Favorable versus unfavorable synoptic backgrounds for indirect precipitation events ahead of tropical cyclones approaching the Korean Peninsula: A comparison of two cases

This study identifies favorable synoptic backgrounds for indirect precipitation events over the Korean Peninsula that occur well in advance of tropical cyclone (TC) landfall. Two TCs, i.e., Rammasun (2002) and Maemi (2003) that made landfall and produced heavy rainfall over the Peninsula are compared. Although both had a remarkably similar accumulated rainfall pattern over the peninsula, the temporal evolutions of hourly rainfall were different. Only Maemi had an indirect precipitation event in conjunction with a midlatitude trough to its north. The confluent flows at middle-to-upper levels were strengthened due to the increased pressure gradient between the midlatitude trough and the subtropical high, and the warm advection by the confluent flows also became stronger near the confluent zone. By contrast, Rammasun encountered the subtropical ridge while moving northward, which results in slow recurvature and reduction of the thermal gradient over the peninsula. The highly baroclinic synoptic backgrounds in the Maemi case lead to the midlevel frontogenesis. Budget analyses using the three-dimensional frontogenesis equation revealed that the horizontal deformation forcing had a primary role in generating the front. The front was associated with a thermally direct circulation that contributed to strong ascent and indirect precipitation over the peninsula well in advance of the landfall of Maemi. Moreover, the indirect precipitation could intensify due to the abundant low-level moisture supply to the frontal zone by the southerly wind on the east side of the TC.     

A Landsat surface reflectance dataset for North America, 1990-2000

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center has processed and released 2100 Landsat Thematic Mapper and Enhanced Thematic Mapper Plus surface reflectance scenes, providing 30-m resolution wall-to-wall reflectance coverage for North America for epochs centered on 1990 and 2000. This dataset can support decadal assessments of environmental and land-cover change, production of reflectance-based biophysical products, and applications that merge reflectance data from multiple sensors [e.g., the Advanced Spaceborne Thermal Emission and Reflection Radiometer, Multiangle Imaging Spectroradiometer, Moderate Resolution Imaging Spectroradiometer (MODIS)]. The raw imagery was obtained from the orthorectified Landsat GeoCover dataset, purchased by NASA from the Earth Satellite Corporation. Through the LEDAPS project, these data were calibrated, converted to top-of-atmosphere reflectance, and then atmospherically corrected using the MODIS/6S methodology. Initial comparisons with ground-based optical thickness measurements and simultaneously acquired MODIS imagery indicate comparable uncertainty in Landsat surface reflectance compared to the standard MODIS reflectance product (the greater of 0.5% absolute reflectance or 5% of the recorded reflectance value). The rapid automated nature of the processing stream also paves the way for routine high-level products from future Landsat sensors.     

The impact of the diurnal cycle on the MJO over the Maritime Continent: a modeling study assimilating TRMM rain rate into global analysis

In the present study, we use modeling experiments to investigate the impact of the diurnal cycle on the Madden-Julian Oscillation (MJO) during the Australian summer. Physical initialization and a nudging technique enable us to assimilate the observed Tropical Rainfall Measuring Mission (TRMM) rain rate and atmospheric variables from the National Centers for Environmental Prediction—National Center for Atmospheric Research Reanalysis 2 (R2) into the Florida State University Global Spectral Model (FSUGSM), resulting in a realistic simulation of the MJO. Model precipitation is also significantly improved by TRMM rain rate observation via the physical initialization. We assess the influence of the diurnal cycle on the MJO by modifying the diurnal component during the model integration. Model variables are nudged toward the daily averaged values from R2. Globally suppressing the diurnal cycle (NO_DIURNAL) exerts a strong impact on the Maritime Continent. The mean state of precipitation increases and intraseasonal variability becomes stronger over the region. It is well known that MJO weakens as it passes over the Maritime Continent. However, the MJO maintains its strength in the NO_DIURNAL experiment, and the diminution of diurnal signals during the integration does not change the propagating speed of the MJO. We suggest that diminishing the diurnal cycle in NO_DIURNAL consumes less moist static energy (MSE), which is required to trigger both diurnal and intraseasonal convection. Thus, the remaining MSE may play a major role along with larger convective instability and stronger lower level moisture convergence in intensifying the MJO over the Maritime Continent in the model simulation.     

Spin-up behavior of soil moisture content over East Asia in a land surface model

This study presents an investigation of the spin-up behavior of soil moisture content (SMC) and evapotranspiration (ET) in an offline Noah land surface model (LSM) for East Asia, focusing on its interplay with the Asian monsoon. The set of 5-year recursive runs is conducted to properly assess the spin-up behavior of land surface processes and consists of simulations initialized with (1) a spatially uniform soil moisture, (2) NCEP GDAS soil moisture data, and (3) ECMWF ERA-Interim soil moisture data. Each run starts either after or before the summer monsoon. Initial SMCs from GDAS and ERA-Interim data significantly deviate from the equilibrium state (spin-up state) with the given input forcing even though the same equilibrium is reached within 3-year spin-up time, indicating that spin-up of land surface process is necessary. SMC reaches the equilibrium much quickly when (1) the consistent LSMs have been used in the prediction and analysis systems and (2) the spin-up simulation starts before the onset of heavy rainfall events during summer monsoon. For an area with heavy monsoon rainfall, the total column SMC and ET spin up quickly. The spin-up time over dry land is about 2–3?years, but for monsoon rainfall area decreases dramatically to about 3?months if the spin-up run starts just before the onset of monsoon. Further scrutiny shows that the spin-up time is well correlated with evaporative fraction given by the ratio between the latent heat flux and the available energy at the land surface.     

Holocene environmental changes on the east coast of Korea

We present a record of Holocene environmental change on the east coast of Korea, inferred using pollen, carbon-isotopic composition (??¹³C), total organic carbon, total sulfur, carbon/nitrogen ratios, particle size analysis and major element geochemistry in a sediment core from Soonpogae Lagoon. A multi-proxy paleoenvironmental approach had not previously been applied in Korea and allowed us to reconstruct climate and vegetation change, sea-level rise, lagoon development, and human impact on the east coast of Korea over the last 8,000?years. Evidence from Soonpogae Lagoon supports the following three conclusions: (1) As a drying trend prevailed on the east coast of Korea after ~5,900?cal?yr BP, chemical weathering weakened and herbaceous plants became more important than during the previous humid phase (Holocene Climate Optimum), (2) Sea-level rise on the east coast slowed dramatically about 6,800?cal?yr BP, resulting in low rates of sedimentation in Soonpogae Lagoon, and (3) Soonpogae Lagoon was almost completely isolated from the sea by sand barriers when human impact intensified ~2,100 BP.     

Downscaling large-scale NCEP CFS to resolve fine-scale seasonal precipitation and extremes for the crop growing seasons over the southeastern United States

Seasonally predicted precipitation at a resolution of 2.5° was statistically downscaled to a fine spatial scale of ~20 km over the southeastern United States. The downscaling was conducted for spring and summer, when the fine-scale prediction of precipitation is typically very challenging in this region. We obtained the global model precipitation for downscaling from the National Center for Environmental Prediction/Climate Forecast System (NCEP/CFS) retrospective forecasts. Ten member integration data with time-lagged initial conditions centered on mid- or late February each year were used for downscaling, covering the period from 1987 to 2005. The primary techniques involved in downscaling are Cyclostationary Empirical Orthogonal Function (CSEOF) analysis, multiple regression, and stochastic time series generation. Trained with observations and CFS data, CSEOF and multiple regression facilitated the identification of the statistical relationship between coarse-scale and fine-scale climate variability, leading to improved prediction of climate at a fine resolution. Downscaled precipitation produced seasonal and annual patterns that closely resemble the fine resolution observations. Prediction of long-term variation within two decades was improved by the downscaling in terms of variance, root mean square error, and correlation. Relative to the coarsely resolved unskillful CFS forecasts, the proposed downscaling drove a significant reduction in wet biases, and correlation increased by 0.1–0.5. Categorical predictability of seasonal precipitation and extremes (frequency of heavy rainfall days), measured with the Heidke skill score (HSS), was also improved by the downscaling. For instance, domain averaged HSS for two category predictability by the downscaling are at least 0.20, while the scores by the CFS are near zero and never exceed 0.1. On the other hand, prediction of the frequency of subseasonal dry spells showed limited improvement over half of the Georgia and Alabama region.     

Late Quaternary glaciation in the Nun‐Kun massif,northwestern India

The late Quaternary glacial history of the Nun‐Kun massif, located on the boundary between the Greater Himalaya and the Zanskar range in northwestern India, was reconstructed. On the basis of morphostratigraphy and ¹⁰Be dating of glacial landforms (moraines and glacial trimlines), five glacial stages were recognized and defined, namely: (i) the Achambur glacial stage dated to Marine Oxygen Isotope Stage 3 to 4 (38.7–62.7 ka); (ii) the Tongul glacial stage dated to the early part of the Lateglacial (16.7–17.4 ka); (iii) the Amantick glacial stage dated to the later part of the Lateglacial (14.3 ka, 11.7–12.4 ka); (iv) the Lomp glacial stage dated to the Little Ice Age; and (v) the Tanak glacial stage, which has the youngest moraines, probably dating to the last few decades or so. Present and former equilibrium‐line altitudes (ELAs) were calculated using the standard area accumulation ratio method. The average present‐day ELA of ～4790 m above sea level in the Greater Himalaya is lower than those in the Ladakh and Zanskar ranges, namely 5380 and ～5900 m a.s.l., respectively. The ELA in the Zanskar range is higher than in the Ladakh range, possibly due to the higher peaks in the Ladakh range that are able to more effectively capture and store snow and ice. ELA depressions decrease towards the Ladakh range (i.e. inner Plateau). Peat beds interbedded with aeolian deposits that cap the terminal moraine of Tarangoz Glacier suggest millennial‐time‐scale climate change throughout the Holocene, with soil formation times at c. 1.5, c. 3.4 and c. 5.2 ka, probably coinciding with Holocene abrupt climate change events. Given the style and timing of glaciation in the study area, it is likely that climate in the Nun‐Kun region is linked to Northern Hemisphere climate oscillations with teleconnections via the mid‐latitude westerlies.     

Impact of transient eddies on extratropical seasonal-mean predictability in DEMETER models

The impact of transient eddies on extratropical seasonal-mean prediction and predictability was examined using DEMETER seasonal prediction data. Two distinct groups were found among the seven DEMETER models based on the simulated properties of their climatological state: (1) models of a strong jet stream and strong transient activity (strong transient models), which is close to the observed intensity, and (2) models of a weak jet stream and weak transient activity (weak transient models). In addition to climatology, the strong transient models tend to predict strong Pacific North American (PNA) patterns, whereas the weak transient models predict weak PNA patterns. Here we demonstrate that these differences mainly result from differences in the eddy feedback intensity. Due to synoptic eddy feedback, the strong transient models exhibit not only strong signal variance but also strong noise variance compared with those of the weak transient models. Interestingly two groups of models show the potential predictability of deterministic forecast, measured by the signal to noise ratio, which is similar to each other. However, the strong transient models produce the error to spread ratio smaller than that of the weak transient models, implying that the former models produce a more reliable spread for the probabilistic forecast. This study implies that a better representation of transient statistics is needed to improve the extratropical predictability of the dynamical seasonal prediction.