contoured Frequency by Optical Depth Diagrams (CFODDs), in order to fill in some blind spots that conventional CFODDs have. Results indicate that HadGEM3 has weak linkage between the size of particle radius and warm rain formation processes, and switching to the new warm rain microphysics scheme causes more difference in warm rain formation processes than switching to the new aerosol scheme through reducing overly produced drizzle mode in HadGEM3. Finally, we run an experiment in which we perturb the second aerosol indirect effect (AIE) to study the rainfall-aerosol interaction in HadGEM3. Since the large changes in the cloud droplet number concentration (CDNC) appear in the AIE experiment, a large impact in warm rain diagnostics is expected. However, regions with large fractional changes in CDNC show a muted change in precipitation, arguably because large-scale constraints act to reduce the impact of such a big change in CDNC. The adjustment in cloud liquid water path to the AIE perturbation produces a large negative shortwave forcing in the midlatitudes.

scholarly journals Object Detection and Image Segmentation with Deep Learning on Earth Observation Data: A Review—Part II: Applications

2020 ◽  
Vol 12 (18) ◽  
pp. 3053 ◽  
Author(s):  
Thorsten Hoeser ◽  
Felix Bachofer ◽  
Claudia Kuenzer
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Object Detection ◽  
Land Surface ◽  
Large Scale ◽  
Earth Observation ◽  
Observation Data ◽  
Fine Grained ◽  
The Impact ◽  
Object Dynamics

In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by investigating aggregated classes. The increase in data with a very high spatial resolution enables investigations on a fine-grained feature level which can help us to better understand the dynamics of land surfaces by taking object dynamics into account. To extract fine-grained features and objects, the most popular deep-learning model for image analysis is commonly used: the convolutional neural network (CNN). In this review, we provide a comprehensive overview of the impact of deep learning on EO applications by reviewing 429 studies on image segmentation and object detection with CNNs. We extensively examine the spatial distribution of study sites, employed sensors, used datasets and CNN architectures, and give a thorough overview of applications in EO which used CNNs. Our main finding is that CNNs are in an advanced transition phase from computer vision to EO. Upon this, we argue that in the near future, investigations which analyze object dynamics with CNNs will have a significant impact on EO research. With a focus on EO applications in this Part II, we complete the methodological review provided in Part I.

Impact of an Exponential Profile of Saturated Hydraulic Conductivity within the ISBA LSM: Simulations over the Rhône Basin

2006 ◽  
Vol 7 (1) ◽  
pp. 61-80 ◽  
Author(s):  
B. Decharme ◽  
H. Douville ◽  
A. Boone ◽  
F. Habets ◽  
J. Noilhan
Keyword(s):  
High Resolution ◽  
Hydraulic Conductivity ◽  
Land Surface ◽  
Large Scale ◽  
Saturated Hydraulic Conductivity ◽  
Rooting Depth ◽  
Surface Model ◽  
Low Resolution ◽  
The Impact ◽  
Hydrological Applications

Abstract This study focuses on the influence of an exponential profile of saturated hydraulic conductivity, ksat, with soil depth on the water budget simulated by the Interaction Soil Biosphere Atmosphere (ISBA) land surface model over the French Rhône River basin. With this exponential profile, the saturated hydraulic conductivity at the surface increases by approximately a factor of 10, and its mean value increases in the root zone and decreases in the deeper region of the soil in comparison with the values given by Clapp and Hornberger. This new version of ISBA is compared to the original version in offline simulations using the Rhône-Aggregation high-resolution database. Low-resolution simulations, where all atmospheric data and surface parameters have been aggregated, are also performed to test the impact of the modified ksat profile at the typical scale of a climate model. The simulated discharges are compared to observations from a dense network consisting of 88 gauging stations. Results of the high-resolution experiments show that the exponential profile of ksat globally improves the simulated discharges and that the assumption of an increase in saturated hydraulic conductivity from the soil surface to a depth close to the rooting depth in comparison with values given by Clapp and Hornberger is reasonable. Results of the scaling experiments indicate that this parameterization is also suitable for large-scale hydrological applications. Nevertheless, low-resolution simulations with both model versions overestimate evapotranspiration (especially from the plant transpiration and the wet fraction of the canopy) to the detriment of total runoff, which emphasizes the need for implementing subgrid distribution of precipitation and land surface properties in large-scale hydrological applications.

Land–Atmosphere Interaction in Tropical Africa

2020 ◽  
Author(s):  
Cathy Hohenegger
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Surface State ◽  
Land Surface ◽  
Large Scale ◽  
Moisture Distribution ◽  
Sahel Region ◽  
The Impact

Even though many features of the vegetation and of the soil moisture distribution over Africa reflect its climatic zones, the land surface has the potential to feed back on the atmosphere and on the climate of Africa. The land surface and the atmosphere communicate via the surface energy budget. A particularly important control of the land surface, besides its control on albedo, is on the partitioning between sensible and latent heat flux. In a soil moisture-limited regime, for instance, an increase in soil moisture leads to an increase in latent heat flux at the expanse of the sensible heat flux. The result is a cooling and a moistening of the planetary boundary layer. On the one hand, this thermodynamically affects the atmosphere by altering the stability and the moisture content of the vertical column. Depending on the initial atmospheric profile, convection may be enhanced or suppressed. On the other hand, a confined perturbation of the surface state also has a dynamical imprint on the atmospheric flow by generating horizontal gradients in temperature and pressure. Such gradients spin up shallow circulations that affect the development of convection. Whereas the importance of such circulations for the triggering of convection over the Sahel region is well accepted and well understood, the effect of such circulations on precipitation amounts as well as on mature convective systems remains unclear. Likewise, the magnitude of the impact of large-scale perturbations of the land surface state on the large-scale circulation of the atmosphere, such as the West African monsoon, has long been debated. One key issue is that such interactions have been mainly investigated in general circulation models where the key involved processes have to rely on uncertain parameterizations, making a definite assessment difficult.

Sensitivity of Summertime Heatwaves to Vegetation Cover in the Northern Hemisphere

2020 ◽  
Author(s):  
Jing Li ◽  
Chi-Yung Tam ◽  
Amos P. K. Tai ◽  
Ngar-Cheung Lau
Keyword(s):  
North America ◽  
Latent Heat ◽  
Vegetation Cover ◽  
Land Surface ◽  
Large Scale ◽  
Longwave Radiation ◽  
Surface Friction ◽  
Sensible Heat ◽  
Southeastern Part ◽  
Area Index

<p>Heatwaves are a serious threat to society and can lead to grave consequences. It is well known that persistent large-scale circulation anomalies are the key to generating heatwaves. Vegetation plays a vital role in energy and water exchange between land and atmosphere, through its responses to incoming radiation and emission of longwave radiation, its imposition of surface friction and transpiration. However, its impact on surface energy exchange during heatwaves is largely unknown. In this study, we first analyzed the relationship between summer heatwaves and vegetation cover, based on the Global Heatwave and Warm-spell Record (GHWR) and leaf area index (LAI) products from satellites during 1982-2011. Our results revealed differences in the correlation between heatwave characteristics and summertime LAI in different regions. In particular, lower LAI over Central Europe is associated with more frequent heatwaves locally. Over the south to the southeastern part of North America, a similar negative correlation is found. However, in the northeastern part of the continent, the reverse tends to be true, with higher-than-normal LAI associated with an increase of heatwave occurrence. These findings are in general supported by composite analyses of extreme LAI years in these regions and heatwave characteristics therein.</p><p>We speculate that the difference between surface heat flux responses for different vegetation types during heatwaves may explain the results. Focusing on North America, and using various datasets including those generated by the Global Land Data Assimilation System (GLDAS) with three different land surface models (CLM, MOS, NOAH), three reanalysis datasets (MERRA-2, NOAA-CIRES-DOS, NCEP/NCAR), and also observations from an extensive network of flux towers, it was found that over coniferous forests (both boreal and temperate), the sensible heat anomalies increase significantly during heatwaves in high-LAI years. Also, during high-LAI years, over boreal evergreen forests (BEF), changes of latent heat anomalies are much smaller than positive sensible heat anomalies, so that BEF can prolong and amplify heatwaves significantly. On the other hand, for temperate deciduous forests (TDF) and grassland (GSL), both negative sensible heat anomalies and positive latent heat anomalies during heatwaves are found in all datasets; these response act to weaken the heatwave amplitudes. Model experiments were further carried out, in order to test the sensitivity of heatwaves to LAI forcings. It was found that heatwaves are most sensitive to BEF LAI variations, but the response of heatwaves are opposite between middle and high latitudes when BEF LAI increased. For TDF and GSL, heatwaves shortened slightly when LAI increased.</p>

Regional Impacts of Irrigation in Mexico and the Southwestern United States on Hydrometeorological Fields in the North American Monsoon Region

2016 ◽  
Vol 17 (12) ◽  
pp. 2981-2995 ◽  
Author(s):  
Alex Mahalov ◽  
Jialun Li ◽  
Peter Hyde
Keyword(s):  
North American ◽  
Land Surface ◽  
Large Scale ◽  
Rainfall Variability ◽  
Convective Available Potential Energy ◽  
North American Monsoon ◽  
Western Slope ◽  
Surface Model ◽  
Southern Mexico ◽  
The Impact

Abstract In this study, the impacts of Mexican and southwestern U.S. agricultural and urban irrigation on North American monsoon (NAM) rainfall and other hydrometeorological fields are investigated using the Weather Research and Forecasting (WRF) Model by implementing an irrigation scheme into the WRF–land surface model. Taking the 2000–12 monsoon seasons as examples, multiple WRF simulations with irrigation are conducted by designing different crops’ maximum allowable water depletions (SWm). In comparison with gridded rainfall observations in urban and rural area, the WRF simulations with/without irrigation generally capture the observations very well, but with underestimation along the western slope of the Sierra Madre Occidental (SMO) and overestimation over southern Mexico. The simulations of WRF with irrigation are slightly improved over those without irrigation, compared with rainfall and sounding observations. Sensitivity studies reveal that the impact of irrigation on rainfall varies with location and NAM rainfall variability. Irrigation increases rainfall in eastern Arizona–western New Mexico and in northwestern Mexico because of the irrigation-induced increases of convective available potential energy (CAPE) and precipitable water. Overall, irrigation decreases rainfall in western Arizona, along the western slope of the SMO, and in central Mexico because of irrigation-induced increases of convective inhibition (CIN), decreases of CAPE, and/or large-scale water vapor divergence.

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