While the terrain-following (sigma) system of representing topography in atmospheric models has been dominant for about the last 60 years, already half a century ago problems using the system were reported in areas of steep topography. A number of schemes had been proposed to address these problems. However, when topography steepness exceeds a given limit all these schemes except the vertical interpolation of the pressure gradient begin to use model information that for physical reasons they should not use.
A radical departure from the system was that of the step-topography eta; but its attractiveness was reduced by the discovery of the corner separation problem. The shaved-cell scheme, nowadays referred to as cut-cell, was free of that problem, and was tested subsequently in idealized as well as real case experiments with encouraging results. The eta discretization has lately been refined to make it also a cut-cell scheme. Another method referred to usually as immersed boundary method enabling treatment of terrain as complex as urban landscape came from computational fluid dynamics. It was made available coupled to the atmospheric Weather Research and Forecasting model.
Results of recent experiments of the cut-cell Eta driven by European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble members are analyzed. In these experiments, all cut-cell Eta members achieved better verification scores with respect to 250 hPa wind speed than their ECMWF driver members. This occurred when an upper-tropospheric trough was crossing the Rocky Mountains barrier. These results are considerably less favorable for the Eta when switched to use sigma, i.e., Eta/sigma, pointing to the benefits of using topography intersecting as opposed to terrain-following systems. But even so the Eta/sigma shows an advantage over its driver members, suggesting that its other features deserve attention.
This study compares the regional characteristics of heavy rain clouds in terms of Cloud Top Height (CTH) and Storm Height (SH) from long-term Tropical Rainfall Measuring Mission (TRMM) observations. The SH is derived from Precipitation Radar reflectivity, and the CTH is estimated, using visible and infrared scanner brightness temperature (10.8 µm) and reanalysis temperature profiles. As the rain rate increases, the average CTH and average SH increase, but by different degrees in different regions. Heavy rainfall in continental rainfall regimes, such as Central Africa and the United States, is characterized by high SH, in contrast to oceanic rainfall regions, such as the northwestern Pacific, Korea, and Japan; the increased atmospheric instability in dry environments is interpreted as a continental flood mechanism. Conversely, heavy rain events in Korea and Japan occur in a thermodynamically near-neutral environment with large amounts of water vapor, which are characterized by the lowest CTH, SH, and ice water content. The northwestern Pacific exhibits the lowest SH in humid environments, similar to Korea and Japan; however, this region also characteristically exhibits the highest convective instability condition, as well as high CTH and CTH–SH values, in contrast to Korea and Japan. The observed CTH and SH characteristics of heavy rain clouds should be useful for evaluating and improving satellite-based precipitation estimates and numerical model cloud parameterization.
From 9 to 11 September 2015, the Kanto and Tohoku regions of Japan experienced an extremely heavy rainfall event. The synoptic-scale field was characterized by two typhoons, Etau (T1518) and Kilo (T1517). After Etau made landfall in the Tokai region and transformed into an extra-tropical cyclone over the Sea of Japan, meridionally-oriented rain bands persisted over the Kanto region for about 12 hours and caused heavy rainfall, particularly over the Tochigi prefecture. During this time, Kilo approached the eastern ocean of the Kanto region. In this study, we examine the role of Kilo in this event by conducting numerical experiments using a stretched version of the Nonhydrostatic Icosahedral Atmospheric Model, configured with a minimum grid interval of about 5.6 km. The control experiment reproduced intense rain bands around the same period and place as the observed event, although they were not reproduced in an experiment with a longer lead time. Sensitivity experiments were conducted, in which Kilo was weakened by removing moisture in its central region with a longer lead time. In contrast to the expectation that reduced moisture would lead to a weaker typhoon, and hence weaker rain, the sensitivity experiment reproduced the rain band with a realistic location, but 5 % less precipitation than the control experiment. Furthermore, this experiment indicated that precipitation over the outer band of Etau, which covers the Kanto region, increased by 10 % compared to the control experiment. We found that a southeasterly wind, induced by a high pressure ridge between Kilo and the Kanto region, played a greater role in supplying moisture to the Kanto region than the strong easterly wind produced by the pressure gradient between Kilo and the Okhotsk high. In this case, weaker Kilo resulted in an enhanced northwestward moisture flux associated with the ridge, thereby inducing heavier rainfall over the Kanto region.
The southerly surface wind index over the summertime East Asia (SWI) is strengthened in the future in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). However, the differences among the models are much larger than the ensemble average. The empirical orthogonal function (EOF) analysis is applied to the future changes in the East Asian surface pressure pattern responsible for the SWI. The ensemble average and five EOF modes for the pressure patterns and the associated precipitation changes are identified, and their possible sources are examined.
The CMIP5 ensemble mean change in the summertime Asia Pacific surface pressure pattern possesses the characteristics of the first to third modes. The first and second mode components contribute to the positive SWI in the future, but are cancelled mostly by the third mode component. The first mode is high surface pressure anomalies over low Asia Pacific sea surface temperature. The second mode is related to warm temperature anomalies over the Northern Hemisphere continents and the increased equatorial Pacific precipitation. The large model dependence of the SWI is created by the third mode, which represents the weak Pacific High in northern East Asia and is characterized with suppressed vertical motions over the northern Indian and Pacific oceans. The fourth mode is the Okhotsk High. The fifth mode represents the east–west contrast of the southern East Asian surface pressure anomalies and is associated with the Northern Hemisphere ocean temperatures. The fourth and fifth modes feature the mean projection using the 10 models reproducing an accurate present-day summertime East Asian climatology.
The mode-related suppressed vertical motions in global warming reflect the present-day vertical motion (i.e., precipitation) climatology; hence, the future increase/decrease in the SWI tends to be projected by models simulating the relatively small/large Asia Pacific monsoon precipitation over the tropical oceans, except near the mountains, in the present-day model climatology.
Accurate forecast of global horizontal irradiance (GHI) is one of the key issues for power grid managements with large penetration of solar energy. A challenge for solar forecasting is to forecast the solar irradiance with a lead time of 1–8 hours, here termed as intra-day forecast. This study investigated an algorithm using a long short-term memory (LSTM) model to predict the GHI in 1–8 hours. The LSTM model has been applied before for inter-day (> 24 hours) solar forecast but never for the intra-day forecast. Four years (2010–2013) of observations by the National Renewable Energy Laboratory (NREL) at Golden, Colorado were used to train the model. Observations in 2014 at the same site were used to test the model performance. According to the results, for a 1–4 hour lead time, the LSTM-based model can make predictions of GHIs with root-mean-square-errors (RMSE) ranging from 77 to 143 W m−2, and normalized RMSEs around 18.4–33.0 %. With five-minute inputs, the forecast skill of LSTM with respect to smart persistence model is 0.34–0.42, better than random forest forecast (0.27) and the numerical weather forecast (−0.40) made by the Weather Research and Forecasting (WRF) model. The performance levels off beyond 4-hour lead time. The model performs better in fall and winter than in spring and summer, and better under clear-sky conditions than under cloudy conditions. Using adjacent information from the reanalysis as extra inputs can further improve the forecast performance.
The impact of assimilating thermodynamic profiles measured with lidars into the Weather Research and Forecasting (WRF)-Noah-Multiparameterization model system on a 2.5-km convection-permitting scale was investigated. We implemented a new forward operator for direct assimilation of the water vapor mixing ratio (WVMR). Data from two lidar systems of the University of Hohenheim were used: the water vapor differential absorption lidar (UHOH WVDIAL) and the temperature rotational Raman lidar (UHOH TRL). Six experiments were conducted with 1-hour assimilation cycles over a 10-hour period by applying a 3DVAR rapid update cycle (RUC): 1) no data assimilation 2) assimilation of conventional observations (control run), 3) lidar–temperature added, 4) lidar–moisture added with relative humidity (RH) operator, 5) same as 4) but with the WVMR operator, 6) both lidar–temperature and moisture profiles assimilated (impact run). The root-mean-square-error (RMSE) of the temperature with respect to the lidar observations was reduced from 1.1 K in the control run to 0.4 K in the lidar–temperature assimilation run. The RMSE of the WVMR with respect to the lidar observations was reduced from 0.87 g kg−1 in the control run to 0.53 g kg−1 in the lidar-moisture assimilation run with the WVMR operator, while no improvement was found with the RH operator; it was reduced further to 0.51 g kg−1 in the impact run. However, the RMSE of the temperature in the impact run did not show further improvement. Compared to independent radiosonde measurements, the temperature assimilation showed a slight improvement of 0.71 K in the RMSE to 0.63 K, while there was no conclusive improvement in the moisture impact. The correlation between the temperature and WVMR variables in the static-background error-covariance matrix affected the improvement in the analysis of both fields simultaneously. In the future, we expect better results with a flow-dependent error covariance matrix. In any case, the initial attempt to develop an exclusive thermodynamic lidar operator gave promising results for assimilating humidity observations directly into the WRF data assimilation system.
This study proposes a new energy balance model to determine the cloud fraction of low-level clouds. It is assumed that the horizontal cloud field consists of several individual cloud cells with a similar structure. Using a high–resolution simulation dataset with a wide numerical domain, we conducted an energy budget analysis. Here we show that the energy injected into the domain by surface flux is approximately balanced with that loss due to radiation and advection due to large–scale motion. The analysis of cloud cells within the simulated cloud field showed that the cloud field consists of a number of cloud cells with similar structures. We developed a simple model for the cloud fraction from the energy conservation equation. The cloud fraction determined using the model developed in this study was able to quantitatively captured the simulated cloud fraction.
This study examined the effects of an upper-level anticyclonic circulation and a lower-level cyclonic circulation on tropical cyclone (TC) genesis. We ran idealized simulations using the Advanced Research Weather Research and Forecasting (WRF-ARW) model. The simulation results show that the upper-level anticyclonic circulation makes a negative contribution to TC genesis, while the lower-level cyclonic circulation makes a positive contribution. The upper-level anticyclonic circulation results in slower TC genesis due to a substantial vertical zonal wind shear that shifts the upper-level vortex eastward from its initial position. This shift is unfavorable for the vortex's vertical alignment and warm core maintenance. This substantial vertical zonal wind shear is associated with the asymmetric vertical motion and associated diabatic heating, induced by the lower-level beta gyre. The upper-level anticyclonic circulation increases the westerly wind north of the vortex, resulting in a substantial vertical westerly wind shear. Thus, the initial upper-level anticyclonic circulation is unnecessary for TC genesis. The strong upper-level anticyclonic circulation, generally observed with a strong TC, should be considered a result of deep convection. The strong lower-level winds induce large surface heat fluxes and vorticity due to the superposition of the large-scale lower-level cyclonic circulation and vortex. These conditions lead to strengthened convection and diabatic heating and a quick build-up of positive vorticity, resulting in rapid TC genesis.
Uncertainty in numerical weather forecasts arising from an imperfect knowledge of the initial condition of the atmospheric system and the discrete modeling of physical processes is addressed with ensemble prediction systems. The breeding method allows the creation of initial condition perturbations in a simple and computationally inexpensive way. This technique uses the full nonlinear dynamics of the system to identify fast-growing modes in the analysis fields, obtained from the difference between control and perturbed runs rescaled at regular time intervals. This procedure is more suitable for the high-resolution ensemble forecasts required to reproduce small-scale high-impact weather events, as the complete nonlinear model is employed to generate the perturbations. The underdispersion commonly observed in ensemble forecasts emphasizes the need to develop methods that increase ensemble spread and diversity at no cost to forecast skill. In this sense, we investigate the benefits of different breeding techniques in terms of ensemble diversity and forecast skill for a mesoscale ensemble over the Western Mediterranean region. In addition, we propose a new method, Bred Vectors Tailored Ensemble Perturbations, designed to control the scale of the perturbations and indirectly the ensemble spread. The combination of this method with orthogonal bred vectors shows significant improvements in terms of ensemble diversity and forecast skill with respect to the current arithmetic methods.
The tropical oceans spawn hundreds of tropical disturbances during the tropical cyclone (TC) peak season every year, but only a small fraction eventually develop into TCs. In this study, using observations from the Global Precipitation Measurement (GPM) satellite, tropical disturbances over the western North Pacific (WNP) from July to October during 2014–2016 are categorized into developing and nondeveloping groups to investigate the differences between satellite-retrieved convective and stratiform precipitation properties in both the inner-core (within 200 km of the disturbance center) and outer-core (within 200–400 km of the disturbance center) regions. The developing disturbances experience a remarkably more oscillatory process in the inner-core region than in the outer-core region. The large areal coverage of strong rainfall in the inner-core region of the disturbance breaks into scattered remnants and then reorganizes and strengthens near the disturbance center again. Contrarily, the precipitation characteristics in the nondeveloping group evolve more smoothly. It can be summarized that disturbances prone to developing into a TC over the WNP satisfy two essential preconditions in terms of precipitation characteristics. First, a large fraction of stratiform precipitation covers the region that is within 400 km from the disturbance center. The mean vertically integrated unconditional latent heating rate of stratiform and convective precipitation in the developing group above 5.5 km is 6.6 K h−1 and 2.4 K h−1, respectively; thus, the stratiform rainfall makes a major contribution to the warming of the upper troposphere. Second, strong convective precipitation occurs within the inner-core region. Compared with stratiform precipitation, which plays a critical role in warming the mid-to-upper levels, the most striking feature of convective precipitation is that it heats the mid-to-lower troposphere. Overall, the formation of TCs evolving from parent disturbances can be regarded as an outcome of the joint contribution from the two distinct types (convective and stratiform) of precipitation clouds.
The impacts of the saturation adjustment type approach to sub-grid-scale (SGS) ice clouds in a turbulent closure scheme on the high clouds and their response to global warming were investigated based on the radiative–convective equilibrium experiments (RCEs). This was motivated by the fact that the time scale of ice condensation is several orders of magnitude longer than that for liquid water. The RCEs were conducted with uniform sea surface temper atures over the spherical domain for the Earth's radius without rotation using an explicit cloud microphysics and a non-hydrostatic icosahedral atmospheric model. This study revealed that suppressing the phase change effect associated with the SGS ice condensation on the buoyancy of the SGS turbulence could cause approximately a 20 % reduction of the total high cloud covers and a significantly different response of high cloud amounts to global warming due to the change in static stability near high clouds, which leads to weaker vertical heat transport at a sub-grid scale there. Since the typical value of the time scale of the ice-phase cloud is much longer than that of liquid water and the ice supersaturation is in general, using the saturation adjustment type approach for SGS ice clouds could lead to an overestimation of the effect of ice condensation for the turbulent mixing and model biases in simulations with both cloud resolving and general circulation models. The present result underlines the critical nature of the treatment of SGS ice clouds in turbulence schemes which reflects a realistic ice condensation time scale not only for a better representation of high clouds in the current climate but for an improved projection of changes of high clouds due to global warming.
A method is proposed to gain insight into ozone recovery over Antarctica. The following metrics relating to the ozone hole are considered: minimum total column ozone (TCO3) within the hole, TCO3 at the South Pole, area of the ozone hole, mass of ozone loss within the hole, and density of loss per unit area. The daily metric values, based on the Royal Netherlands Meteorological Institute archives of the ozone hole, are averaged for each year over the period 1979–2019 for the following intervals: 1–30 September, 15 September–15 October, 1–31 October, 15 October–15 November, and 1–30 November. The following indicators of the ozone hole recovery are examined: the metric recovery rate by 2019 (i.e., the change between its extreme and its 2019 level divided by the change between the extreme year and 1980) and the year of metric recovery. The recovery year is derived by forward-in-time extrapolation of the metric linear trend found for the period 2000–2019. The uncertainties in these indicators are obtained using a bootstrap approach analyzing statistics of the synthetic time series of the metrics. A comparison of the proposed ozone hole healing indicators with the indicators inferred from the equivalent effective stratospheric chlorine (EESC) loading over Antarctica (22.1 % and year 2076) shows to what extent recovery of the ozone layer is associated with EESC effects. For the mass and density of ozone loss in the periods 1–30 September and 15 September–15 October, the metric recovery rate by 2019 is ∼ 2 times larger and the recovery year is at least 20–30 years earlier than the corresponding indicators of the EESC changes. Therefore, the ozone hole is recovering faster during these periods than expected based on the stratospheric halogen loading alone.