Evaluating the calculated dry deposition velocities of reactive nitrogen oxides and ozone from two community models over a temperate deciduous forest

Hourly measurements of O3, NO, NO2, PAN, HNO3 and NOy concentrations, and eddy-covariance fluxes of O3 and NOy over a temperate deciduous forest from June to November, 2000 were used to evaluate the dry deposition velocities (Vd) estimated by the WRF-Chem dry deposition module (WDDM), which adopted Wesely (1989) scheme for surface resistance (Rc), and the Noah land surface model coupled with a photosynthesis-based Gas-exchange Evapotranspiration Model (Noah-GEM). Noah-GEM produced better Vd(O3) variations due to its more realistically simulated stomatal resistance (Rs) than WDDM. Vd(O3) is very sensitive to the minimum canopy stomatal resistance (Ri) which is specified for each seasonal category assigned in WDDM. Treating Sep-Oct as autumn in WDDM for this deciduous forest site caused a large underprediction of Vd(O3) due to the leafless assumption in 'autumn' seasonal category for which an infinite Ri was assigned. Reducing Ri to a value of 70sm-1, the same as the default value for the summer season category, the modeled and measured Vd(O3) agreed reasonably well. HNO3 was found to dominate the NOy flux during the measurement period; thus the modeled Vd(NOy) was mainly controlled by the aerodynamic and quasi-laminar sublayer resistances (Ra and Rb), both being sensitive to the surface roughness length (z0). Using an appropriate value for z0 (10% of canopy height), WDDM and Noah-GEM agreed well with the observed daytime Vd(NOy). The differences in Vd(HNO3) between WDDM and Noah-GEM were small due to the small differences in the calculated Ra and Rb between the two models; however, the differences in Rc of NO2 and PAN between the two models reached a factor of 1.1-1.5, which in turn caused a factor of 1.1-1.3 differences for Vd. Combining the measured concentrations and modeled Vd, NOx, PAN and HNO3 accounted for 19%, 4%, and 70% of the measured NOy fluxes, respectively. © 2011 Elsevier Ltd

Evaluating and improving modeled turbulent heat fluxes across the North American Great Lakes

Turbulent fluxes of latent and sensible heat are important physical processes that influence the energy and water budgets of the North American Great Lakes. These fluxes can be measured in situ using eddy covariance techniques and are regularly included as a component of lake–atmosphere models. To help ensure accurate projections of lake temperature, circulation, and regional meteorology, we validated the output of five algorithms used in three popular models to calculate surface heat fluxes: the Finite Volume Community Ocean Model (FVCOM, with three different options for heat flux algorithm), the Weather Research and Forecasting (WRF) model, and the Large Lake Thermodynamic Model. These models are used in research and operational environments and concentrate on different aspects of the Great Lakes' physical system. We isolated only the code for the heat flux algorithms from each model and drove them using meteorological data from four over-lake stations within the Great Lakes Evaporation Network (GLEN), where eddy covariance measurements were also made, enabling co-located comparison. All algorithms reasonably reproduced the seasonal cycle of the turbulent heat fluxes, but all of the algorithms except for the Coupled Ocean–Atmosphere Response Experiment (COARE) algorithm showed notable overestimation of the fluxes in fall and winter. Overall, COARE had the best agreement with eddy covariance measurements. The four algorithms other than COARE were altered by updating the parameterization of roughness length scales for air temperature and humidity to match those used in COARE, yielding improved agreement between modeled and observed sensible and latent heat fluxes.</p

Exploring the Link Between Droughts and Atmospheric Aerosol Loading

Are higher atmospheric aerosol levels and droughts related? To address this question, we explore the relation between atmospheric aerosol loading and droughts using insitu and satellite observations over different urban/rural settings and heterogeneous drought conditions. A related objective was to report on the relationship and the variability between aerosol optical depth (AOD) retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) and insitu particular matter (PM2.5 and PM10) over different land use. Daily measurement of PM2.5 and PM10 data were retrieved from seven EPA air quality monitoring stations in Indiana: Virgo, Lake and Clark County in urban area, Marion, Know and Henry County in agriculture area, and Delaware County in suburban area during summer (June 1 – August 31, 2007) and winter (January 1, 2007 – March 31, 2007). The MODIS AOD data were extracted from the daily MODIS L2 land aerosol products at 0.55 um wavelength with 10 x 10 1 km resolution grids. The Geographic Information System (GIS) was used to determine the closet coordinate of observation stations from MODIS images. The drought status was obtained from the US Drought Monitor and the Standardized Precipitation Index. A regression analysis was undertaken to compare daily insitu PM 2.5 and PM10 measurements with the column integrated MODIS AOD values. Results indicate higher AOD values under drought conditions during summer period and severe drought occurrence. The data also shows higher variability and lesser correlation between the column integrated MODIS AOD and the PM measurements during summer and fall seasons. The difference between column integrated versus surface measurements is more with high values of AOD and drought condition. The average correlations between AOD and PM2.5 and PM 10 are 0.6 and 0.3 respectively for all land use. The average bias during drought condition (summer) is 0.23 and during non drought (winter) is 1.44 in urban area. In agriculture area the bias is higher than urban area during drought(0.48) but is lower than urban area during non drought (-0.14). The correlation of AOD, PM2.5 and PM 10 in agricultural area is higher than the correlation in urban area with AOD being relatively comparable with the PM 2.5 concentration. Further study is underway to understand the relationship between the air pollution feedback and climate variability and local drought conditions using satellite datasets

A Hydroclimatological Assessment of the Regional Drought Vulnerability: Indiana Drought

Characterizing and developing drought climatology continues to be a challenging problem. Also as decision makers seek guidance on water management strategies, there is a need for assessing the performance of drought indices. This requires the adaptation of appropriate drought indices that aid in monitoring droughts and hydrological vulnerability on a regional scale. This study aims to assist the process of developing a statewide water shortage and assessment plan (WSP) for the state of Indiana, USA by conducting a focused hydroclimatological assessment of drought variability. Drought climatology was assessed using in-situ observations and regional reanalysis data. A summary of precipitation and evaporation trends, estimated drought variability, worst-case drought scenarios, drought return period, as well as frequency and duration was undertaken, using multiple drought indices and streamflow analysis. Results indicated a regional and local variability in drought susceptibility. The worst-case (200 year return period) prediction showed that Indiana has a 0.5% probability of receiving 45% of normal precipitation over a 12 month drought in any years. Consistent with other studies, the Standard Precipitation Index (SPI) was found to be appropriate for detecting short-term drought conditions over Indiana. This recommendation has now been incorporated in the 2009 Indiana Water Shortage Plan. This study also highlights the difficulties in identifying past droughts from available climatic data, and our results suggest a persistent, high degree of uncertainty in making drought predictions using future climatic projections

Impact of improved land surface representation on modeling land surface atmosphere interactions under heterogeneous soil moisture conditions

The purpose of this study was to focus on how soil moisture and vegetation heterogeneity can play an important role on surface processes such as atmospheric feedback under drought and non-drought conditions. The study also aims to improve land surface representation climatology in terms of single and coupled modes of land surface and weather forecasting models. The general methodology was applied to evaluate the performance of the offline high resolution Noah land surface model (version 3.1) versus the Noah land surface model with the photosynthesis-based Gas exchange Evapotranspiration Model (Noah GEM) using different land types such as forest and agricultural areas (i.e., the Niwot Ridge Ameriflux site, USA and the Avignon CarboEurope site, France) The coupled model Weather Research - Advanced Research Version (ARW ver. 3) was also employed to help understand the coupled processes between biochemical plant physiology, soil moisture, and atmosphere. Three cases were conducted: 1) an LLJ (low level jet) event observed on 3 June 2002 over the IHOP (International H20 Project) field experiment, 2) a severe drought from 11-19 June 2006 over the Southern Great Plains region (SGP); and 3) deep and shallow convection from 10-13 June 2007 over the CLASIC (Cloud and Land Surface Interaction Campaign) SGP region. Field experiment and aircraft data from the Ameriflux and CarboEurope site, IHOP, and the CLASIC campaign were used to calibrate and validate the models. All three hypotheses have been answered showing 1) The improved land surface initial conditions (soil moisture and temperature) using a high resolution land data assimilation system (HRLDAS) will lead to enhanced predictions of summer daytime and nighttime mesoscale forcing under both weak and intense synoptically-driven cumulus convection conditions. 2) Vegetation transpiration is more efficient than soil evaporation in transporting moisture from the land surface to the atmosphere during convection simulations. 3) Interactions between local and large-scale land surface heterogeneity can affect regional convection in the Southern Great Plains for both IHOP and the CLASIC field phase (June 2002 and June 2007). This study provides some of the first results highlighting land surface-vegetation-soil moisture-atmospheric feedback as an important factor not only for daytime processes but also for improved simulation of early morning and nighttime convection. Also the improved Noah land surface model predicted more accurate energy flux, cloud radiation, rainfall, soil moisture, and soil temperature during extreme drought conditions and shallow cumulus convection. Future works include the use of finer-scale data assimilation and long-term soil moisture climatology to improve model performance. Additional plant physiological biochemistry formulations need further evaluation. The impact of convection triggers and vegetation transpiration on deep convection also need further investigation

Seventh grade students\u27 mental models of the greenhouse effect

This constructivist study investigates 225 student drawings and explanations from three different schools in the midwest in the US, to identify seventh grade students\u27 mental models of the greenhouse effect. Five distinct mental models were derived from an inductive analysis of the content of the students\u27 drawings and explanations: Model 1, a \u27greenhouse\u27 for growing plants; Model 2, greenhouse gases cause ozone depletion or formation, causing the Earth to warm; Model 3, greenhouse gases, but no heating mechanism, simply gases in the atmosphere; Model 4, greenhouse gases \u27trap\u27 the sun\u27s rays, heating the Earth; and Model 5, the sun\u27s rays are \u27bounced\u27 or reflected back and forth between the Earth\u27s surface and greenhouse gases, heating the Earth. Science textbooks are critiqued in light of the students\u27 mental models and curricular and instructional implications are explored. [ABSTRACT FROM AUTHOR

Do Earth anD EnvironmEntal SciEncE tExtbookS PromotE miDDlE anD high School StuDEntS’concEPtual DEvEloPmEnt about climatE changE?

Misconceptions or a lack of relevant prior concepts can hinder students from developing an understanding of scientific concepts. Science education research suggests that building on students\u27 prior concepts is an effective way to develop students\u27 scientific knowledge. This study reports the results of an analysis of earth and environmental science textbooks\u27 representations of climate change concepts and an examination of these presentations for possible contribution to students\u27 common misconceptions of climate change. A literature review was conducted to identify students\u27 common misconceptions of climate change. Textbooks\u27 conceptual coverage and their ways of presenting scientific conceptions were examined concerning their potential influence on further reinforcing and adding greater confidence to students\u27 misconceptions. Our results indicate that the reviewed textbooks were not designed based on careful consideration of students\u27 common misconceptions of climate change. We made recommendations for improving the conceptual clarity and organization of climate change concepts in Earth and environmental science textbooks

Students’ conceptions about the greenhouse effect, global warming, and climate change

The purpose of this study was to investigate students\u27 conceptions of the greenhouse effect, global warming, and climate change. The study was descriptive in nature and reflected a cross-age design involving the collection of qualitative data from 51 secondary students from three different schools in the Midwest, USA. These data were analyzed for content in an inductive manner to identify student\u27s conceptions. The categories that emerged from the students\u27 responses reflected different degrees of sophistication of students\u27 conceptions about the greenhouse effect, global warming, and climate change. Based on these findings we make curricular recommendations that build on the students\u27 conceptions, the IPCC Findings, the NRC (1996) science education standards, and NOAA\u27s climate literacy framework

Evaluating a New Deposition Velocity Module in the Noah Land-Surface Model

The community Noah land-surface model (Noah LSM) has been modified to couple with a photosynthesis-transpiration scheme (GEM) to estimate the deposition velocity (V ) for air quality studies. This new capability of the Noah-GEM model was tested in a point version of the National Center for Atmospheric Research-High Resolution Land Data Assimilation System (HRLDAS). Ozone V observations from June 1-30, 2002 over the AmeriFlux forested site located at Niwot Ridge, Colorado, USA (40°1′58′′N;105°32′47′′W) were used. The model reasonably captures V variations for both dry and wet conditions but has problems at nighttime. Experiments were performed to assess the sensitivity of V calculations to surface characteristics related to vegetation and soil parameters. The results indicated that V values are sensitive to accurate specifications of the leaf area index (LAI) and a lesser extent to vegetation type, maximum stomatal resistance (R ) and soil texture prescription. The model sensitivity to canopy resistance was noted for both daytime and nighttime. For this forest site, neither soil textures nor soil moisture appeared to affect V calculations significantly, though they affected the surface heat-flux estimation particularly under low soil moisture conditions. Therefore, the V estimation in the Noah model can be enhanced by either site-specific LAI or assimilating regional normal difference vegetation index information for specific time periods. Results also highlighted the need to lower the current constant R value used in Noah and other land-surface models. © 2010 Springer Science+Business Media B.V. d d d d d smax d d sma