Convective Parameterization Schemes Research Articles

Parameterizing Convective Organization Effects With a Moisture‐PDF Approach in Climate Models: Concept and a Regional Case Simulation

AbstractWe propose a parameterization scheme of convective organization effects based on a moisture‐distribution approach, which can reflect aggregation of convective cells within a model grid as well as the interaction between convection and spatial heterogeneity in free‐troposphere moisture. With this concept, convective cells in an aggregated state are surrounded by air that is moister than the grid‐mean condition, which provides a “shielding” effect favorable for deeper convective updrafts. Such effects are represented quantitatively via utilizing a schematic diagram about the geometric interpretation of convective cluster, dry area, and their contact area, in which both the convective cluster size and dry area fraction increase during the development of convection. Our sensitivity analyses indicate that the new scheme performs well in capturing the mean precipitation features. Excluding the convective organization effects in the model leads to a considerable reduction in the simulated precipitation magnitude. Notably, there exists an inverse relationship between background mean moisture condition and sub‐grid moisture variability for a given rain rate, suggesting that with a high spatial heterogeneity in free‐troposphere moisture, convection can still develop and maintain its strength under relatively dry background conditions, consistent with the convection‐permitting model simulation. Overall, our new parameterization of convective organization effects can successfully reproduce the relationship between precipitation and sub‐grid moisture variability, which is a missing element in traditional convection parameterization schemes but important for the simulations of precipitation variability at various scales in climate models.

WRF ensemble dynamical downscaling of precipitation over China using different cumulus convective schemes

Ensemble dynamical downscaling of precipitation over China was conducted based on simulations of the Weather and Research Forecasting model using both Kain–Fritsch and Grell cumulus convective parameterization schemes. The simulations were driven by ERA-Interim reanalysis data with 25-km horizontal resolution for the period 1980–2015. Results indicated that superior performance was achieved by the ensemble based on the two different schemes because certain observed signals were captured complementarily by each scheme over distinct regions. For climatological mean precipitation, the ensemble improved the annual mean pattern, probability distribution, and seasonal evolution of precipitation. With regard to interannual variation, the ensemble showed the highest skill in representing the series of precipitation anomalies at regional scales for all subregions. Improvement was also evident in the spatial patterns of the dominant precipitation variability modes and the corresponding temporal variations. For extreme precipitation, several indices were selected, and the ensemble was better able to capture the main features with higher spatial pattern correlations and closer magnitudes. The advantages of the ensemble are due to its appropriate regime specific weights derived from the Kain–Fritsch and Grell schemes

Lightning forecasting in Bangladesh based on the lightning potential index and the electric potential

This work documents the performances of diagnostic and explicit lightning forecasts for selected high impact weather events over Bangladesh. The lightning flashes are calculated by three methods: (1) a diagnostic lightning parameterization that bases its algorithm on the level of neutral buoyancy from a convective parameterization scheme, (2) lightning potential index (LPI) using local graupel and ice contents, and (3) explicit prediction of electric fields and lightning initiation from WRF-ELEC. Five lightning events that occurred on 02 April 2019, 17 May 2019, 20 April 2020, 26 May 2020, and 20 May 2021 were examined to evaluate the forecasting capability of each scheme for the lightning over a 24-h forecast period. Prior to diagnosing lightning activity, the composite radar reflectivity and the neighborhood score metrics (ETS, FSS) for hourly rainfall were analyzed to determine if the simulated precipitation structure is consistent with the observations. Analyses based on performance diagrams were also included for a better illustration of how simulations perform on predicting precipitation. The spatial distribution of LPI and lightning flashes is compared against the NASA Lightning Imaging Sensor (LIS) dataset. The qualitative results show that in most of the studied cases, there is a good agreement between the observations and the WRF-ELEC-based simulations in terms of detecting the primary regions of lightning activity. The LPI based predictions perform also considerably well. The results from this endeavor constitute an essential initiative towards the implementation of an effective operational lightning warning system to mitigate lightning-related hazards in Bangladesh and northeast India.

Convection Modeling of Pure-steam Atmospheres

Abstract Condensable species are crucial to shaping planetary climate. A wide range of planetary climate systems involve understanding nondilute condensable substances and their influence on climate dynamics. There has been progress on large-scale dynamical effects and on 1D convection parameterization, but resolved 3D moist convection remains unexplored in nondilute conditions, though it can have a profound impact on temperature/humidity profiles and cloud structure. In this work, we tackle this problem for pure-steam atmospheres using three-dimensional, high-resolution numerical simulations of convection in postrunaway atmospheres. We show that the atmosphere is composed of two characteristic regions, an upper condensing region dominated by gravity waves and a lower noncondensing region characterized by convective overturning cells. Velocities in the condensing region are much smaller than those in the lower, noncondensing region, and the horizontal temperature variation is small. Condensation in the thermal photosphere is largely driven by radiative cooling and tends to be statistically homogeneous. Some condensation also happens deeper, near the boundary of the condensing region, due to triggering by gravity waves and convective penetrations and exhibits random patchiness. This qualitative structure is insensitive to varying model parameters, but quantitative details may differ. Our results confirm theoretical expectations that atmospheres close to the pure-steam limit do not have organized deep convective plumes in the condensing region. The generalized convective parameterization scheme discussed in Ding & Pierrehumbert is appropriate for handling the basic structure of atmospheres near the pure-steam limit but cannot capture gravity waves and their mixing which appear in 3D convection-resolving models.

Evaluation and Comparison of Two Deep Convection Parameterization Schemes at Convection-Permitting Resolution

AbstractCoarse-grained results from a large-eddy simulation (LES) using the Weather Research and Forecasting (WRF) Model were compared in this study with the WRF simulations at a typical convection-permitting horizontal grid spacing of 3 km for an idealized case of deep moist convection. The purpose of this comparison is to identify major differences at the subgrid process level between two widely used deep convection parameterization schemes in the WRF Model. It is shown that there are considerable differences in subgrid process representations between the two schemes due to different parameterization formulations and underlying assumptions. The two schemes not only differ in trigger function, subgrid cloud model, and closure assumptions but also disagree with the coarse-grained LES results in terms of vertical mass flux profiles. Thus, it is difficult to discern which scheme is more advantageous over the other at the subgrid process level. The conclusions from this study highlight the importance of establishing benchmarks using observations and LES to develop and evaluate convection parameterization schemes suitable for models at convection-permitting resolution.

Improving Numerical Weather Prediction–Based Near-Cloud Aviation Turbulence Forecasts by Diagnosing Convective Gravity Wave Breaking

AbstractBased on a convective gravity wave drag parameterization scheme in a numerical weather prediction (NWP) model, previously proposed near-cloud turbulence (NCT) diagnostics for better detecting turbulence near convection are tested and evaluated by using global in situ flight data and outputs from the operational global NWP model of the Korea Meteorological Administration for one year (from December 2016 to November 2017). For comparison, 11 widely used clear air turbulence (CAT) diagnostics currently used in operational NWP-based aviation turbulence forecasting systems are separately computed. For selected cases, NCT diagnostics predict more accurately localized turbulence events over convective regions with better intensity, which is clearly distinguished from the turbulence areas diagnosed by conventional CAT diagnostics that they mostly failed to forecast with broad areas and low magnitudes. Although overall performance of NCT diagnostics for one whole year is lower than conventional CAT diagnostics due to the fact that NCT diagnostics exclusively focus on the isolated NCT events, adding the NCT diagnostics to CAT diagnostics improves the performance of aviation turbulence forecasting. Especially in the summertime, performance in terms of an area under the curve (AUC) based on probability of detection statistics is the best (AUC = 0.837 with a 4% increase, compared to conventional CAT forecasts) when the mean of all CAT and NCT diagnostics is used, while performance in terms of root-mean-square error is the best when the maximum among combined CAT and single NCT diagnostic is used. This implies that including NCT diagnostics to currently used NWP-based aviation turbulence forecasting systems should be beneficial for safety of air travel.

Suppressing Grid-Point Storms in a Numerical Forecasting Model

The convective parameterization scheme of the Korean Integrated Model (KIM) is tentatively modified to suppress grid-point storms in the Western Pacific Ocean. The KIM v3.2.11 suffers from the numerical problem that grid-point storms degrade forecasts in the tropical oceans and around the Korean Peninsula. Another convective parameterization scheme, the new Tiedtke scheme, is implemented in the KIM. The artificial storms are suppressed in the test version because the heating and drying tendencies of the new Tiedtke scheme are stronger than those of the default KIM Simplified Arakawa-Schubert (KSAS) scheme. Based on this comparison, the KSAS scheme is modified to strengthen its heating and drying tendencies by reducing the entrainment and detrainment rates. The modified KSAS scheme suppresses grid-point storms and thus decreases grid-scale precipitation in a summertime case simulation. Twenty 10-day forecasts with the default convection scheme (KSAS) and twenty forecasts with the modified scheme are conducted and compared with each other, confirming that the modified KSAS scheme successfully suppresses grid-point storms.

Sensitivity of convective parameterization schemes in regional climate model: precipitation extremes over India

Sensitivity of convective parameterization schemes in regional climate model: precipitation extremes over India

The interaction of deep convection with the general circulation in Titan’s atmosphere. Part 2: Impacts on the climate

The impact of methane convection on the circulation of Titan is investigated in the Titan Atmospheric Model (TAM), using a simplified Betts–Miller (SBM) moist convection parameterization scheme. We vary the reference relative humidity (RHSBM) and relaxation timescale of convection (τ) parameters of the SBM scheme. Titan’s atmosphere is mostly insensitive to changes in τ, but convective instability and precipitation are highly impacted by changes in RHSBM. Convection behavior changes from infrequent (<1 per Titan year), intense events at summer solstice that quickly encompass the entire globe at low RHSBM to near-continuous precipitation at the poles during summer at high RHSBM (85%). The intermediate regime (RHSBM=70%–80%) consists of frequent events (∼10 per Titan year) of moderate intensity that are limited in meridional extent to their respective hemisphere. Using results from the Titan Regional Atmospheric Modeling System (TRAMS) and observations, we tune the parameters of the SBM parameterization with optimum values of RH=80% and τ=28800 s. We present a simulated decadal climatology that qualitatively matches observations of Titan’s humidity and cloud activity and generally resembles previous results with TAM. Comparing this simulation to one without moist convection demonstrates that convection strengthens the meridional circulation, warms the mid-levels and cools the surface at the poles, and magnifies zonal-mean global moisture anomalies.

Precipitation Simulation from the Cumulus Convection Parameterization Schemes Based on the WRF Model in the Weihe River Basin, china

Two cumulus convection parameterization schemes, i.e., Kain-Fritsch (K-F) and Grell-3 based on the V4.1.2 Weather Research and Forecasting (WRF) model, were used to simulate the summer precipitation in the Weihe River Basin using hourly precipitation data at the resolution of 5 km and 2 km. the precipitation experiment results at different resolution were compared and analyzed. The root square error and correlation coefficient were used to verify and evaluate the simulation results. The results show that in K-F and Grell-3, the two cumulus model simulations with a resolution of 5 km can explain the spatial distribution pattern of precipitation and the diurnal variation process, and the experimental simulation results are consistent with the actual observations. The summer precipitation simulation in June, July, and August is highly sensitive to the two cumulus parameter schemes of K-F and Grell-3. The simulated precipitation value is higher than the actual value, and the root mean square errors (RMSEs) of K-F and Grell-3 schemes are 5.49-13.29 and 5.69-10.88, respectively. In terms of precipitation simulation, Grell-3 scheme is better than K-F scheme, especially in areas with heavy rainfall. When the resolution is increased to 2 km, the regions with heavy precipitation can be displayed more finely. The influence of water vapor flux and vertical velocity changes on precipitation in the Weihe River is analyzed from two aspects, i.e., water conditions and atmospheric instability. From the simulation results by the K-F scheme, the vertical velocity fluctuations are unstable and strong in the convective area, and the convective rainfall is relatively high. From the simulation results by Grell-3, the vertical velocity is large and increased rapidly, which is conducive to the generation of large-scale heavy precipitation. Both schemes are very sensitive to the simulation of water vapor transport and vertical velocity. This study provides a basis for the research on the adaptability of regional precipitation simulation.

Multi-Model Multi-Physics Ensemble: A Futuristic Way to Extended Range Prediction System

In an endeavor to design better forecasting tools for real-time prediction, the present work highlights the strength of the multi-model multi-physics ensemble over its operational predecessor version. The exiting operational extended range prediction system (ERPv1) combines the coupled, and its bias-corrected sea-surface temperature forced atmospheric model running at two resolutions with perturbed initial condition ensemble. This system had accomplished important goals on the sub-seasonal scale skillful forecast; however, the skill of the system is limited only up to 2 weeks. The next version of this ERP system is seamless in resolution and based on a multi-physics multi-model ensemble (MPMME). Similar to the earlier version, this system includes coupled climate forecast system version 2 (CFSv2) and atmospheric global forecast system forced with real-time bias-corrected sea-surface temperature from CFSv2. In the newer version, model integrations are performed six times in a month for real-time prediction, selecting the combination of convective and microphysics parameterization schemes. Additionally, more than 15 years hindcast are also generated for these initial conditions. The preliminary results from this system demonstrate appreciable improvements over its predecessor in predicting the large-scale low variability signal and weekly mean rainfall up to 3 weeks lead. The subdivision-wise skill analysis shows that MPMME performs better, especially in the northwest and central parts of India.

Improving Convection Trigger Functions in Deep Convective Parameterization Schemes Using Machine Learning

AbstractDeficiencies in convection trigger functions, used in deep convection parameterizations in General Circulation Models (GCMs), have critical impacts on climate simulations. A novel convection trigger function is developed using the machine learning (ML) classification model XGBoost. The large‐scale environmental information associated with convective events is obtained from the long‐term constrained variational analysis forcing data from the Atmospheric Radiation Measurement (ARM) program at its Southern Great Plains (SGP) and Manaus (MAO) sites representing, respectively, continental mid‐latitude and tropical convection. The ML trigger is separately trained and evaluated per site, and jointly trained and evaluated at both sites as a unified trigger. The performance of the ML trigger is compared with four convective trigger functions commonly used in GCMs: dilute convective available potential energy (CAPE), undilute CAPE, dilute dynamic CAPE (dCAPE), and undilute dCAPE. The ML trigger substantially outperforms the four CAPE‐based triggers in terms of the F1 score metric, widely used to estimate the performance of ML methods. The site‐specific ML trigger functions can achieve, respectively, 91% and 93% F1 scores at SGP and MAO. The unified trigger also has a 91% F1 score, with virtually no degradation from the site‐specific training, suggesting the potential of a global ML trigger function. The ML trigger alleviates a GCM deficiency regarding the overprediction of convection occurrence, offering a promising improvement to the simulation of the diurnal cycle of precipitation. Furthermore, to overcome the black box issue of the ML methods, insights derived from the ML model are discussed, which may be leveraged to improve traditional CAPE‐based triggers.

Operational Precipitation Forecast Over China Using the Weather Research and Forecasting (WRF) Model at a Gray-Zone Resolution: Impact of Convection Parameterization

AbstractThe quantitative precipitation forecast in the 9 km operational modeling system (without the use of a convection parameterization scheme) at the Shanghai Meteorological Service (SMS) usually suffers from excessive precipitation at the grid scale and less-structured precipitation patterns. Two scale-aware convection parameterizations were tested in the operational system to mitigate these deficiencies. Their impacts on the warm-season precipitation forecast over China were analyzed in case studies and two-month retrospective forecasts. The results from case studies show that the importance of convection parameterization depends on geographical regions and weather regimes. Considering a proper magnitude of parameterized convection can produce more realistic precipitation distribution and reduce excessive grid-scale precipitation in southern China. In the northeast and southwest China, however, the convection parameterization plays an insignificant role in precipitation forecast because of strong synoptic-scale forcing. A statistical evaluation of the two-month retrospective forecasts indicates that the forecast skill for precipitation in the 9-km operational system is improved by choosing proper convection parameterization. This study suggests that improvement in contemporary convection parameterizations is needed for their usage for various meteorological conditions and reasonable partitioning between parameterized and resolved convection.

Means and Extremes: Evaluation of a CMIP6 Multi-Model Ensemble in Reproducing Historical Climate Characteristics across Alberta, Canada

This study evaluates General Circulation Models (GCMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for their ability in simulating historical means and extremes of daily precipitation (P), and daily maximum (Tmax), and minimum temperature (Tmin). Models are evaluated against hybrid observations at 2255 sub-basins across Alberta, Canada using established statistical metrics for the 1983–2014 period. Three extreme indices including consecutive wet days (CWD), summer days (SD), and warm nights (WN) are defined based on the peak over the threshold approach and characterized by duration and frequency. The tail behaviour of extremes is evaluated using the Generalized Pareto Distribution. Regional evaluations are also conducted for four climate sub-regions across the study area. For both mean annual precipitation and mean annual daily temperature, most GCMs more accurately reproduce the observations in northern Alberta and follow a gradient toward the south having the poorest representation in the western mountainous area. Model simulations show statistically better performance in reproducing mean annual daily Tmax than Tmin, and in reproducing annual mean duration compared to the frequency of extreme indices across the province. The Kernel density curves of duration and frequency as simulated by GCMs show closer agreement to that of observations in the case of CWD. However, it is slightly (completely) overestimated (underestimated) by GCMs for warm nights (summer days). The tail behaviour of extremes indicates that GCMs may not incorporate some local processes such as the convective parameterization scheme in the simulation of daily precipitation. Model performances in each of the four sub-regions are quite similar to their performances at the provincial scale. Bias-corrected and downscaled GCM simulations using a hybrid approach show that the downscaled GCM simulations better represent the means and extremes of P characteristics compared to Tmax and Tmin. There is no clear indication of an improved tail behaviour of GPD based on downscaled simulations.

Future Changes in Seasonality in East Africa from Regional Simulations with Explicit and Parameterized Convection

AbstractThe East African precipitation seasonal cycle is of significant societal importance, and yet the current generation of coupled global climate models fails to correctly capture this seasonality. The use of convective parameterization schemes is a known source of precipitation bias in such models. Recently, a high-resolution regional model was used to produce the first pan-African climate change simulation that explicitly models convection. Here, this is compared with a corresponding parameterized-convection simulation to explore the effect of the parameterization on representation of East Africa precipitation seasonality. Both models capture current seasonality, although an overestimate in September–October in the parameterized simulation leads to an early bias in the onset of the boreal autumn short rains, associated with higher convective instability and near-surface moist static energy. This bias is removed in the explicit model. Under future climate change both models show the short rains getting later and wetter. For the boreal spring long rains, the explicit convection simulation shows the onset advancing but the parameterized simulation shows little change. Over Uganda and western Kenya both simulations show rainfall increases in the January–February dry season and large increases in boreal summer and autumn rainfall, particularly in the explicit convection model, changing the shape of the seasonal cycle, with potential for pronounced socioeconomic impacts. Interannual variability is similar in both models. Results imply that parameterization of convection may be a source of uncertainty for projections of changes in seasonal timing from global models and that potentially impactful changes in seasonality should be highlighted to users.

Sensitivity evaluation of the different physical parameterizations schemes in regional climate model RegCM4.5 for simulation of air temperature and precipitation over North and West of Iran

In this research the dynamic downscaling method by Regional Climate Model (RegCM4.5) was used to assess the performance and sensitivity of seasonal simulated North and West of Iran (NI&WI) climate factors to different convection schemes, and transforms the large-scale simulated climate variables into land surface states over the North of Iran (NI) and West of Iran (WI). A 30-year (1986–2015) numerical integration simulation of climate over NI&WI was conducted using the regional climate model RegCM4.5 nested in one-way ERA-Interim reanalysis data. The Grell, Kuo and MIT-Emanuel cumulus convection with Holtslag and University of Washington (UW) planetary boundary layer (PBL) parameterization schemes were applied in the running of RegCM4.5 to test their capability in simulating precipitation and temperature in winter-spring (January–April) over NI and WI. The results demonstrated that the RegCM4.5 model has a good potential for simulating the variables and trend of surface temperature over the NI and WI region. Magnitude of the model bias for land surface temperature over different regions of Iran varies by convection parameterization schemes. In most cases, the root mean square error between post-processed simulated seasonal average temperature and observation value was less than 1 °C, but there is a systematic “cold bias”. In general, with respect to land surface temperature simulations, a better performance is obtained when using post-processing model’s data with Holtslag PBL-Grell and Holtslag PBL-Kuo configuration schemes, compared to the other simulations, over the NI&WI region. Also, the UW PBL convection schemes show a relatively excellent spatial correlations and normalized standard deviations closer to 1 for thirty-year seasonal land surface temperature anomalies over the entire NI&WI region. However, the simulation accuracy of model for precipitation is not as optimal as for temperature. The dominant feature in model simulations is a dry bias with the largest average value (∼1.04 mm/day) over NI region, while the lowest mean bias precipitation (∼−0.47 mm/day), mainly located in WI region. In the comparison of six configuration convection schemes, the Emanuel scheme has been proven to be the most accurate for simulating winter-spring seasonal mean precipitation over NI&WI region. The accuracy of the scheme also showed great difference in simulated station interpolation of precipitation, which urges the improvement for the simulation capability of spatial distribution of precipitation. In general, for seasonal variation of precipitation, the Emanuel convection with two (Holtslag, UW) PBL configuration schemes outperforms with a good correlation score between 0.7−0.8 and normalized standard deviations closer to 1.

Sensitivity of tropical cyclones to convective parameterization schemes in RegCM4

This study investigates the sensitivity of simulated tropical cyclones (TC) affecting the Philippines to convective parameterization schemes (CPS) in the Regional Climate Model Version 4 (RegCM4). Five ERA-Interim driven RegCM4 simulations at 25-km horizontal resolution were conducted utilizing the CPS of Grell with Arakawa–Schubert closure (GR), Emanuel (EM), Kain–Fritsch (KF), Tiedtke (TE), and a combined Grell scheme over land and Emanuel over the ocean (GR-EM). Comparisons made between the observed and RegCM4-simulated TCs covering a 30-year period (1981–2010) indicate that the EM scheme yields an annual-mean TC frequency that is closest to observations. The GR-EM scheme, on the other hand, closely reproduces the observed seasonal patterns of TC tracks, spatial patterns of TC track density and TC-associated rainfall, and TC lifespan. The KF scheme is the only CPS that was able to simulate intense TCs (maximum wind speed > 40 m s–1) within the domain. In contrast, both GR and TE schemes largely underestimated the TC frequency, and were only able to simulate weak TCs. Such underestimation in the TC frequency and intensity in the GR and TE simulations can be attributed to the dry mid-tropospheric environment and the absence of a large area with positive low-level relative vorticity over the Pacific Ocean inhibiting TC formation and further development over the area. These findings would be helpful in selecting the more appropriate CPS for TC-related model simulations over the Philippines and in further model improvements, given the climate modeling imperfections and associated biases.

On Thunderstorm Microphysics under Urban Heat Island, Sea Breeze, and Cold Front Effects in the Metropolitan Area of S&amp;#227;o Paulo, Brazil

This work discusses issues related to the impact of urbanization on the microphysical processes of precipitating systems associated with synoptic, mesoscale, and local scale systems. Among the issues addressed is the impact of urban heat island (UHI) in São Paulo city center and urban densification (UD) in the Metropolitan Area of São Paulo (MASP) on the microphysical, dynamic, and thermodynamic properties and distribution of precipitation and heavier rainfall from sea-breeze (SB) e cold-front (CF) combined during their space-time evolutions. For this purpose, it used four components: classification of hydrometeors with fuzzy logic, calculation of the raindrop diameters, an estimate of liquid water mass and ice mass from polarimetric-variables measured with dual-pola- rization X-band meteorological radar. The results indicated that urban densification (UD) and heat island (UHI) of the São Paulo city center impact the formation of precipitation, liquid water mass, and ice mass, depth, and duration of a thunderstorm. It was also observed the asymmetric configuration of the thunderstorm is induced by the strong convergence in the São Paulo city center, and this strong convergence is induced by the intense heat island (UHI) in the São Paulo city center. Was also observed that this event that is formed in the Metropolitan Area of São Paulo (MASP) depends on microphysical processes of mixed-phase of the cloud (water and ice) above the 0°C isotherm for the production of intense rain and cold pool at the surface. These important microphysical processes within long-lasting secondary convective cells over the São Paulo city center should be taken into account on convective parameterization schemes as well as the associated cold pool dynamics.

Evaluation of Daily Precipitation from the ERA5 Global Reanalysis against GHCN Observations in the Northeastern United States

Precipitation is a primary input for hydrologic, agricultural, and engineering models, so making accurate estimates of it across the landscape is critically important. While the distribution of in-situ measurements of precipitation can lead to challenges in spatial interpolation, gridded precipitation information is designed to produce a full coverage product. In this study, we compare daily precipitation accumulations from the ERA5 Global Reanalysis (hereafter ERA5) and the US Global Historical Climate Network (hereafter GHCN) across the northeastern United States. We find that both the distance from the Atlantic Coast and elevation difference between ERA5 estimates and GHCN observations affect precipitation relationships between the two datasets. ERA5 has less precipitation along the coast than GHCN observations but more precipitation inland. Elevation differences between ERA5 and GHCN observations are positively correlated with precipitation differences. Isolated GHCN stations on mountain peaks, with elevations well above the ERA5 model grid elevation, have much higher precipitation. Summer months (June, July, and August) have slightly less precipitation in ERA5 than GHCN observations, perhaps due to the ERA5 convective parameterization scheme. The heavy precipitation accumulation above the 90th, 95th, and 99th percentile thresholds are very similar for ERA5 and the GHCN. We find that daily precipitation in the ERA5 dataset is comparable to GHCN observations in the northeastern United States and its gridded spatial continuity has advantages over in-situ point precipitation measurements for regional modeling applications.

Adaptation of the Predicted Particles Properties (P3) Microphysics Scheme for Large-Scale Numerical Weather Prediction

AbstractA parameterization for the subgrid-scale cloud and precipitation fractions has been incorporated into the Predicted Particle Properties (P3) microphysics scheme for use in atmospheric models with relatively coarse horizontal resolution. The modified scheme was tested in a simple 1D kinematic model and in the Canadian Global Environmental Multiscale (GEM) model using an operational global NWP configuration with a 25-km grid spacing. A series of 5-day forecast simulations was run using P3 and the much simpler operational Sundqvist condensation scheme as a benchmark for comparison. The effects of using P3 in a global GEM configuration, with and without the modifications, were explored through statistical metrics of common forecast fields against upper-air and surface observations. Diagnostics of state variable tendencies from various physics parameterizations were examined to identify possible sources of errors resulting from the use of the modified scheme. Sensitivity tests were performed on the coupling between the deep convection parameterization scheme and the microphysics, specifically regarding assumptions in the physical properties of detrained ice. It was found that even without recalibration of the suite of moist physical parameterizations, substituting the Sundqvist condensation scheme with the modified P3 microphysics resulted in some significant improvements to the temperature and geopotential height bias throughout the troposphere and out to day 5, but with degradation to error standard deviation toward the end of the integrations, as well as an increase in the positive bias of precipitation quantities. The modified P3 scheme was thus shown to hold promise for potential use in coarse-resolution NWP systems.