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Steven Marcus, Jinwon Kim, Toshio Chin, David Danielson, and Jayme Laber

Abstract

The effects of precipitable water vapor (PWV) retrievals from the Southern California Integrated GPS Network (SCIGN) on quantitative precipitation forecast (QPF) skill are examined over two flood-prone regions of Southern California: Santa Barbara (SB) and Ventura County (VC). Two sets of QPFs are made, one using the initial water vapor field from the NCEP 40-km Eta initial analysis, and another in which the initial Eta water vapor field is modified by incorporating the PWV data from the SCIGN receivers. Lateral boundary data for the QPFs, as well as the hydrostatic component of the GPS zenith delay data, are estimated from the Eta analysis. Case studies of a winter storm on 2 February during the 1997/98 El Niño, and storms leading up to the La Conchita, California, landslide on 10 January 2005, show notably improved QPFs for the first 3–6 h with the addition of GPS PWV data. For a total of 47 winter storm forecasts between February 1998 and January 2005 the average absolute QPF improvement is small; however, QPF improvements exceed 5 mm in several underpredicted rainfall events, with GPS data also improving most cases with overpredicted rainfall. The GPS improvements are most significant (above or near the 2σ level) when the low-level winds off the coast of Southern California are from the southern (SW to SE) quadrant. To extend the useful forecast skill enhancement beyond six hours, however, additional sources of water vapor data over broader areas of the adjacent Pacific Ocean are needed.

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Jinwon Kim, Tae-Kook Kim, Raymond W. Arritt, and Norman L. Miller

Abstract

Regional-scale projections of climate change signals due to increases in atmospheric CO2 are generated for the western United States using a regional climate model (RCM) nested within two global scenarios from a GCM. The downscaled control climate improved the local accuracy of the GCM results substantially. The downscaled control climate is reasonably close to the results of an 8-yr regional climate hindcast using the same RCM nested within the NCEP–NCAR reanalysis, despite wet biases in high-elevation regions along the Pacific coast.

The downscaled near-surface temperature signal ranges from 3 to 5 K in the western United States. The projected warming signals generally increase with increasing elevation, consistent with earlier studies for the Swiss Alps and the northwestern United States. In addition to the snow–albedo feedback, seasonal variations of the low-level flow and soil moisture appear to play important roles in the spatial pattern of warming signals. Projected changes in precipitation characteristics are mainly associated with increased moisture fluxes from the Pacific Ocean and the increase in elevation of freezing levels during the cold season. Projected cold season precipitation increases substantially in mountainous areas along the Pacific Ocean. Most of the projected precipitation increase over the Sierra Nevada and the Cascades is in rainfall, while snowfall generally decreases except above 2500 m. Projected changes in summer rainfall are small. The snow budget signals are characterized by decreased (increased) cold season snowfall (snowmelt) and reduced snowmelt during spring and summer. The projected cold season runoff from high-elevation regions increases substantially in response to increased cold season rainfall and snowmelt, while the spring runoff decreases due to an earlier depletion of snow, except above 2500 m.

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Woosuk Choi, Chang-Hoi Ho, Jinwon Kim, Hyeong-Seog Kim, Song Feng, and KiRyong Kang

Abstract

A seasonal prediction model of tropical cyclone (TC) activities for the period August–October over the North Atlantic (NA) has been developed on the basis of TC track patterns. Using the fuzzy c-means method, a total of 432 TCs in the period 1965–2012 are categorized into the following four groups: 1) TCs off the U.S. East Coast, 2) TCs over the Gulf of Mexico, 3) TCs that recurve into the open ocean of the central NA, and 4) TCs that move westward in the southern NA. The model is applied to predict the four TC groups separately in conjunction with global climate forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2). By adding the distributions of the four TC tracks with precalculated weighting factors, this seasonal TC forecast model provides the spatial distribution of TC activities over the entire NA basin. Multiple forecasts initialized in six consecutive months from February to July are generated at monthly intervals to examine the applicability of this model in operational TC forecasting. Cross validations of individual forecasts show that the model can reasonably predict the observed TC frequencies over NA at the 99% confidence level. The model shows a stable spatial prediction skill, proving its advantage for forecasting regional TC activities several months in advance. In particular, the model can generate reliable information on regional TC counts in the near-coastal regions as well as in the entire NA basin.

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Chang-Kyun Park, Doo-Sun R. Park, Chang-Hoi Ho, Tae-Won Park, Jinwon Kim, Sujong Jeong, and Baek-Min Kim

Abstract

Because spring precipitation in East Asia is critical for recharging water resources after dry winters, its spatiotemporal variations and related mechanisms need in-depth research. This study analyzed a leading spatiotemporal variability of precipitation over East Asia for boreal spring (March–May) during 1979 to 2017. We found that a dipole mode dominates the anomalous spring precipitation between southern China and Southeast Asia with significant interannual and decadal variations. The interannual dipole mode is attributable to the eastern Pacific (EP)-type El Niño–Southern Oscillation (ENSO) while the decadal dipole mode is related to the decadal variation of the central Pacific (CP)-type ENSO. In the El Niño phases of both time scales, the anticyclonic anomaly over the South China Sea and Philippines causes moisture convergence (divergence) over southern China (Southeast Asia), resulting in positive (negative) precipitation anomalies therein; the opposite occurs in the La Niña phases. The ensemble experiments using the Community Atmosphere Model version 5.1 confirmed that the tropical sea surface temperature (SST) in the EP- and CP-type ENSO can be the major drivers of the interannual and decadal dipole modes, respectively. About half of 15 climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) showed that the El Niño phase of dipole mode will become dominant in the future. The individual models’ future projections however considerably vary, implying that there is still large uncertainty.

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Jinwon Kim, Norman L. Miller, Alexander K. Guetter, and Konstantine P. Georgakakos

Abstract

A numerical study of precipitation and river flow from November 1994 to May 1995 at two California basins is presented. The Hopland watershed of the Russian River in the northern California Coastal Range and the headwater of the North Fork American River in the northern Sierra Nevada were selected to investigate the hydroclimate, snow budget, and streamflow at different elevations. Simulated precipitation and streamflow at the Hopland basin closely approximated observed values. An intercomparison between the semidistributed TOPMODEL and two versions of the lumped Sacramento model for the severe storm event of January 1995 indicates that both types of models predicted a similar response of river outflows from this basin, with the exception that TOPMODEL predicted a faster recession of river flow with less base flow after precipitation ended. Precipitation in this low-elevation watershed was predominantly in the form of rain, causing a fast streamflow response. The high-elevation Sierra Nevada watershed received most of its precipitation as snowfall. As a result, the frozen water held in surface storage delayed runoff and streamflow. Application of a simple elevation-dependent snowfall and rainfall partitioning scheme showed the significance of finescale terrain variation in the surface hydrology at high-elevation watersheds.

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Yong-Sang Choi, Chang-Hoi Ho, Jinwon Kim, Dao-Yi Gong, and Rokjin J. Park

Abstract

The authors investigate the short-term relationship between aerosol concentrations and summer rainfall frequency in China using the daily surface observations of particulate matters with a diameter of less than 10 μm (PM10) mass concentration, rainfall, and satellite-observed cloud properties. Results in this study reveal that on the time scale of a few days aerosol concentration is positively correlated with the frequency of moderate-rainfall (10–20 mm day−1) days but is negatively correlated with the frequency of light-rainfall (<5 mm day−1) days. Satellite observations of cloud properties show that higher aerosol concentrations are positively correlated with the increase in mixed cloud amount, cloud effective radius, cloud optical depth, and cloud-top heights; this corresponds to the decrease in low-level liquid clouds and the increase in midlevel ice–mixed clouds. Based on this analysis, the authors hypothesize that the increase in aerosol concentration results in the increase in summer rainfall frequency in China via enhanced ice nucleation in the midtroposphere. However, over the past few decades, observations show an increasing long-term trend in aerosol concentration but decreasing trends in summer rainfall frequency and relative humidity (RH) in China. Despite the short-term positive relationship between summer rainfall frequency and aerosol concentration found in this study, the long-term variations in summer rainfall frequency in China are mainly determined by other factors including RH variation possibly caused by global and regional climate changes. A continuous decrease in RH resulting in less summer rainfall frequency may further enhance aerosol concentrations in the future in conjunction with the increase in the anthropogenic emissions.

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Woosuk Choi, Chang-Hoi Ho, Doo-Sun R. Park, Jinwon Kim, and Johnny C. L. Chan

Abstract

Prediction of tropical cyclone (TC) activity is essential to better prepare for and mitigate TC-induced disasters. Although many studies have attempted to predict TC activity on various time scales, very few have focused on near-future predictions. Here a decrease in seasonal TC activity over the North Atlantic (NA) for 2016–30 is shown using a track-pattern-based TC prediction model. The TC model is forced by long-term coupled simulations initialized using reanalysis data. Unfavorable conditions for TC development including strengthened vertical wind shear, enhanced low-level anticyclonic flow, and cooled sea surface temperature (SST) over the tropical NA are found in the simulations. Most of the environmental changes are attributable to cooling of the NA basinwide SST (NASST) and more frequent El Niño episodes in the near future. The consistent NASST warming trend in the projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) suggests that natural variability is more dominant than anthropogenic forcing over the NA in the near-future period.

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Jinwon Kim, Norman L. Miller, John D. Farrara, and Song-You Hong

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The authors present a seasonal hindcast and prediction of precipitation in the western United States and stream flow in a northern California coastal basin for December 1997–February 1998 (DJF) using the Regional Climate System Model (RCSM). In the seasonal hindcast simulation, in which the twice-daily National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis was used for the initial conditions and time-dependent boundary forcing, RCSM has simulated realistically the temporal and spatial variations of precipitation in California and stream flow in a northern California coastal basin. For the headwater basin of the Russian River in the northern California Coast Ranges, the Topography-Based Hydrologic Model (TOPMODEL) forced by observed daily precipitation resulted in a correlation coefficient of 0.88 between observed and simulated DJF stream flow. In the coupled stream flow hindcast, the authors obtained a correlation coefficient of 0.7 between simulated and observed stream flow for the same period. The coupled hindcast has generally overestimated (underestimated) low (high) flow events in the basin. Errors in the simulated stream flow were due mostly to the errors in the simulated precipitation. A seasonal hydroclimate prediction experiment, in which RCSM was nested within the global forecast data from the University of California, Los Angeles, GCM, has predicted well the season-total precipitation in the western United States. Temporal variations of predicted precipitation were affected strongly by the predictability of the general circulation model. The predicted DJF-total snowfall agrees well with the snowfall simulated in the hindcast, especially in the central Cascades and the Sierra Nevada, where snowfall was the heaviest.

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Seungkyu K. Hong, Sang-Boom Ryoo, Jinwon Kim, and Sang-Sam Lee

Abstract

This study evaluates the Korea Meteorological Administration (KMA) Asian Dust Aerosol Model 2 (ADAM2) for Asian dust events over the dust source regions in northern China during the first half of 2017. Using the observed hourly particulate matter (PM) concentration from the China Ministry of Environmental Protection (MEP) and station weather reports, we find that a threshold value of PM10–PM2.5 = 400 μg m−3 works well in defining an Asian dust event for both the MEP-observed and the ADAM2-simulated data. In northwestern China, ADAM2 underestimates the observed dust days mainly due to underestimation of dust emissions; ADAM2 overestimates the observed Asian dust days over Manchuria due to overestimation of dust emissions. Performance of ADAM2 in estimating Asian dust emissions varies quite systematically according to dominant soil types within each region. The current formulation works well for the Gobi and sand soil types, but substantially overestimates dust emissions for the loess-type soils. This suggests that the ADAM2 model errors are likely to originate from the soil-type-dependent dust emissions formulation and that the formulation for the mixed and loess-type soils needs to be recalibrated. In addition, inability to account for the concentration of fine PMs from anthropogenic sources results in large false-alarm rates over heavily industrialized regions. Direct calculation of PM2.5 in the upcoming ADAM3 model is expected to alleviate the problems related to anthropogenic PMs in identifying Asian dust events.

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Chang-Eui Park, Su-Jong Jeong, Chang-Hoi Ho, and Jinwon Kim

Abstract

This study examines the impacts of global warming on the timing of plant habitat changes in the twenty-first century using climate scenarios from multiple global climate models (GCMs). The plant habitat changes are predicted by driving the bioclimate rule in a dynamic global vegetation model using the climate projections from 16 coupled GCMs. The timing of plant habitat changes is estimated by the first occurrence of specified fractional changes (10%, 20%, and 30%). All future projections are categorized into three groups by the magnitude of the projected global-mean land surface temperature changes: low (<2.5 K), medium (2.5–3.5 K), and high (>3.5 K) warming. During the course of the twenty-first century, dominant plant habitat changes are projected in ecologically transitional (i.e., from tropical to temperate and temperate to boreal) regions. The timing of plant habitat changes varies substantially according to regions. In the low-warming group, habitat changes of 10% in southern Africa occur in 2028, earlier than in the Americas by more than 70 yr. Differences in the timing between regions increase with the increase in warming and fractional threshold. In the subtropics, fast plant habitat changes are projected for the Asia and Africa regions, where countries of relatively small gross domestic product (GDP) per capita are concentrated. Ecosystems in these regions will be more vulnerable to global warming, because countries of low economic power lack the capability to deal with the warming-induced habitat changes. Thus, it is important to establish international collaboration via which developed countries provide assistance to mitigate the impacts of global warming.

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