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At least 1,171 records · Page 65

Climate change in the circum-North Atlantic region during the last deglaciation

A survey of new and published palaeoclimate data indicates that both the high- and low-latitude North Atlantic regions were characterized by at least three synchronous periods of abrupt climate change during the last glacial-to-interglacial transition. Climate model results suggest that changes in the melting history of the Laurentide Ice Sheet may explain much of this nonlinear response of the climate system to astronomical (Milankovitch) forcing.

Overpeck, Jonathan T.↗

Role of the Polar Oceans in Global Climate

The project focused on ice-ocean model development and in particular on the assimilation of ice motion data and ice concentration data into both regional and global models. Many of the resulting publications below deal with improvements made in the physics treated by the model and the procedures for assimilating data. Several papers examine how the ability of the model to simulate the past behavior of the ice cover, especially to represent the ice thickness and ice deformation, is improved by data assimilation. A second aspect of the work involved interpretation of modeled behavior. Resulting papers treat the decline of arctic ice thickness over the last thirty years, and how that decline was caused by a slight warming of the near-surface atmosphere, and also how large variation in ice thickness are due to changes in wind patterns associated with a well- known oscillation of the atmospheric circulation. The research resulted in over 20 published papers on these topics.

Rothrock, D. A.↗

Climate Hazard Assessment for Stakeholder Adaptation Planning in New York City

This paper describes a time-sensitive approach to climate change projections, developed as part of New York City's climate change adaptation process, that has provided decision support to stakeholders from 40 agencies, regional planning associations, and private companies. The approach optimizes production of projections given constraints faced by decision makers as they incorporate climate change into long-term planning and policy. New York City stakeholders, who are well-versed in risk management, helped pre-select the climate variables most likely to impact urban infrastructure, and requested a projection range rather than a single 'most likely' outcome. The climate projections approach is transferable to other regions and consistent with broader efforts to provide climate services, including impact, vulnerability, and adaptation information. The approach uses 16 Global Climate Models (GCMs) and three emissions scenarios to calculate monthly change factors based on 30-year average future time slices relative to a 30- year model baseline. Projecting these model mean changes onto observed station data for New York City yields dramatic changes in the frequency of extreme events such as coastal flooding and dangerous heat events. Based on these methods, the current 1-in-10 year coastal flood is projected to occur more than once every 3 years by the end of the century, and heat events are projected to approximately triple in frequency. These frequency changes are of sufficient magnitude to merit consideration in long-term adaptation planning, even though the precise changes in extreme event frequency are highly uncertain

Horton, Radley M.↗

End-Use Savings Shapes Measure Documentation: Window Film

This documentation focuses on a single end-use savings shape measure - window film. The window film studied in this analysis, called solar control film, is a passive retrofit solution for windows that does not involve window replacement. This type of film is composed of transparent, tinted, or metalized laminated polyester layers and can be attached to an existing window surface (either on the exterior or interior side of the window). The properties of the window film are designed to shift the thermal and optical performances of the overall glazing system in order to serve various needs the customer would have (e.g., heat, glare). While the practical goal of purchasing and installing a window film varies widely in the real market, this study only focuses on the goal of energy savings, and highlighting the corresponding emissions. Other important aspects that customers typically consider include visual comfort, privacy, aesthetics, ultraviolet protection, etc. Thus, in practice, customers often choose a window film product not only to save energy (or cost) but also to mitigate issues around glare, excessive light, daytime privacy, or inconsistent appearance of the building. Window film products that were modeled in this analysis significantly reduced the solar heat gain coefficient of the overall glazing system, resulting in better energy savings for buildings in hot climate regions. However, significantly reducing the solar heat gain coefficient that can block unfavorable heat during the summer can actually harm blocking favorable heat during the winter. By applying window films on a stock of buildings covering various load and weather conditions, this analysis highlights when (e.g., time of day) and where (e.g., geospacial location) we can save energy with window films.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Stratospheric Benzene and Hydrocarbon Aerosols Detected in Saturn's Auroral Regions

Context. Saturn's polar upper atmosphere exhibits significant auroral activity; however, its impact on stratospheric chemistry (i.e. the production of benzene and heavier hydrocarbons) and thermal structure remains poorly documented. Aims. We aim to bring new constraints on the benzene distribution in Saturn's stratosphere, to characterize polar aerosols (their vertical distribution, composition, thermal infrared optical properties), and to quantify the aerosols' radiative impact on the thermal structure. Methods. Infrared spectra acquired by the Composite Infrared Spectrometer (CIRS) on board Cassini in limb viewing geometry are analysed to derive benzene column abundances and aerosol opacity profiles over the 3 to 0.1 mbar pressure range. The spectral dependency of the haze opacity is assessed in the ranges 680-900 and 1360-1440 cm(exp −1). Then, a radiative climate model is used to compute equilibrium temperature profiles, with and without haze, given the haze properties derived from CIRS measurements. Results. On Saturn's auroral region (80 deg S), benzene is found to be slightly enhanced compared to its equatorial and mid-latitude values. This contrasts with the Moses & Greathouse (2005, J. Geophys. Res., 110, 9007) photochemical model, which predicts a benzene abundance 50 times lower at 80◦S than at the equator. This advocates for the inclusion of ion-related reactions in Saturn's chemical models. The polar stratosphere is also enriched in aerosols, with spectral signatures consistent with vibration modes assigned to aromatic and aliphatic hydrocarbons, and presenting similarities with the signatures observed in Titan's stratosphere. The aerosol mass loading at 80 deg S is estimated to be 1−4 × 10(exp −5) g cm(exp −2), an order of magnitude less than on Jupiter, which is consistent with the order of magnitude weaker auroral power at Saturn.We estimate that this polar haze warms the middle stratosphere by 6 K in summer and cools the upper stratosphere by 5 K in winter. Hence, aerosols linked with auroral activity can partly account for the warm polar hood observed in Saturn's summer stratosphere.

satellites↗

Observations of Saharan dust in the Caribbean and Implications for Regional Climate Variability

Massive quantities of dust aerosol, originating at source locations in the Saharan desert are frequently transported westward across the Atlantic. Saharan dust has been frequently identified at ground-based stations in South America, on Barbados, in Florida and in Texas. Recently, in July of 2000, the Puerto Rican Dust Experiment (PRiDE), consisting of researchers from the U.S. Navy, NASA, the University of Miami and the University of Puerto Rico joined together to study this important phenomenon. Numerical forecast models tracked each dust event as the dust left the African continent and transversed the Atlantic. Ground-based, ship-based, airborne and satellite sensors were used to characterize the physical and radiative properties of the dust aerosol. The dust plays an important role in terms of radiative forcing of regional climate. Satellite sensors such as NASA's EOS-MODIS aboard the Terra satellite will provide important continuing information on the dust aerosol and its climatic effects.

Remer, L.↗

Modeling the Effect of Wetlands, Flooding, and Irrigation on River Flow: Application to the Aral Sea

As the world's population continues to increase, additional stress is placed on water resources. This stress, coupled with future uncertainties regarding climate change, makes arid and semi-arid regions particularly vulnerable. One example is the Aral Sea where the freshwater inflow, which is dominated by snowmelt runoff, has decreased significantly since the expansion of intensive irrigation in the 1960s. The purpose of this paper is to use a river routing scheme from a global climate model to examine the flow of the Amu Dar'ya River into the Aral Sea. The river routing scheme is modified to include groundwater flow, flooding, and evaporative losses in the river's wetlands and floodplain, and anthropogenic withdrawals for irrigation. A set of scenarios is designed to test the sensitivity of river flow to the inclusion of these modifications into the river routing scheme. When riverine wetlands and floodplains are present, the river flow is reduced significantly and is similar to the observed flow. In addition the model results show that it is essential to incorporate human diversions to accurately represent the inflow to the Aral Sea, and they also indicate potential management strategies that might be appropriate to maintain a balance between inflow to the Sea and upstream diversions for irrigation.

Ferrari, Michael R.↗

Absorption Properties of Mediterranean Aerosols Obtained from Multi-year Ground-based and Satellite Remote Sensing Observations

Aerosol absorption properties are of high importance to assess aerosol impact on regional climate. This study presents an analysis of aerosol absorption products obtained over the Mediterranean Basin or land stations in the region from multi-year ground-based AERONET and satellite observations with a focus on the Absorbing Aerosol Optical Depth (AAOD), Single Scattering Albedo (SSA) and their spectral dependence. The AAOD and Absorption Angstrom Exponent (AAE) data set is composed of daily averaged AERONET level 2 data from a total of 22 Mediterranean stations having long time series, mainly under the influence of urban-industrial aerosols and/or soil dust. This data set covers the 17 yr period 1996-2012 with most data being from 2003-2011 (approximately 89 percent of level-2 AAOD data). Since AERONET level-2 absorption products require a high aerosol load (AOD at 440 nm greater than 0.4), which is most often related to the presence of desert dust, we also consider level-1.5 SSA data, despite their higher uncertainty, and filter out data with an Angstrom exponent less than 1.0 in order to study absorption by carbonaceous aerosols. The SSA data set includes both AERONET level-2 and satellite level-3 products. Satellite-derived SSA data considered are monthly level 3 products mapped at the regional scale for the spring and summer seasons that exhibit the largest aerosol loads. The satellite SSA dataset includes the following products: (i) Multi-angle Imaging SpectroRadiometer (MISR) over 2000-2011, (ii) Ozone Monitoring Instrument (OMI) near-UV algorithm over 2004-2010, and (iii) MODerate resolution Imaging Spectroradiometer (MODIS) Deep-Blue algorithm over 2005-2011, derived only over land in dusty conditions. Sun-photometer observations show that values of AAOD at 440 nm vary between 0.024 +/- 0.01 (resp. 0.040 +/- 0.01) and 0.050 +/- 0.01 (0.055 +/- 0.01) for urban (dusty) sites. Analysis shows that the Mediterranean urban-industrial aerosols appear "moderately" absorbing with values of SSA close to approximately 0.94-0.95 +/- 0.04 (at 440 nm) in most cases except over the large cities of Rome and Athens, where aerosol appears more absorbing (SSA approximately 0.89-0.90 +/- 0.04). The aerosol Absorption Angstrom Exponent (AAE, estimated using 440 and 870 nm) is found to be larger than 1 for most sites over the Mediterranean, a manifestation of mineral dust (iron) and/or brown carbon producing the observed absorption. AERONET level-2 sun-photometer data indicate the existence of a moderate East-West gradient, with higher values over the eastern basin (AAEEast. = 1.39/AAEWest. = 1.33) due to the influence of desert dust. The North-South AAE gradient is more pronounced, especially over the western basin. Our additional analysis of AERONET level-1.5 data also shows that organic absorbing aerosols significantly affect some Mediterranean sites. These results indicate that current climate models treating organics as nonabsorbing over the Mediterranean certainly underestimate the warming effect due to carbonaceous aerosols. A~comparative analysis of the regional SSA variability has been attempted using satellite data. OMI and MODIS data show an absorbing zone (SSA approximately 0.90 at 470-500 nm) over Northeastern Africa that does not appear in the MISR retrievals. In contrast, MISR seems able to observe the East-West SSA gradient during summer, as also detected by AERONET. Also, the analysis of SSA provided by satellites indicates that the aerosol over the Mediterranean Sea appears less absorbing during spring (MAM) than summer (JJA).

satellite remote sensing observations↗

Relating Satellite-Based Contrail Detection to NWA Output

Contrail-induced cloud cover has been shown to be a significant factor in regional climate change over the United States of America. As air traffic increases, the potential for globally significant impacts also rises. To better understand and predict these potential climatic effects, it is necessary to develop models that can accurately represent contrail properties based on ambient atmospheric variables including temperature, relative humidity and winds. Several high-resolution numerical weather analyses (NWA) including the 20-km Rapid Update Cycle (RUC) and the University of Oklahoma Center for Analysis and Prediction of Storms Advanced Regional Prediction System (ARPS) can provide the temperature, humidity and wind information necessary to diagnose contrail formation. One outstanding problem that must be addressed to achieve a realistic simulation of contrails is the large uncertainties in upper tropospheric relative humidity (UTH) in numerical weather analyses. Current numerical weather analyses tend to underestimate UTH due to large dry biases in the balloon soundings used to construct the analyses. To evaluate each of the models, we match several months of contrail properties derived from satellite and surface observations to the NWA-derived humidity, vertical velocity, wind shear and atmospheric stability. The relationships between several contrail properties (including optical depth and areal contrail coverage) and the NWA-derived statistics will be analyzed to determine under which atmospheric conditions widespread contrail outbreaks are favored.

Duda, David P.↗

Investigation of the Seasonal Freeze/Thaw Cycle of Soils in the GAPP Regions

The objective of this project is to understand the current and future impacts and feedbacks of seasonally frozen ground on the regional and global climate system and the ecosystem as a whole. More specifically, we proposed to: investigate the dynamics of the seasonally freezing and thawing processes and their relations to current climatic conditions through in situ data analysis and numerical modeling; develop a comprehensive algorithm to detect surface soil freeze/thaw status for snow-free land surface using passive microwave remote sensing data and for snow-covered land surface using numerical modeling, and validate the algorithm and numerical model using available ground-based measurements; investigate seasonal and inter-annual variations of frozen soils in the GAPP regions using data generated from the new validated algorithm and their relations to the environmental factors such as air temperature, snow cover, surface morphology, soil type and soil moisture; generate a frozen soil data set which describes the timing, duration, thickness, and area extent of seasonally frozen ground for the period from 1978 to present. The proposed research will be accomplished through data analysis, remote sensing, and numerical modeling.

FREEZE-THAW TESTS↗

NPCC4: New York City Climate Risk Information 2022—Observations and Projections

New York City (NYC) faces many challenges in the coming decades due to climate change and its interactions with social vulnerabilities and uneven urban development patterns and processes. This New York City Panel on Climate Change (NPCC) report contributes to the Panel’s mandate to advise the city on climate change and provide timely climate risk information that can inform flexible and equitable adaptation pathways that enhance resilience to climate change. This report presents up-to-date scientific information as well as updated sea level rise projections of record. We also present a new methodology related to climate extremes and describe new methods for developing the next generation of climate projections for the New York metropolitan region. Future work by the Panel should compare the temperature and precipitation projections presented in this report with a subset of models to determine the potential impact and relevance of the “hot model” problem. NPCC4 expects to establish new projections-of-record for precipitation and temperature in 2024 based on this comparison and additional analysis. Nevertheless, the temperature and precipitation projections presented in this report may be useful for NYC stakeholders in the interim as they rely on the newest generation of global climate models.

NPCC4↗

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral shortwave instruments produce high-resolution and information-dense spectra, thus offering the opportunity to reduce uncertainties in retrieval products. We are in the process of developing a retrieval that uses the very fast Principal Component Radiative Transfer Model in the solar spectral region (PCRTM-Solar) in the forward model calculations. This retrieval will use measured reflectances from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder) instruments. In this manuscript we present progress towards a reference retrieval employing a widely used, verified, accurate, yet computationally slower radiative transfer modeling technique. The reference retrieval, while too slow for using the complete hyperspectral measurement, will allow us to study the behavior of retrieval products and help us verify results from our in-development fast retrieval. Both retrievals will use the optimal estimation retrieval framework. In this manuscript we present results from an uncertainty analysis considering three uncertainty sources for a cirrus cloud retrieval in the form of error covariance matrices: reflectance uncertainty due to water vapor, the reflectance uncertainty due to ice crystal scattering assumptions, and the instrument measurement uncertainty. Results show that the uncertainty due to habit selection is the largest, while that due to water vapor is at most 0.6% relative to channel reflectance. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water.

Cirrus cloud↗

Spatial controls of methane uptake in upland soils across climatic and geological regions in Greenland

Abstract In the Arctic, the spatiotemporal variation of net methane uptake in upland soils depends on unresolved interactive controls between edaphic and microbial factors not yet included in current models, underpinning the uncertainty of upscaling the Arctic methane budget. Here we show that upland soils in Greenland are consistent methane sinks (−1.83 ± 0.19 nmol methane g −1 dw d −1 ) across a N-S (64–83 °N) pedoclimatic transect. We demonstrate that methane oxidizers abundance, soil pH, and available soil copper are important controls on the spatial variation in methane oxidation. We revised a soil biogeochemical model with a high-resolution land classification and meteorological data for Greenland and tested it against our methane uptake measurements. The model simulated well the magnitudes of observed methane uptake but not the spatial variation across all sites. This work provides novel insights into the controls of methane uptake, which are critical for the accuracy of methane budgets.

Environmental Sciences & Ecology↗

Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive

This dataset contains results from two GIPL runs for RCP4.5 and RCP8.5 across the Seward Peninsula. The model was run on 500 m by 500 m resolution for the period 1901-2100. Meteo variables include forcing air temperature and precipitation as well as modeled maxim and average snow height. This dataset also includes ground temperature at 10 different depths for every grid cell, active layer depth and talik thickness. Auxillary variables include ecotype map and projected latitude and longitude. Ground temperature borehole data that is used for model calibration and validation of GIPL2 for Seward Peninsula 500 m resolution model runs for 1901-2100 time period. Dataset also includes calibrated model parameters for future use. The main purpose of this dataset is the reproducibility of research. Data were produced for regional permafrost distribution assessment for present and future, in addition, model parameters can be used for future model runs on adjacent territories. This dataset contains *.pdf, *.txt, *.csv, and *.nc. files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

A Regional-Scale Assessment of Satellite Derived Precipitable Water Vapor Across The Amazon Basin

Atmospheric water vapor is widely recognized as a key climate variable, linking an assortment of poorly understood and complex processes. It is a major element of the hydrological cycle and provides a mechanism for energy exchange among many of the Earth system components. Reducing uncertainty in our current knowledge of water vapor and its role in the climate system requires accurate measurement, improved modeling techniques, and long-term prediction. Satellites have the potential to satisfy these criteria, as well as provide high resolution measurements that are not available from conventional sources. The focus of this paper is to examine the temporal and mesoscale variations of satellite derived precipitable water vapor (PW) across the Amazon Basin. This region is pivotal in the functioning of the global climate system through its abundant release of latent heat associated with heavy precipitation events. In addition, anthropogenic deforestation and biomass burning activities in recent decades are altering the conditions of the atmosphere, especially in the planetary boundary layer. A physical split-window (PSW) algorithm estimates PW using images from the GOES satellites along with the NCEP/NCAR Reanalysis data that provides the first guess information. Retrievals are made at a three-hourly time step during daylight hours in the Amazon Basin and surrounding areas for the months of June and October in 1988 (dry year) and 1995 (wet year). Spatially continuous fields are generated 5 times daily at 12Z, 15Z, 18Z, 21Z, and 00Z. These fields are then averaged to create monthly and 3 hourly monthly grids. Overall, the PSW estimates PW reasonable well in the Amazon with MAE ranging from 3.0 - 9.0 mm and MAE/observed mean around 20% in comparison to radiosonde observations. The distribution of PW generally mimics that of precipitation. Maximum values (42 - 52 mm) are located in the Northwest whereas minimum values (18 - 27 mm) are found along Brazil's East coast. Aside from the East coast, PW has a stronger north-south gradient than that of rainfall. As for the temporal variation of PW, June (1988 and 1995) experiences a peak about 1400 local time, corresponding to a maximum in air temperature. In contrast, October (1988 and 1995) experiences a maximum early in the day, 1100 local time, with a gradual decrease toward nighttime.

DeLiberty, Tracy↗

A multistage distributionally robust optimization approach to water allocation under climate uncertainty

This paper investigates a Multistage Distributionally Robust Optimization (MDRO) approach to water allocation under climate uncertainty. The MDRO is formed by creating sets of conditional distributions (called conditional ambiguity sets) on a finite scenario tree. The distributions in the conditional ambiguity sets remain close to a nominal conditional distribution according a ø-divergence (e.g., Kullback-Leibler divergence, Hellinger distance, Burg entropy, etc.). Here, the paper discusses a decomposition algorithm to solve the resulting MDRO with ø-divergences, which uses the dual formulation and solves only linear subproblems instead of convex ones. Some properties of the algorithm such as generating feasible policies and valid upper/lower bounds are established. The paper then applies the modeling and solution techniques to allocate water in a rapidly-developing area of Tucson, Arizona. Tucson, like many arid and semi-arid regions around the world, faces considerable uncertainty in its ability to provide water for its citizens in the future. The primary sources of uncertainty in the Tucson region include (1) unpredictable population growth, (2) the availability of water from the Colorado River, and (3) the effects of climate variability on water consumption. This paper integrates forecasts for all these sources of uncertainty into a single optimization model for robust and sustainable water allocation. Then, it uses this model to analyze the value of constructing additional treatment facilities to reduce future water shortages. The results indicate that the MDRO approach can be very valuable for water managers by providing insights to minimize their risks and help them plan for the future.

54 ENVIRONMENTAL SCIENCES↗

Identifying Chemical and Optical Smoke Signatures in Suborbital Observations to Improve Model Projections

Biomass Burning (BB) fires are expected to occur more frequently in the future due to climate change, the build‐up of fuels due to fire suppression, and the expansion of the wildland‐urban interface [Schoennagel et al., 2017; Shivdenko & Schepaschenko, 2013; Stevens et al., 2014; Turner et al., 2019; Yue et al., 2015; Tilman et al., 2001]. Accurate knowledge of the abundance, distribution, and optical properties of absorbing aerosols such as BB smoke is essential to understanding regional and global aerosol radiative effects [Boucher et al., 2013]. It is recognized that differing fuel types (e.g., rice straw, ponderosa pine), combustion modes (i.e., flaming, smoldering or both) and temperature/ moisture content produce smoke with differing optical characteristics (e.g., aerosol light scattering and absorption) and component mixing ratios [e.g., BC, OC and inorganic species such as sulfate, potassium, chloride; Streets et al. 2003; Reid et al., 2005a, b; Janhäll et al., 2010; Sayer et al., 2014]. However, climate models often ascribe a fixed set of emission factors [i.e., amount of particulate for a given species released in the atmosphere per unit dry fuel burned; Darmenov and Dasilva, 2013] and optical properties [Hess et al., 1998] to all BB aerosol plumes, inherently limiting accurate representation of the global and regional heterogeneity of BB. The overarching goal of the proposed work is to improve the microphysical and optical representation of different types of Biomass Burning in Chemistry Transport Models. Our strategy is to capitalize on multiple airborne campaigns (e.g., ARCTAS, SEAC4RS, ORACLES, FIREX-AQ), which sampled different types of BB plumes at different aging stages. Models, when improved and combined with satellite, airborne, and ground observations will help address many aerosol science objectives from the NASA Decadal survey [National Academies of Sciences, Engineering, and Medicine. 2018].

Meloe Shenandoah F Kacenelenbogen↗

Improving High-Resolution Weather Forecasts using the Weather Research and Forecasting (WRF) Model with an Updated Kain-Fritsch Scheme

Efforts to improve the prediction accuracy of high resolution (1-10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at these spatial scales due to uncertainties in initial meteorological conditions and/or grid-scale cloud microphysics schemes. In particular, it is still unclear to what extent a subgrid-scale convection scheme could be modified to bring in scale-awareness for improving high-resolution short-term precipitation forecasts in the WRF model. To address these issues, we introduced scale-aware parameterized cloud dynamics for high-resolution forecasts by making several changes to the Kain-Fritsch (KF) convective parameterization scheme in the WRF model. These changes include subgrid-scale cloud-radiation interactions, a dynamic adjustment timescale, impacts of cloud updraft mass fluxes on grid-scale vertical velocity, and lifting condensation level-based entrainment methodology that includes scale dependency. A series of 48-hour retrospective forecasts using a combination of three treatments of convection (KF, updated KF, and the use of no cumulus parameterization), two cloud microphysics schemes and two types of initial condition datasets were performed over the U.S. southern Great Plains on 9- and 3-km grid spacings during the summers of 2002 and 2010. Results indicate that (1) the source of initial conditions play a key role in high-resolution precipitation forecasting, and (2) our updated KF scheme greatly alleviates the excessive precipitation at 9-km grid spacing and improves results at 3-km grid spacing as well. Overall, we found that the updated KF scheme incorporated into a high-resolution model does provide better forecasts for precipitation location and intensity.

convective parameterization↗