Intraseasonal SST–precipitation relationship in a coupled reanalysis experiment using the MRI coupled atmosphere–ocean data assimilation system

To evaluate the atmosphere–ocean coupled data assimilation system developed at the Meteorological Research Institute, the lead-lag relation between the intraseasonal variations (with a time scale of 20–100 days) in precipitation and sea surface temperature (SST) is examined in the tropics. It is shown that the relationship over the tropical western Pacific in the coupled reanalysis experiment (CDA) follows the observed relationship more closely than that in the uncoupled reanalysis experiment (UCPL). However, the lead-lag correlations with the observed SST are almost identical between precipitations in CDA and UCPL, indicating that the atmospheric component is strongly constrained by atmospheric observations and hardly affected by the SSTs as boundary conditions. Better representation of the SST–precipitation relationship in CDA is, thus, mostly due to the SST variation modified by the model physics. Comparison with additional reanalysis experiments using coupled and uncoupled systems that assimilate only in-situ observations without satellite observations suggests that the coupled model's physics complements the relatively weak observation constraints and reduces the degradation of the SST–precipitation relationship. Additional analysis for CDA suggests that the warming-to-cooling (cooling-to-warming) transition of the surface net flux, which is in phase with precipitation, is delayed from the positive (negative) peak of SST due to downward heat propagation in the ocean. Comparison of the oceanic near-surface temperature field with observation data indicates that the downward propagation of heat signals is too fast in CDA, resulting in smaller lags of transitions of the net heat flux and precipitation behind SST peaks.

Levee Overtopping Risk Assessment under Climate Change Scenario in Kao-Ping River, Taiwan

With the growing concern about the failure risk of river embankments in a rapidly changing climate, this study aims to quantify the overtopping probability of river embankment in Kao-Ping River basin in southern Taiwan. A water level simulation model is calibrated and validated with historical typhoon events and the calibrated model is further used to assess overtopping risk in the future under a climate change scenario. A dynamic downscaled projection dataset, provided by Meteorological Research Institute (MRI) has been further downscaled to 5-km grids and bias-corrected with a quantile mapping method, is used to simulate the water level of Kao-Ping River in the future. Our results highlighted that the overtopping risk of Kao-Ping River increased by a factor of 5.7~8.0 by the end of the 21st century.

MODELING DISTRIBUTION OF SAURY CATCHES IN RELATION WITH ENVIRONMENTAL FACTORS

Pacific saury Cololabis saira is widely distributed in the North Pacific, with commercial harvesting in the area between 140–172о E. Relationship of its commercial catches distribution with environmental factors is investigated using the daily SST data, the daily data set of multivariate ocean variational estimation system (MOVE) produced by Meteorological Research Institute (Japan) for the area between 140–159о E (about 95 % of all catches and 100 % of the Russian catches of saury were landed in this area in 1994–2017), and the daily set of saury catches position with 1 km resolution collected by the Russian vessel monitoring system. Spatial resolution for all data sets is upscaled to the resolution of MOVE system (0.1 x 0.1 degree). Contribution and permutation importance for the catch distribution are estimated for 184 possible combinations of SST and MOVE products with the lags of 0–7 days and moving average window from 0 to 7 days using the method of maximum entropy (MaxEnt). For synchronic relationships, the best results are found for SST, water temperature at 50 m depth and its spatial gradient, moreover, SST provides high contribution with the lag up to 2 days and the temperature at 50 m and its gradient — with the lag 3–7 days. The same sets of environmental parameters are used for the catches distribution modeling with GAMs and Random Forest techniques; the latter method shows better accuracy and other indices of the confusion matrix. Year-to-year changes of the total area with predicted conditions favorable for the saury fishery within the EEZ of Russia and Japan correlate strongly (r = 0.96, p < 0.05) with the total annual catch of saury, in particular for the extreme years (high catches in 2008, 2014, and 2018, low catch in 2017).

Significant improvement of cloud representation in the global climate model MRI-ESM2

The development of the climate model MRI-ESM2 (Meteorological Research Institute Earth System Model version 2), which is planned for use in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) simulations, involved significant improvements to the representation of clouds from the previous version MRI-CGCM3 (Meteorological Research Institute Coupled Global Climate Model version 3), which was used in the CMIP5 simulations. In particular, the serious lack of reflection of solar radiation over the Southern Ocean in MRI-CGCM3 was drastically improved in MRI-ESM2. The score of the spatial pattern of radiative fluxes at the top of the atmosphere for MRI-ESM2 is better than for any CMIP5 model. In this paper, we set out comprehensively the various modifications related to clouds that contribute to the improved cloud representation and the main impacts on the climate of each modification. The modifications cover various schemes and processes including the cloud scheme, turbulence scheme, cloud microphysics processes, interaction between cloud and convection schemes, resolution issues, cloud radiation processes, interaction with the aerosol model, and numerics. In addition, the new stratocumulus parameterization, which contributes considerably to increased low-cloud cover and reduced radiation bias over the Southern Ocean, and the improved cloud ice fall scheme, which alleviates the time-step dependency of cloud ice content, are described in detail.

An inexpensive anemometer using Arduino board

In all studies involving wind speed, such as meteorology, wind turbines and agriculture accurate speed information for decision making is required. There are several types of anemometers, with medium and high costs, such as cup, hot wire and pitot tubes, the hot wire being more sensitive and expensive than others. The device developed in this work is the cup anemometer, that is easy to build. The great advantage of this device is the low cost, with an approximate value of US$ 50.00, using simple materials that are easy to find in commercial stores. The Reed Switch sensor is also another advantage as it does not require a sophisticated programming, as well as the open platform Arduino. The use of theoretical aerodynamic drag coefficients and the presented calculations resulted in values very close to a commercial anemometer. The coefficient of determination between the cup Anemometer and the standard sensor of Meteorological Research Institute IPMet/Brazil is R2=0.9999, indicating strong correlation between the instruments. As the reference anemometer (IPMet) has high embedded technology and the prototype is low cost, we conclude that the project has an attractive cost benefit for possible development and production, reaching the objective of this work.

JRAero: the Japanese Reanalysis for Aerosol v1.0

A global aerosol reanalysis product named the Japanese Reanalysis for Aerosol (JRAero) was constructed by the Meteorological Research Institute (MRI) of the Japan Meteorological Agency. The reanalysis employs a global aerosol transport model developed by MRI and a two-dimensional variational data assimilation method. It assimilates maps of aerosol optical depth (AOD) from MODIS onboard the Terra and Aqua satellites every 6 h and has a TL159 horizontal resolution (approximately 1.1° × 1.1°). This paper describes the aerosol transport model, the data assimilation system, the observation data, and the setup of the reanalysis and examines its quality with AOD observations. Comparisons with MODIS AODs that were used for the assimilation showed that the reanalysis showed much better agreement than the free run (without assimilation) of the aerosol model and improved under- and overestimation in the free run, thus confirming the accuracy of the data assimilation system. The reanalysis had a root mean square error (RMSE) of 0.05, a correlation coefficient (R) of 0.96, a mean fractional error (MFE) of 23.7 %, a mean fractional bias (MFB) of 2.8 %, and an index of agreement (IOA) of 0.98. The better agreement of the first guess, compared to the free run, indicates that aerosol fields obtained by the reanalysis can improve short-term forecasts. AOD fields from the reanalysis also agreed well with monthly averaged global AODs obtained by the Aerosol Robotic Network (AERONET) (RMSE = 0.08, R = 0. 90, MFE = 28.1 %, MFB = 0.6 %, and IOA = 0.93). Site-by-site comparison showed that the reanalysis was considerably better than the free run; RMSE was less than 0.10 at 86.4 % of the 181 AERONET sites, R was greater than 0.90 at 40.7 % of the sites, and IOA was greater than 0.90 at 43.4 % of the sites. However, the reanalysis tended to have a negative bias at urban sites (in particular, megacities in industrializing countries) and a positive bias at mountain sites, possibly because of insufficient anthropogenic emissions data, the coarse model resolution, and the difference in representativeness between satellite and ground-based observations.

Future Changes in the Ozone Quasi-Biennial Oscillation with Increasing GHGs and Ozone Recovery in CCMI Simulations

The future quasi-biennial oscillation (QBO) in ozone in the equatorial stratosphere is examined by analyzing transient climate simulations due to increasing greenhouse gases (GHGs) and decreasing ozone-depleting substances under the auspices of the Chemistry–Climate Model Initiative. The future (1960–2100) and historical (1979–2010) simulations are conducted with the Meteorological Research Institute Earth System Model. Three climate periods, 1960–85 (past), 1990–2020 (present), and 2040–70 (future) are selected, corresponding to the periods before, during, and after ozone depletion. The future ozone QBO is characterized by increases in amplitude by 15%–30% at 5–10 hPa and decreases by 20%–30% at 40 hPa, compared with the past and present climates; the future and present ozone QBOs increase in amplitude by up to 60% at 70 hPa, compared with the past climate. The increased amplitude at 5–10 hPa suggests that the temperature-dependent photochemistry plays an important role in the enhanced future ozone QBO. The weakening of vertical shear in the zonal wind QBO is responsible for the decreased amplitude at 40 hPa in the future ozone QBO. An interesting finding is that the weakened zonal wind QBO in the lowermost tropical stratosphere is accompanied by amplified QBOs in ozone, vertical velocity, and temperature. Further study is needed to elucidate the causality of amplification about the ozone and temperature QBOs under climate change in conditions of zonal wind QBO weakening.