Abstract

Whether precipitation falls in the form of rain or snow is of great importance to glacier accumulation and ablation. Assessments of phase-aware precipitation have been lacking over the vast area of the Tibetan Plateau (TP) due to the scarcity of surface measurements and the low quality of satellite estimates in this region. In this study, we attempt a satellite radar-based method for this precipitation partition, in which the CloudSat radar is used for snowfall while the Global Precipitation Measurement Mission radar is used for rainfall estimation. Assuming that 11-yr snowfall and 5-yr rainfall estimates represent the mean states of precipitation at each phase, the phase partition characteristics, including its annual mean, spatial pattern, seasonal dependence, and variation with elevations, are then discussed. Averaged over the highland area (over 1 km above mean sea level) in TP, the annual total precipitation is estimated to be around 400 mm, of which about 40% falls as snow. The snowfall mass fraction is about 45% in the northern and 30% in the southern part of TP, and about 80% in the cold and 30% in the warm half of the year. Surface elevation is found to be a high-impact factor on total precipitation and its phase partition, generally with total precipitation decreasing but snowfall fraction increasing with the increase of elevation. While there are some shortcomings, the current approach in combining snowfall and rainfall estimates from two satellite radars presents a useful pathway to assessing phase-aware precipitation over the TP region.

Abstract

An atmospheric general circulation model (AGCM) is used to examine the role of Indian Ocean sea surface temperature (SST) anomalies in regional climate variability. In particular, the authors focus on the effect of the basinwide warming that occurs during December through May after the mature phase of El Niño. To elucidate the relative importance of local and remote forcing, model solutions were sought for experiments where SST anomalies are inserted in the (i) tropical Indo-Pacific Oceans, (ii) tropical Pacific Ocean, and (iii) tropical Indian Ocean. A 10-member ensemble simulation is carried out for each of the three forcing scenarios.

The model solutions demonstrate that precipitation variations over the southwest Indian Ocean are tied to local SST anomalies and are highly reproducible. Changes in the Indian Ocean–Walker circulation suppress precipitation over the tropical west Pacific–Maritime Continent, contributing to the development of a low-level anticyclone over the Philippine and South China Seas. Our model results indicate that more than 50% of the total precipitation anomalies over the tropical west Pacific–Maritime Continent is forced by remote Indian Ocean SST anomalies, offering an additional mechanism for the Philippine Sea anticyclone apart from Pacific SST. This anticyclone increases precipitation along the East Asian winter monsoon front from December to May. The anomalous subsidence over the Maritime Continent in conjunction with persistent anomalies of SST and precipitation over the Indian Ocean in spring prevent the northwestward migration of the ITCZ and the associated deep moist layer, causing a significant delay in the Indian summer monsoon onset in June by 6–7 days. At time scales of 5 days, however, the reproducibility of the northward progression of the ITCZ during the onset is low.

Results indicate that Indian Ocean SST anomalies during December through May that develop in response to both atmospheric and oceanic processes to El Niño need to be considered for a complete understanding of regional climate variability, particularly around the Indian Ocean rim.

Abstract

An hourly dataset of automatic weather stations over Beijing Municipality in China is developed and is employed to analyze the spatial and temporal characteristics of urban heat island intensity (UHII) over the built-up areas. A total of 56 stations that are located in the built-up areas [inside the 6th Ring Road (RR)] are considered to be urban sites, and 8 stations in the suburban belts surrounding the built-up areas are taken as reference sites. The reference stations are selected by using a remote sensing method. The urban sites are further divided into three areas on the basis of the city RRs. It is found that the largest UHII generally takes place inside the 4th RR and that the smallest ones occur in the outer belts of the built-up areas, between the 5th RR and the 6th RR, with the areas near the northern and southern 6th RR experiencing the weakest UHI phenomena. On a seasonal basis, the strongest UHII generally occurs in winter and weak UHII is dominantly observed in summer and spring. The UHII diurnal variations for each of the urban areas are characterized by a steadily strong UHII stage from 2100 local solar time (LST) to 0600 LST and a steadily weak UHII stage from 1100 to 1600 LST, with the periods 0600–1100 LST and 1600–2100 LST experiencing a swift decline and rise, respectively. UHII diurnal variation is seen throughout the year, but the steadily strong UHII stage at night is longer (shorter) and the steadily weak UHII stage during the day is shorter (longer) during winter and autumn (summer and spring).

Abstract

A fast and flexible model is developed to simulate the transfer of thermal infrared radiation at wavenumbers from 700 to 1300 cm⁻¹ with a spectral resolution of 0.1 cm⁻¹ for scattering–absorbing atmospheres. In a single run and at multiple user-defined levels, the present model simulates radiances at different viewing angles and fluxes. Furthermore, the model takes into account complicated and realistic scenes in which ice cloud, water cloud, and mineral dust layers may coexist within an atmospheric column. The present model is compared to a rigorous reference model, the 32-stream Discrete Ordinate Radiative Transfer model (DISORT) code. For an atmosphere with three scattering layers (water, ice, and mineral dust), the root-mean-square error of the simulated brightness temperatures at the top of the atmosphere is approximately 0.05 K, and the relative flux errors at the boundary and internal levels are much smaller than 1%. Within the same computing environment, the fast model runs more than 10 000, 6000, and 4000 times faster than DISORT under single-layer, two-layer, and three-layer cloud–aerosol conditions, respectively. With its computational efficiency and accuracy, the present model may optimally facilitate the forward radiative transfer simulations involved in remote sensing implementations based on high-spectral-resolution and narrowband infrared measurements and in the data assimilation applications of the weather forecasting system. The selected 0.1-cm⁻¹ spectral resolution is an obstacle to extending the present model to strongly absorptive bands (e.g., 600–700 cm⁻¹). However, the present clear-sky module can be substituted by a more accurate model for specific applications involving spectral bands with strong absorption.

Abstract

Using station observations of the number of days covered by snow (SCD) and snowfall over the Tibetan Plateau (TP), the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis, and precipitation from rain gauge stations in China for the period of 1973–2001, temporal/spatial variations of SCD over the TP and its associations with the hemispheric extratropical atmospheric circulation and East Asian summer monsoon rainfall are investigated.

An increase of spring (April–May) SCD over the TP is associated with decreases of local tropospheric temperature and geopotential height in the spring and early summer (June). The anomalies in the tropospheric temperature and geopotential height show a westward propagation from the TP to western Asia as a result of the westward propagation of the anomalous wave energy. These tropospheric anomalies over the TP are connected with changes in the hemispheric extratropical atmospheric circulation along the westerly jet stream that acts as a waveguide.

The increase of the spring SCD is also associated with the variation of the East Asian summer monsoon rainfall. Soil moisture in May–June might act as a bridge linking the spring snow anomaly and the subsequent summer monsoon. Corresponding to the increase of SCD, there is a significant decrease of the June 500-mb geopotential height from the TP to the western North Pacific. Meanwhile, the anomalous northeasterlies extend from Japan, through the east coast of China, to central-eastern China, which weaken the East Asian summer monsoon, leading to a decrease of surface air temperature and rainfall in the Yangtze and Hwai Rivers and an increase of rainfall in southeastern China.

Additionally, the spring SCD anomaly is likely due to a variation of local synchronous snowfall, rather than previous winter SCD conditions. The spring SCD is not related to previous winter El Niño/La Niña events, but is associated with the equatorial central and eastern Pacific sea surface temperature from the subsequent summer through winter. The climatic implications for this relationship are not clear.

Statistical prediction of tropical sea surface temperatures (SSTs) is performed using linear inverse models (LIMs) that are constructed from both observations and general circulation model (GCM) output of SST. The goals are to establish a baseline for tropical SST predictions, to examine the extent to which the skill of a GCM-derived LIM is indicative of that GCM’s skill in forecast mode, and to examine the linkages between mean state bias and prediction skill. The observation-derived LIM is more skillful than a simple persistence forecasts in most regions. Its skill also compares well with some GCM forecasts except in the equatorial Pacific, where the GCMs are superior. The observation-derived LIM is matched or even outperformed by the GCM-derived LIMs, which may be related to the longer data record available for GCMs. The GCM-derived LIMs provide a fairly good measure for the skill achieved by their parent GCMs in forecast mode. In some cases, the skill of the LIM is actually superior to that of its parent GCM, indicating that the GCM predictions may suffer from initialization problems. A weak-to-moderate relation exists between model mean state error and prediction skill in some regions. An example is the eastern equatorial Atlantic, where an erroneously deep thermocline reduces SST variability, which in turn affects prediction skill. Another example is the equatorial Pacific, where skill appears to be linked to cold SST biases in the western tropical Pacific, which may reduce the strength of air–sea coupling.

Abstract

The summer (June–August) Asian–Pacific Oscillation (APO), a large-scale atmospheric teleconnection pattern, is closely associated with climate anomalies over the Northern Hemisphere. Using the NOAA/CIRES twentieth-century reanalysis, the ECMWF twentieth-century atmospheric reanalysis, and the NCEP reanalysis, this study investigates the variability of the summer APO on the interannual time scale and its relationship with the thermal condition over the Tibetan Plateau (TP). The results show that the interannual variability of the APO is steadily related to the summer TP surface air temperature during the last 100 years. Observation and simulation further show that a positive heating anomaly over the TP can increase the upper-tropospheric temperature and upward motion over Asia. This anomalous upward flow moves northward in the upper troposphere, and then turns and moves eastward, before finally descending over the mid- to high latitudes of the central-eastern North Pacific, concurrently accompanied by anomalous upward motion over the lower latitudes of the central-eastern North Pacific. The anomalous downward and upward motions over the central-eastern North Pacific reduce the in situ mid- and upper-tropospheric temperature, mainly through modulating condensation latent heat from precipitation and/or dry adiabatic heat, which ultimately leads to the interannual variability of the summer APO. In this process, the zonal vertical circulation over the extratropical Asian–North Pacific sector plays an important bridging role.

Abstract

It is essential to explore reliable streamflow forecasting techniques for water resources management. In this study, a Bayesian wavelet–support vector regression model (BWS model) is developed for one- and multistep-ahead streamflow forecasting using local meteohydrological observations and climate indices including El Niño–Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) as potential predictors. To accomplish this, a two-step strategy is applied. In the first step, the discrete wavelet transform is coupled with a support vector regression model for streamflow prediction. The three key factors of mother wavelets, decomposition levels, and edge effects are considered in the wavelet decomposition phase when using the hybrid wavelet–support vector regression model (WS model). Different combinations of these factors form a variety of WS models with corresponding forecasts. The second step combines multiple candidate WS models with “good” performance via Bayesian model averaging. This integrates the predictive strengths of different candidate WS models, giving a realistic assessment of the predictive uncertainty. The new ensemble model is used to forecast daily and monthly streamflows at two sites in Dongjiang basin, southern China. The results show that the proposed BWS model consistently generates more reliable predictions for daily (lead times of 1–7 days) and monthly (lead times of 1–3 months) forecasts as compared with the best single-member WS models and the adaptive neuro-fuzzy inference system (ANFIS). Furthermore, the proposed BWS model provides detailed information about the predictive uncertainty.

Abstract

Effects of the sea surface temperature (SST) front along the East China Sea Kuroshio on sea surface winds at different time scales are investigated. In winter and spring, the climatological vector wind is strongest on the SST front while the scalar wind speed reaches a maximum on the warm flank of the front and is collocated with the maximum difference between sea surface temperature and surface air temperature (SST − SAT). The distinction is due to the change in relative importance of two physical processes of SST–wind interaction at different time scales. The SST front–induced sea surface level pressure (SLP) adjustment (SF–SLP) contributes to a strong vector wind above the front on long time scales, consistent with the collocation of baroclinicity in the marine boundary layer and corroborated by the similarity between the thermal wind and observed wind shear between 1000 and 850 hPa. In contrast, the SST modulation of synoptic winds is more evident on the warm flank of the SST front. Large thermal instability of the near-surface layer strengthens temporal synoptic wind perturbations by intensifying vertical mixing, resulting in a scalar wind maximum. The vertical mixing and SF–SLP mechanisms are both at work but manifest more clearly at the synoptic time scale and in the long-term mean, respectively. The cross-frontal variations are 1.5 m s⁻¹ in both the scalar and vector wind speeds, representing the vertical mixing and SF–SLP effects, respectively. The results illustrate the utility of high-frequency sampling by satellite scatterometers.

Abstract

Two dominant high-frequency features of Northern Hemisphere summer climatology are examined in an atmosphere–land general circulation model (AGCM): the sudden onset of rains in south Asia, and the midsummer rainfall minimum in the tropical Americas. A control simulation succeeds in capturing these observed features fairly well. A slowed-calendar experiment is performed, to see whether these features are close to equilibrium with seasonally evolving forcings (orbital geometry and SST). The results indicate that some lag (disequilbrium) within the AGCM delays south Asian onset by about a month, from May in the experiment when seasonal forcing evolves extremely slowly to June in the normal, full-speed seasonal cycle. Disequilibrium also acts to delay and limit the amplitude of the Americas midsummer drought, and the associated intrusion of the Atlantic subtropical high into the Intra-Americas Seas’ region. It is hypothesized that early summer (centered on the solstice) temperature over mid- and high-latitude continents, which differs greatly between experiment and control, drives the low-latitude rainfall differences. A more mysterious pole-to-pole, annual-mean, zonal wave-1 difference is also found in the slowed-calendar experiment.