Kain-Fritsch Convective Scheme Research Articles

A Modified Kain–Fritsch Convection Scheme for Extended-Range Prediction

Abstract This paper describes the convection parameterization in the Navy Earth System Prediction Capability (ESPC) system developed at the Naval Research Laboratory, with a focus on the scheme configuration in the v2.0 system. The parameterization is an update of a modification of the Kain–Fritsch convection scheme by Ridout et al. based on an assumed quasi-balance of updraft parcel buoyancy at the cloud-base level. Scheme updates include the treatment of updraft/environment mixing and additional updraft model features, including a parameterized reduction in net detrainment in cases of significant near-cloud upward motion, and a modified cloud-top condition. The scheme includes two convection modes: a turbulence-triggered and a dynamically triggered mode. Hindcast sensitivity with Navy ESPC to features of the scheme is investigated with 45-day integrations from 1 November 2011 for a portion of the Dynamics of the Madden–Julian Oscillation (DYNAMO) research program observational period that overlaps with the occurrence of two episodes of the MJO. The modified updraft mixing is critical in the hindcasts for consistent MJO eastward propagation, whereas the additional updraft updates significantly improve the representation of small-scale rainfall variability, while helping to inhibit development of excessive low-level easterly flow. The added turbulence-triggered convection mode helps to improve the representation of the separation of periods of enhanced MJO convection. The relative occurrence frequency of convective cloud-top height and column water vapor in the equatorial Indo-Pacific is investigated in the hindcasts, showing significant similarities with satellite retrieval results. Significance Statement This study describes the scheme used to represent the effects of convective clouds such as cumulus and cumulonimbus (thunderstorm clouds) in computerized 45-day global forecasts of the Earth system in a forecast model developed at the Naval Research Laboratory, focusing on the version currently undergoing testing for use by the U.S. Navy. Some of the development history and physical basis for the scheme are presented, and results from test simulations are included. The test results investigate potential forecast sensitivity to various features of the scheme and illustrate that the scheme can successfully represent certain effects of convective clouds on large-scale storm systems in the tropics that have global-scale impacts on extended-range (several weeks) prediction of the Earth’s atmosphere/ocean system.

Study of Convection using the Kain-Fritsch Convective Scheme of WRF Numerical Model

We have studied a convection from a convective cloud that brought damage to people and economy on 14-15 July of 2010 in the area of Ulaanbaatar city, using ARW, the third version of the WRF simulation program. The results have been compared to meteorological observed data and the reliability was 87%.

A study on the Sensitivity of Parameterizations for Regional Climate models in the Simulation of Tropical Cyclones over Western Pacific Ocean and East Sea

This study investigates the sensitivity of physical parameterization schemes in two regional dynamic models clWRF (the climate Weather Research and Forecasting) and RegCM (the Regional Climate Model) in the simulation of tropical cyclones (TCs) over Western Pacific Ocean and East Sea. The experiments include 12-cases for clWRF model and 6-cases for RegCM model were conducted to run the simulation, with the same domain parameters, resolution 25 km. Results show that the clWRF can simulate TCs well with the Betts-Miller-Janjic convection scheme and WSM6 microphysics, in which convection schemes are more influential, and the RegCM is with the Kain-Fritsch convection scheme and Zeng oceanic flux. Regarding the number of TCs simulation, most of them are higher than observed and CFSnl (Climate Forecast System analysis) data, therein the RegCM is higher than the clWRF.

Sensitivity of Dynamical Downscaling Seasonal Precipitation Forecasts to Convection and Land Surface Parameterization in a High-Resolution Regional Climate Model

Both convection and land surface parameterization influence seasonal precipitation forecasts. In this study, the sensitivity of dynamical downscaling seasonal precipitation forecasts to convection and land surface parameterization was investigated by nesting the Weather Research and Forecasting (WRF) model into the NCEP’s Climate Forecast System version 2 (CFSv2) retrospective forecasts with four convective schemes: Kain–Fritsch (KF), Betts–Miller–Janjic (BMJ), Grell–Freitas (GF), and new simplified Arakawa–Schubert (NSAS) schemes, and two land surface schemes: Noah and simplified Simple Biosphere (SSiB) schemes over the Han River basin. The CFSv2 model biases are reduced when the KF convective scheme is used in the wet summer season. However, negative biases still exist especially when the combination of BMJ and SSiB schemes is used. Compared with CFSv2 reforecasts and other combinations of schemes, the forecast skills of spatial patterns of precipitation anomalies are highest when the combination of KF and Noah schemes is used in summer. In contrast, the combination of BMJ and SSiB schemes shows lowest forecast skills in summer. To understand the causes of the differences in precipitation forecasts using different parameterization schemes, the simulated moisture flux convergence, thermodynamic parameters at different pressure levels, convective available potential energy (CAPE), convective inhibition (CIN), and heat fluxes are compared with the data in the ERA-5 reanalysis dataset. The WRF model-simulated moisture flux convergence is closer to that of the ERA-5 reanalysis compared with that of the CFSv2 reforecasts in summer. The vertical thermodynamic profiles also suggest that the combination of the KF and Noah schemes has caused a more unstable atmosphere, which is crucial for precipitation. In contrast, the combination of BMJ and SSiB schemes shows a less unstable atmospheric environment in summer, which explains the lower forecast skills compared with other schemes. The spatial patterns of CAPE are also improved when using the WRF model, which further enhances the precipitation forecast skills over the Han River basin.

Lightning NO<sub>2</sub> simulation over the contiguous US and its effects on satellite NO<sub>2</sub> retrievals

Abstract. Lightning is an important NOx source representing ∼10 % of the global source of odd N and a much larger percentage in the upper troposphere. The poor understanding of spatial and temporal patterns of lightning contributes to a large uncertainty in understanding upper tropospheric chemistry. We implement a lightning parameterization using the product of convective available potential energy (CAPE) and convective precipitation rate (PR) coupled with the Kain–Fritsch convective scheme (KF/CAPE-PR) into the Weather Research and Forecasting-Chemistry (WRF-Chem) model. Compared to the cloud-top height (CTH) lightning parameterization combined with the Grell 3-D convective scheme (G3/CTH), we show that the switch of convective scheme improves the correlation of lightning flash density in the southeastern US from 0.30 to 0.67 when comparing against the Earth Networks Total Lightning Network; the switch of lightning parameterization contributes to the improvement of the correlation from 0.48 to 0.62 elsewhere in the US. The simulated NO2 profiles using the KF/CAPE-PR parameterization exhibit better agreement with aircraft observations in the middle and upper troposphere. Using a lightning NOx production rate of 500 mol NO flash−1, the a priori NO2 profile generated by the simulation with the KF/CAPE-PR parameterization reduces the air mass factor for NO2 retrievals by 16 % on average in the southeastern US in the late spring and early summer compared to simulations using the G3/CTH parameterization. This causes an average change in NO2 vertical column density 4 times higher than the average uncertainty.

Evaluation of Southwest Monsoon Change over Thailand by High-resolution Regional Climate Model under High RCP Emission Scenario

The 5×5 km resolution of Non-Hydrostatic Regional Climate Model (NHRCM) developed by Meteorological Research Institute, Japan was used to evaluate the southwest monsoon season that affects to Thailand during mid-May until mid-October in each years. Bulk-type cloud microphysics, Kain-Fritsch convective scheme, Mellor-Yamada-Nakanishi-Niino level 3 PBL scheme, clear-sky radiation scheme and Hirai-Ohizumi land surface scheme are used as model configuration to simulate climate data under high emission scenario-RCP 8.5. This research was conducted for 2 time periods, i.e., baseline period (1981–2000) and future period (2080–2099), to estimate the southwest monsoon season onset and offset over Thailand by using average wind vector and cumulative precipitation in consecutive 5 days (pentad). Furthermore, the rain-break phase, less precipitation ranges during the southwest monsoon season, had also been analysed.

Convective and microphysics parameterization impact on simulating heavy rainfall in Semarang (case study on February 12th, 2015)

The meteorological model WRF-ARW version 3.8.1 is used for simulating the heavy rainfall in Semarang that occurred on February 12th, 2015. Two different convective schemes and two different microphysics scheme in a nested configuration were chosen. The sensitivity of those schemes in capturing the extreme weather event has been tested. GFS data were used for the initial and boundary condition. Verification on the twenty-four hours accumulated rainfall using GSMaPsatellite data shows that Kain-Fritsch convective scheme and Lin microphysics scheme is the best combination scheme among the others. The combination also gives the highest success ratio value in placing high intensity rainfall area. Based on the ROC diagram, KF-Lin shows the best performance in detecting high intensity rainfall. However, the combination still has high bias value.

High-Resolution Dynamical Downscaling of Seasonal Precipitation Forecasts for the Hanjiang Basin in China Using the Weather Research and Forecasting Model

AbstractManagement of water resources may benefit from seasonal precipitation forecasts, but for obtaining high enough resolution, dynamical downscaling is necessary. This study investigated the downscaling capability of the Weather Research and Forecasting (WRF) Model ARW, version 3.5, on seasonal precipitation forecasts for the Hanjiang basin in China during 2001–09, which was the water source of the middle route of the South-to-North Water Diversion Project (SNWDP). The WRF Model is forced by the National Centers for Environmental Prediction Operational Climate Forecast System, version 2 (CFSv2), and it performs at a high horizontal resolution of 10 km with four selected convection schemes. The National Oceanic and Atmospheric Administration’s Climate Prediction Center global daily precipitation data were employed to evaluate the WRF Model on multiple scales. On average, when large biases were removed, the WRF Model slightly outperformed the CFSv2 in all seasons, especially summer. In particular, the Kain–Fritsch convective scheme performed best in summer, whereas little difference was found in winter. The WRF Model showed similar results in monthly precipitation, but no time-dependent characteristics were observed for all months. The spatial anomaly correlation coefficient showed greater uncertainty than the bias and the temporal correlation coefficient. In addition, the performance of the WRF Model showed considerable regional variations. The upper basin always showed better agreement with observations than did the middle and lower parts of the basin. A comparison of the forecast and observed daily precipitation revealed that the WRF Model can provide more accurate extreme precipitation information than the CFSv2.

Performance evaluation of an operational lightning forecasting system in Europe

This study presents the evaluation of 1 year of operational lightning forecasts provided for Europe, using the Weather Research and Forecasting model coupled with a cloud-top height-based lightning parameterization scheme. Three different convective parameterization schemes were employed for parameterizing sub-grid cloud-top heights and consequently driving the lightning scheme. Triggering of the lightning scheme was controlled by means of a model-resolved microphysics-based masking filter, while the formulation for deriving lightning flash rates was also modified, assuming a single “marine” equation instead of the original equations discriminating between continental and marine lightning. Gridded lightning observations were used for evaluating model performance on a dichotomous decision basis. Analysis showed that the lightning scheme is sensitive to the parameterization of convection. In particular, the Kain–Fritsch convective scheme was found to outperform the Grell–Devenyi and Grell–Freitas schemes, showing a statistically significant better performance with respect to lightning prediction. This was most evident during the warm season, while smaller differences among the schemes were recorded during the cold season. Further, for all examined convective schemes, it was found that the application of the masking filter is desirable for improving model performance in terms of lightning forecasting. Last, the reported results revealed that the refinement of the formulation of the lightning parameterization scheme, adhering to a “global” marine equation instead of distinguishing between land and sea lightning, may be necessary in order to obtain reliable lightning forecasts.

Regional climate hindcast simulations within EURO-CORDEX: evaluation of a WRF multi-physics ensemble

Abstract. In the current work we present six hindcast WRF (Weather Research and Forecasting model) simulations for the EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with different configurations in microphysics, convection and radiation for the time period 1990–2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic temperature and precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly linked to the Grell–Devenyi convection and CAM (Community Atmosphere Model) radiation schemes, intensifies the negative bias in summer temperatures over northern Europe (max −2.5 °C). Conversely, a strong positive bias in downward shortwave radiation in summer over central (40–60%) and southern Europe mitigates the systematic cold bias over these regions, signifying a typical case of error compensation. Maximum winter cold biases are over northeastern Europe (−2.8 °C); this location suggests that land–atmosphere rather than cloud–radiation interactions are to blame. Precipitation is overestimated in summer by all model configurations, especially the higher quantiles which are associated with summertime deep cumulus convection. The largest precipitation biases are produced by the Kain–Fritsch convection scheme over the Mediterranean. Precipitation biases in winter are lower than those for summer in all model configurations (15–30%). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature and precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest pathways for model improvement.

Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation

Reasonably modeling the magnitude, south–north gradient and seasonal propagation of precipitation associated with the East Asian summer monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain–Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulated precipitation and surface energy features are generally improved. The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulated precipitation condensational heating, the monsoon circulations are also improved. By using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.

Tropical cyclone predictions over the Bay of Bengal using the high‐resolution Advanced Research Weather Research and Forecasting (ARW) model

AbstractThe performance of the high‐resolution Advanced Research Weather Research and Forecasting (ARW) model for tropical cyclone prediction over the Bay of Bengal region of the northern Indian Ocean is assessed through study of 21 cyclone systems. Error metrics in the predicted fields of maximum sustained winds (MSW), central sea‐level pressure (CSLP) and the vector track position are computed by comparison with corresponding tropical cyclone estimations from the India Meteorological Department (IMD). From 65 sensitivity experiments for five severe cyclones the combination of Kain–Fritsch (KF) convection, Yonsei University (YSU) planetary boundary layer (PBL), LIN explicit microphysics and NOAH land surface schemes are found to provide the best simulations for intensity and track prediction. It has been found that the KF convection scheme gives higher convective warming with stronger vertical motions relative to other tested cumulus schemes and that the YSU scheme simulates more realistic winds in the inflow region than other tested PBL schemes. Results of simulations with the best physics for all 21 cyclones reveal that the model had a tendency to overestimate the intensity, with mean errors ranging from −2 to 15 hPa for CSLP, 1 to 22 m s−1for MSW corresponding to 24 to 72 h predictions. The mean vector landfall position errors are found to be 122 km at 12 h, 170 km at 24 h, 244 km at 48 h and 250 km at 72 h, and 67% of the landfall errors are less than 135 km, indicating fairly good forecasts. Further, the predictions are found to be best for northward moving cyclones followed by northwestward, westward and northeastward moving cyclones.

Results of the meteorological model WRF-ARW over Catalonia, using different parameterizations of convection and cloud microphysics

The meteorological model WRF-ARW (Weather Research and Forecasting - Advanced Research WRF) is a new generation model that has a worldwide growing community of users. In the framework of a project that studies the feasibility of implementing it operationally at the Meteorological Service of Catalonia, a verification of the forecasts produced by the model in several cases of precipitation observed over Catalonia has been carried out. Indeed, given the importance of precipitation forecasts in this area, one of the main objectives was to study the sensitivity of the model in different configurations of its parameterizations of convection and cloud microphysics. In this paper, we present the results of this verification for two domains, a 36-km grid size and one of 12 km grid size, unidirectionally nested to the previous one. In the external domain, the evaluation was based on the analysis of the main statistical parameters (ME and RMSE) for temperature, relative humidity, geopotential and wind, and it has been determined that the combination using the Kain-Fritsch convective scheme with the WSM5 microphysical scheme has provided the best results. Then, with this configuration set for the external domain, some forecasts at the nested domain have been done, by combining different convection and cloud microphysics schemes, leading to the conclusion that the most accurate configuration is the one combining the convective parameterization of Kain-Fritsch and the Thompson microphysics scheme.

Regional Eta model experiments: SALLJEX and MCS development

The rainfall regime over La Plata Basin is strongly influenced by Mesoscale Convective Systems (MCS) that develop during night time, associated with the Low‐Level Jet (LLJ) to the east of the Andes. Since they are mesoscale systems, their predictability depends on the model resolution and its ability to represent the main features associated with their development. This study aimed at finding the best configuration of the regional Eta model applied to the region of frequent MCS development to the east of the Andes and to analyze the performance of the model at high resolution, simulating specific MCS cases using two convection schemes. Three experiments were performed for the South American Low‐Level Jet Experiment (SALLJEX) period. Performance of the nonhydrostatic version was better than the hydrostatic version in cases of MCS development. The use of estimated instead of climatological soil moisture in the model, improved the results for several synoptic variables. Evaluation of the convection parameterization scheme indicated a better simulation using the Kain‐Fritsch (KF) rather than the Betts‐Miller‐Janjic scheme in the cases of MCS development. Therefore the best configuration of the Eta model for the simulation of the MCS occurrences over northern Argentina is the nonhydrostatic version using KF convection scheme and estimated soil moisture. With this configuration, the model was able to simulate the precipitation and the main atmospheric characteristics associated with MCS development, such as the upper level jet, the LLJ, humidity, and associated mechanisms for ascending motion, 72 hours in advance.

Simulation of East African precipitation patterns with the regional climate model CLM

Climate simulations for East Africa have been performed with the regional climate model CLM. Here we evaluate the quality of simulated precipitation by comparing it with observations. Different schemes for convection and cloud ice have been tested in order to determine the configuration with best representation of precipitation patterns for the region. The simulated seasonal behaviour of precipitation is reasonable in all configurations, whereas absolute values are strongly influenced by the selected schemes. Best agreement with observations is achieved with the Tiedtke mass-flux convection scheme in combination with a two-category cloud ice scheme, that considers cloud ice as an additional solid form of water. With the Kain-Fritsch convection scheme the model generally overestimates precipitation. Regional differences are discussed.

Comparison of Impacts of WRF Dynamic Core, Physics Package, and Initial Conditions on Warm Season Rainfall Forecasts

Abstract A series of simulations for 15 events occurring during August 2002 were performed using the Weather Research and Forecasting (WRF) model over a domain encompassing most of the central United States to compare the sensitivity of warm season rainfall forecasts with changes in model physics, dynamics, and initial conditions. Most simulations were run with 8-km grid spacing. The Advanced Research WRF (ARW) and the nonhydrostatic mesoscale model (NMM) dynamic cores were used. One physics package (denoted NCEP) used the Betts–Miller–Janjic convective scheme with the Mellor–Yamada–Janjic planetary boundary layer (PBL) scheme and GFDL radiation package; the other package (denoted NCAR) used the Kain–Fritsch convective scheme with the Yonsei University PBL scheme and the Dudhia rapid radiative transfer model radiation. Other physical schemes were the same (e.g., the Noah land surface model, Ferrier et al. microphysics) in all runs. Simulations suggest that the sensitivity of the model to changes in physics is a function of which the dynamic core is used, and the sensitivity to the dynamic core is a function of the physics used. The greatest sensitivity in general is associated with a change in physics packages when the NMM core is used. Sensitivity to a change in physics when the ARW core is used is noticeably less. For light rainfall, the spread in the rainfall forecasts when physics are changed under the ARW core is actually less at most times than when the dynamic core is changed while NCAR physics are used. For light rainfall, the WRF model using NCAR physics is much more sensitive to a change in dynamic core than the WRF model using NCEP physics. For heavier rainfall, the opposite is true with a greater sensitivity occurring when NCEP physics is used. Sensitivity to initial conditions (Eta versus the Rapid Update Cycle with an accompanying small change in grid spacing) is generally less substantial than the sensitivity to changes in dynamic core or physics, except in the first 6–12 h of the forecast when it is comparable. As might be expected for warm season rainfall, the finescale structure of rainfall forecasts is more affected by the physics used than the dynamic core used. Surprisingly, however, the overall areal coverage and rain volume within the domain may be more influenced by the dynamic core choice than the physics used.

MM5 simulations of interannual change and the diurnal cycle of southern African regional climate

Two cumulus convection and two planetary boundary layer schemes are used to investigate the climate of southern Africa using the MM5 regional climate model. Both a wet (1988/89) and a dry (1991/92) summer (December–February, DJF) rainfall season are simulated and the results compared with three different observational sources: Climate Research Unit seasonal data (precipitation, 2 m surface temperature, number of rain days), satellite-derived diurnal precipitation and the Surface Radiation Budget diurnal short-wave fluxes and optical depth. Using the ETA model boundary layer in MM5 simulates too much incident short-wave radiation at the surface at 12 UTC, whereas the medium range forecast model boundary layer yields a diurnal cycle of short-wave radiation closer to the observed. The Betts-Miller convection scheme in MM5 simulates peak rainfall later in the day and less rain days than observed, whereas when using the Kain-Fritsch convection scheme a peak rainfall earlier in the day and more rain days than observed are simulated. The intensity of the hydrological cycle is therefore dependent on the choice of convection scheme, which in turn is further modified by the boundary layer scheme. Precipitation during the wet 1988/89 season is reasonably captured by most simulations, though using the Betts-Miller scheme more accurately simulates rainfall during the dry 1991/92 season. Mean DJF biases in the surface temperature and diurnal temperature range are consistent with biases in the number of rain days and the diurnal cycles of surface moisture and energy.