The 10 most-cited articles in Monthly Weather Review, 2016

Abstract This paper reviews the development of the ensemble Kalman filter (EnKF) for atmospheric data assimilation. Particular attention is devoted to recent advances and current challenges. The distinguishing properties of three well-established variations of the EnKF algorithm are first discussed. Given the limited size of the ensemble and the unavoidable existence of errors whose origin is unknown (i.e., system error), various approaches to localizing the impact of observations and to accounting for these errors have been proposed. However, challenges remain; for example, with regard to localization of multiscale phenomena (both in time and space). For the EnKF in general, but higher-resolution applications in particular, it is desirable to use a short assimilation window. This motivates a focus on approaches for maintaining balance during the EnKF update. Also discussed are limited-area EnKF systems, in particular with regard to the assimilation of radar data and applications to tracking severe storms and tropical cyclones. It seems that relatively less attention has been paid…

Abstract Ensembles used for probabilistic weather forecasting tend to be biased and underdispersive. This paper proposes a statistical method for postprocessing ensembles based on quantile regression forests (QRF), a generalization of random forests for quantile regression. This method does not fit a parametric probability density function (PDF) like in ensemble model output statistics (EMOS) but provides an estimation of desired quantiles. This is a nonparametric approach that eliminates any assumption on the variable subject to calibration. This method can estimate quantiles using not only members of the ensemble but any predictor available including statistics on other variables. The method is applied to the Météo-France 35-member ensemble forecast (PEARP) for surface temperature and wind speed for available lead times from 3 up to 54 h and compared to EMOS. All postprocessed ensembles are much better calibrated than the PEARP raw ensemble and experiments on real data also show that QRF performs better than EMOS, and can bring a real gain for human forecasters compared to EMOS.…

Abstract Satellite radar and radiometer data indicate that subtropical South America has some of the deepest and most extreme convective storms on Earth. This study uses the full 15-yr TRMM Precipitation Radar dataset in conjunction with high-resolution simulations from the Weather Research and Forecasting Model to better understand the physical factors that control the climatology of high-impact weather in subtropical South America. The occurrence of intense storms with an extreme horizontal dimension is generally associated with lee cyclogenesis and a strengthening South American low-level jet (SALLJ) in the La Plata basin. The orography of the Andes is critical, and model sensitivity calculations removing and/or reducing various topographic features indicate the orographic control on the initiation of convection and its upscale growth into mesoscale convective systems (MCSs). Reduced Andes experiments show more widespread convective initiation, weaker average storm intensity, and more rapid propagation of the MCS to the east (reminiscent of the MCS life cycle downstream of lower…

Abstract Atmospheric data from the Atmospheric Infrared Sounder (AIRS) were used to study an extreme warm and humid air mass transported over the Barents–Kara Seas region by an Arctic cyclone at the end of December 2015. Temperature and humidity in the region was ~10°C (>3 σ above the 2003–14 mean) warmer and ~1.4 g kg −1 (>4 σ above the 2003–14 mean) wetter than normal during the peak of this event. This anomalous air mass resulted in a large and positive flux of energy into the surface via the residual of the surface energy balance (SEB), compared to the weakly negative SEB from the surface to the atmosphere expected for that time of year. The magnitude of the downwelling longwave radiation during the event was unprecedented compared to all other events detected by AIRS in December/January since 2003. An approximate budget scaling suggests that this anomalous SEB could have resulted in up to 10 cm of ice melt. Thinning of the ice pack in the region was supported by remotely sensed and modeled estimates of ice thickness change. Understanding the impact of this anomalous air mass on…

Abstract A method that enables a mass-flux cumulus parameterization scheme (CPS) to work seamlessly in various model grids across CPS gray-zone resolutions is proposed. The convective cloud-base mass flux, convective inhibition, and convective detrainment in the simplified Arakawa–Schubert (SAS) scheme are modified to be functions of the convective updraft fraction. The combination of two updraft fractions is used to modulate the cloud-base mass flux; the first one depends on the horizontal grid space and the other is a function of the grid-scale and convective vertical velocity. The convective inhibition and detrainment of hydrometeors are also modified to be a function of the grid-size-dependent convective updraft fraction. A set of sensitivity experiments with the Weather Research and Forecasting (WRF) Model is conducted for a heavy rainfall case over South Korea. The results show that the revised SAS CPS outperforms the original SAS. At 3 and 1 km, the precipitation core over South Korea is well reproduced by the experiments with the revised SAS scheme. On the contrary, the…

Abstract An analysis of atmospheric rivers (ARs) as defined by an automated AR detection tool based on integrated water vapor transport (IVT) and the connection to heavy precipitation in the southeast United States (SEUS) is performed. Climatological water vapor and water vapor transport fields are compared between the U.S. West Coast (WCUS) and the SEUS, highlighting stronger seasonal variation in integrated water vapor in the SEUS and stronger seasonal variation in IVT in the WCUS. The climatological analysis suggests that IVT values above ~500 kg m −1 s −1 (as incorporated into an objective identification tool such as the AR detection tool used here) may serve as a sensible threshold for defining ARs in the SEUS. Atmospheric river impacts on heavy precipitation in the SEUS are shown to vary on an annual cycle, and a connection between ARs and heavy precipitation during the nonsummer months is demonstrated. When identified ARs are matched to heavy precipitation days (>100 mm day −1 ), an average match rate of ~41% is found. Results suggest that some aspects of an AR identification…

ERA-Interim reanalysis data from the past 35 years have been used with a newly developed feature tracking algorithm to identify Indian monsoon depressions originating in or near the Bay of Bengal. These were then rotated, centralized, and combined to give a fully three-dimensional 106-depression composite structure—a considerably larger sample than any previous detailed study on monsoon depressions and their structure. Many known features of depression structure are confirmed, particularly the existence of a maximum to the southwest of the center in rainfall and other fields and a westward axial tilt in others. Additionally, the depressions are found to have significant asymmetry owing to the presence of the Himalayas, a bimodal midtropospheric potential vorticity core, a separation into thermally cold (~−1.5 K) and neutral (~0 K) cores near the surface with distinct properties, and the center has very large CAPE and very small CIN. Variability as a function of background state has also been explored, with land–coast–sea, diurnal, ENSO, active–break, and Indian Ocean dipole…

An empirical flow-dependent adaptive observation error inflation (AOEI) method is proposed for assimilating all-sky satellite brightness temperatures through observing system simulation experiments with an ensemble Kalman filter. The AOEI method adaptively inflates the observation error when the absolute difference (innovation) between the observed and simulated brightness temperatures is greater than the square root of the combined variance of the uninflated observational error variance and ensemble-estimated background error variance. This adaptive method is designed to limit erroneous analysis increments where there are large representativeness errors, as is often the case for cloudy-affected radiances, even if the forecast model and the observation operator (the radiative transfer model) are perfect. The promising performance of this newly proposed AOEI method is demonstrated through observing system simulation experiments assimilating all-sky brightness temperatures from GOES-R (now GOES-16) in comparison with experiments using an alternative empirical observation error…

Abstract The capability of all-sky microwave radiance assimilation in the Gridpoint Statistical Interpolation (GSI) analysis system has been developed at the National Centers for Environmental Prediction (NCEP). This development effort required the adaptation of quality control, observation error assignment, bias correction, and background error covariance to all-sky conditions within the ensemble–variational (EnVar) framework. The assimilation of cloudy radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) microwave radiometer for ocean fields of view (FOVs) is the primary emphasis of this study. In the original operational hybrid 3D EnVar Global Forecast System (GFS), the clear-sky approach for radiance data assimilation is applied. Changes to data thinning and quality control have allowed all-sky satellite radiances to be assimilated in the GSI. Along with the symmetric observation error assignment, additional situation-dependent observation error inflation is employed for all-sky conditions. Moreover, in addition to the current radiance bias correction, a new bias…

Abstract Northern Chile hosts the driest place on Earth in the Atacama Desert. Nonetheless, an extreme precipitation event affected the region on 24–26 March 2015 with 1-day accumulated precipitation exceeding 40 mm in several locations and hourly mean rainfall rates higher than 10 mm h−1, producing floods and resulting in casualties and significant damage. The event is analyzed using ERA-Interim, surface station data, sounding observations, and satellite-based radar. Two main conditions favorable for precipitation were present at the time of the event: (i) a cutoff low (COL) off the coast of northern Chile and (ii) positive sea surface temperature (SST) anomalies over the eastern tropical Pacific. The circulation driven by the COL was strong but not extraordinary. Regional Climate Model, version 4 (RegCM4), is used to test the sensitivity of precipitation to SST anomalies by removing the warm SST anomaly in the eastern tropical Pacific. The cooler simulation produced very similar COL dry dynamics to that simulated in a control run (with observed SST), but suppressed the…