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Xiaogang Ma
,
Kun Yang
,
Binbin Wang
,
Zhaoguo Li
,
Lazhu
,
Hui Lu
,
Xiangnan Yao
, and
Xin Chen

Abstract

Skin cooling, wherein the surface temperature of a water body T skin is lower than the temperature below the surface, is a widespread phenomenon. Previous studies have almost ignored this effect on the Tibetan Plateau (TP), despite the presence of thousands of lakes on the TP and the fact that extraordinary solar heating leads to very strong energy exchanges on the lake surfaces. This study utilizes in situ observations and MODIS-derived T skin data at Lake Nam Co, one of the largest lakes on the TP, to quantify the skin cooling effect. The observed nighttime skin cooling is approximately 0.52°C on average, with the maximum of about 1°C, during the lake water turnover period (from October to mid-November), which obviously surpasses reported values for oceans (less than 0.4°C). To understand the impact of the skin cooling on the lake thermal processes, a skin cooling parameterization is validated and incorporated into the WRF-lake model. Simulations with the updated model show that accounting for the skin cooling process systematically lowers sensible and latent heat fluxes by a few watts per square meter, which yields an increase in water temperature by 0.45°C at the end of December and may delay the onset of lake freeze. Finally, we show that the inclusion of the skin cooling process in a lake model needs simultaneous adjustment of the parameterization of heat/water vapor transfer.

Significance Statement

Skin cooling is a widespread phenomenon for a water surface, and its intensity depends on the energy flux exchange of the water surface. The Tibetan Plateau possesses the presence of thousands of lakes, but early studies have ignored the skin cooling effect. We found that the nighttime skin cooling magnitude during the lake water turnover period in this region obviously exceeds reported values for oceans, due to the strong surface energy exchange in the Tibetan Plateau. Neglecting the skin cooling process may lead to systematic overestimation of turbulent heat fluxes and underestimation of water temperature. We highlight that accounting for this skin cooling process is crucial to select appropriate parameterization schemes for heat/water vapor transfer in lake thermal process modeling.

Restricted access
Lu Yi
,
Chen Peiyan
,
Yu Hui
,
Fang Pingzhi
,
Gong Ting
,
Wang Xiaodong
, and
Song Shengnan

Abstract

Inland flooding and mudslides from tropical cyclone (TC) rainstorms are among the most destructive natural hazards in China, resulting in considerable direct economic losses and large numbers of fatalities. In this paper, a TC precipitation model (TCPM) is improved by incorporating the effects of complex terrain through a set of new parameters (e.g., slope, roughness, and attenuation distance) for a more accurate assessment of TC rainfall hazards in China. Moreover, by introducing parameterized spiral rainbands, the model could more accurately capture the intensity of extreme precipitation. The model comprehensively considers dynamic and thermodynamic precipitation factors and is adept at capturing the climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China. The model is verified by providing two comparisons. One is analysis including detailed results of three typical TC cases, and the other uses empirical cumulative distribution functions for extreme observations and simulations of historical landfalling TCs in China during the period 1960–2018. The comparisons reveal that the TCPM shows impressive performance for strong TCs with heavy precipitation within 200–300 km of the TC center. Moreover, both the modeled extreme hourly and total TC precipitation probability distributions are consistent with the observations. However, the model needs to be further improved for TCs with dispersive or long-distance precipitation.

Significance Statement

In this paper, an optimized and physics-based model for the simulation of tropical cyclone precipitation is described and used to estimate the risk of TC rainfall hazards in China. The work is innovative in that it considers the effect of complex terrain from three perspectives, including slope, roughness, and attenuation distance. The simulations demonstrated that the model is adept at capturing the main climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China, which is simple to run several hundred thousand times, with bright application prospects in catastrophe risk assessment.

Free access
Jing Sun
,
Kun Yang
,
Hui Lu
,
Xu Zhou
,
Xin Li
,
Yingying Chen
,
Weidong Guo
, and
Jonathon S. Wright

Abstract

Soil organic matter (SOM) is enriched on the eastern Tibetan Plateau, but its effects on the hydrothermal state of the coupled land–atmosphere system remain unclear. This study comprehensively investigates these effects during summer from multiple perspectives based on regional climate modeling, land surface modeling, and observations. Using a regional climate model, we show that accounting for SOM effects lowers cold and wet biases in simulations of this region. SOM increases 2-m air temperature, decreases 2-m specific/relative humidity, and reduces precipitation in coupled simulations. Inclusion of SOM also warms the shallow soil while cooling the deep soil, which may help to preserve frozen soil in this region. This cooling effect is captured by both observations and offline land surface simulations, but it is overestimated in the offline simulations due to no feedback from the atmosphere compared to the coupled ones. Including SOM in coupled climate models could therefore not only imrove their representations of atmospheric energy and water cycles, but also help to simulate the past, present, and future evolution of frozen soil with increased confidence and reliability. Note that these findings are from one regional climate model and do not apply to wetlands.

Significance Statement

The eastern Tibetan Plateau is rich in soil organic matter (SOM), which increases the amount of water the soil can hold while decreasing the rate at which heat moves through it. Although SOM is expected to preserve frozen soil by insulating it from atmospheric warming, researchers have not yet tested the effects of coupled land–atmosphere interactions on this relationship. Using a regional climate model, we show that SOM typically warms and dries the near-surface air, warms the shallow soil, and cools the deep soil by modifying both soil properties and energy exchanges at the land–atmosphere interface. The results suggest that the cooling effect of SOM on deep soil is overestimated when atmospheric feedbacks are excluded.

Free access
Pengfei Shi
,
Bin Wang
,
Yujun He
,
Hui Lu
,
Kun Yang
,
Shiming Xu
,
Wenyu Huang
,
Li Liu
,
Juanjuan Liu
,
Lijuan Li
, and
Yong Wang

Abstract

The land surface is a potential source of climate predictability over the Northern Hemisphere midlatitudes but has received less attention than sea surface temperature in this regard. This study quantified the degree to which realistic land initialization contributes to interannual climate predictability over Europe based on a coupled climate system model named FGOALS-g2. The potential predictability provided by the initialization, which incorporates the soil moisture and soil temperature of a land surface reanalysis product into the coupled model with a dimension-reduced projection four-dimensional variational data assimilation (DRP-4DVar)-based weakly coupled data assimilation (WCDA) system, was analyzed first. The effective predictability (i.e., prediction skill) of the hindcasts by FGOALS-g2 with realistic and well-balanced initial conditions from the initialization were then evaluated. Results show an enhanced interannual prediction skill for summer surface air temperature and precipitation in the hindcast over Europe, demonstrating the potential benefit from realistic land initialization. This study highlights the significant contributions of land surface to interannual predictability of summer climate over Europe.

Open access
Jeng-Lin Tsai
,
Ben-Jei Tsuang
,
Po-Sheng Lu
,
Ken-Hui Chang
,
Ming-Hwi Yao
, and
Yuan Shen

Abstract

The aerodynamic roughness, Bowen ratio, and friction velocity were measured over a rice paddy using tethersonde and eddy covariance (EC) systems. In addition, the height ranges of the atmospheric inertial sublayer (ISL) were derived using the tethersonde data. Comparison of the friction velocity, latent and sensible heat fluxes, and Bowen ratio estimated from these systems show their correlation coefficients to be >0.7. This difference between the observational systems can be associated with their respective footprint areas. The aerodynamic roughness was observed to be about 0.03 m for wind blowing from a paddy-dominated area (PDA) and about 0.37 m from a rice paddy interspersed with buildings (PIB) based on the ISL profile. Results are close to the effective roughness length model of Mason, having the same shear stresses at the blending height. In contrast, both the geometric mean model of Taylor and the arithmetic mean model of Tsai and Tsuang underestimate the effective roughness over the PIB. During daylight hours, the height range of the ISL ranged from a few meters to 25 m above ground level (AGL) for wind blowing from the PDA and 14–42 m for wind blowing from the PIB.

Full access
Yan Wang
,
Kun Yang
,
Zhengyang Pan
,
Jun Qin
,
Deliang Chen
,
Changgui Lin
,
Yingying Chen
,
Lazhu
,
Wenjun Tang
,
Menglei Han
,
Ning Lu
, and
Hui Wu

Abstract

The southern Tibetan Plateau (STP) is the region in which water vapor passes from South Asia into the Tibetan Plateau (TP). The accuracy of precipitable water vapor (PWV) modeling for this region depends strongly on the quality of the available estimates of water vapor advection and the parameterization of land evaporation models. While climate simulation is frequently improved by assimilating relevant satellite and reanalysis products, this requires an understanding of the accuracy of these products. In this study, PWV data from MODIS infrared and near-infrared measurements, AIRS Level-2 and Level-3, MERRA, ERA-Interim, JRA-55, and NCEP final reanalysis (NCEP-Final) are evaluated against ground-based GPS measurements at nine stations over the STP, which covers the summer monsoon season from 2007 to 2013. The MODIS infrared product is shown to underestimate water vapor levels by more than 20% (1.84 mm), while the MODIS near-infrared product overestimates them by over 40% (3.52 mm). The AIRS PWV product appears to be most useful for constructing high-resolution and high-quality PWV datasets over the TP; particularly the AIRS Level-2 product has a relatively low bias (0.48 mm) and RMSE (1.83 mm) and correlates strongly with the GPS measurements (R = 0.90). The four reanalysis datasets exhibit similar performance in terms of their correlation coefficients (R = 0.87–0.90), bias (0.72–1.49 mm), and RMSE (2.19–2.35 mm). The key finding is that all the reanalyses have positive biases along the PWV seasonal cycle, which is linked to the well-known wet bias over the TP of current climate models.

Full access
Tiangang Yuan
,
Siyu Chen
,
Jianping Huang
,
Dongyou Wu
,
Hui Lu
,
Guolong Zhang
,
Xiaojun Ma
,
Ziqi Chen
,
Yuan Luo
, and
Xiaohui Ma

Abstract

The Weather Research and Forecasting Model coupled with chemistry (WRF-Chem) associated with in situ measurements and satellite retrievals was used to investigate the meridional transport of Taklimakan Desert (TD) dust, especially in summer. Both satellite observations and simulations reveal that TD dust particles accumulate over the Tibetan Plateau (TP) and the Tianshan Mountains in summer, resulting in higher dust concentration up to 85 μg m−3 here. The proportions of meridional transport of TD dust in summer increase up to 30% of the total output dust over the TD. Further, the impacts of thermal and dynamic forcing on the meridional transport of TD dust to the TP and Tianshan Mountains are investigated based on composite analysis and numerical modeling. It is found that the weakness of the westerly jet over East Asia significantly decreases the eastward transport of TD dust. More TD dust particles lifted to higher altitude reach up to 8 km induced by the enhanced sensible heating in summer. Under the influence of the northerly airflow over the TD regions, the TD dust particles are strengthened southward and transported to the northern slope of the TP through topographic forcing. Moreover, the cyclonic circulation raises dust particles to higher altitude over the TP. It can further intensify the TP heat source by direct radiative forcing of dust aerosols, which may have a positive feedback to the southward transport of TD dust. This research provides confidence for the investigation of the role of TP dust with regard to the radiation balance and hydrological cycle over East Asia.

Open access
Yuan Yang
,
Ming Pan
,
Peirong Lin
,
Hylke E. Beck
,
Zhenzhong Zeng
,
Dai Yamazaki
,
Cédric H. David
,
Hui Lu
,
Kun Yang
,
Yang Hong
, and
Eric F. Wood

Abstract

Better understanding and quantification of river floods for very local and “flashy” events calls for modeling capability at fine spatial and temporal scales. However, long-term discharge records with a global coverage suitable for extreme events analysis are still lacking. Here, grounded on recent breakthroughs in global runoff hydrology, river modeling, high-resolution hydrography, and climate reanalysis, we developed a 3-hourly river discharge record globally for 2.94 million river reaches during the 40-yr period of 1980–2019. The underlying modeling chain consists of the VIC land surface model (0.05°, 3-hourly) that is well calibrated and bias corrected and the RAPID routing model (2.94 million river and catchment vectors), with precipitation input from MSWEP and other meteorological fields downscaled from ERA5. Flood events (above 2-yr return) and their characteristics (number, spatial distribution, and seasonality) were extracted and studied. Validations against 3-hourly flow records from 6,000+ gauges in CONUS and daily records from 14,000+ gauges globally show good modeling performance across all flow ranges, good skills in reconstructing flood events (high extremes), and the benefit of (and need for) subdaily modeling. This data record, referred as Global Reach-Level Flood Reanalysis (GRFR), is publicly available at https://www.reachhydro.org/home/records/grfr.

Full access
Yujun He
,
Bin Wang
,
Juanjuan Liu
,
Yong Wang
,
Lijuan Li
,
Li Liu
,
Shiming Xu
,
Wenyu Huang
, and
Hui Lu

Abstract

Accurately predicting the decadal variations in Sahel rainfall has important implications for the lives and economy in the Sahel. Previous studies found that the decadal variations in sea surface temperature (SST) in the Atlantic, Mediterranean Sea, Indian Ocean, and Pacific contribute to those in Sahel rainfall. This study evaluates the decadal prediction skills of Sahel rainfall from all the available hindcasts contributing to phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6), in comparison with the related uninitialized simulations. A majority of the prediction systems show high skill with regard to Sahel rainfall. The high skill may be partly attributed to external forcings, which are reflected in good performance of the respective uninitialized simulations. The decadal prediction skills of the key SST drivers and their relationships with the Sahel rainfall are also assessed. Both the hindcasts and the uninitialized simulations generally present high skill for the Atlantic multidecadal variability (AMV) and Mediterranean Sea SST indices and low skill for the Indian Ocean basin mode (IOBM) and interdecadal Pacific variability (IPV) indices. The relationship between the Sahel rainfall and the AMV or Mediterranean Sea SST index is reasonably captured by most prediction systems and their uninitialized simulations, while that between the Sahel rainfall and the IOBM or IPV index is captured by only a few systems and their uninitialized simulations. The high skill of the AMV and Mediterranean Sea SST indices as well as the reasonable representations of their relationships with the Sahel rainfall by both the hindcasts and uninitialized simulations probably plays an important role in predicting the Sahel rainfall successfully.

Significance Statement

Predicting Sahel rainfall on the decadal time scale is of great importance. This study provides a thorough evaluation of the decadal prediction skills of Sahel rainfall in the current decadal prediction systems participating in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). A majority of the systems achieve high prediction skill of Sahel rainfall, which probably results from the high prediction skill of some key sea surface temperature (SST) drivers, especially in the Atlantic and Mediterranean Sea SST, and their relationships with Sahel rainfall. This study provides a reference for better understanding the predictability of Sahel rainfall.

Restricted access
Wenli Wang
,
Kun Yang
,
Long Zhao
,
Ziyan Zheng
,
Hui Lu
,
Ali Mamtimin
,
Baohong Ding
,
Xin Li
,
Lin Zhao
,
Hongyi Li
,
Tao Che
, and
John C. Moore

Abstract

Snow depth on the interior of Tibetan Plateau (TP) in state-of-the-art reanalysis products is almost an order of magnitude higher than observed. This huge bias stems primarily from excessive snowfall, but inappropriate process representation of shallow snow also causes excessive snow depth and snow cover. This study investigated the issue with respect to the parameterization of fresh snow albedo. The characteristics of TP snowfall were investigated using ground truth data. Snow in the interior of the TP is usually only some centimeters in depth. The albedo of fresh snow depends on snow depth, and is frequently less than 0.4. Such low albedo values contrast with the high values (~0.8) used in the existing snow schemes of land surface models. The SNICAR radiative transfer model can reproduce the observations that fresh shallow snow has a low albedo value, based on which a fresh snow albedo scheme was derived in this study. Finally, the impact of the fresh snow albedo on snow ablation was examined at 45 meteorological stations on TP using the land surface model Noah-MP which incorporated the new scheme. Allowing albedo to change with snow depth can produce quite realistic snow depths compared with observations. In contrast, the typically assumed fresh snow albedo of 0.82 leads to too large snow depths in the snow ablation period averaged across 45 stations. The shallow snow transparency impact on snow ablation is therefore particularly important in the TP interior, where snow is rather thin and radiation is strong.

Free access