Xiuhua Zhu

Precipitation climate of Central Asia and the large-scale atmospheric circulation

The precipitation climate in the larger Tian Shan region of Central Asia is described in terms of the climatological seasonal moisture fluxes and background circulation based on the ERA-40 reanalysis data and a precipitation reanalysis. The study area is partitioned into (1) the Tarim river basin, (2) bordering regions of China, Kyrgyzstan and Kazakhstan, and (3) Northwestern China. Moisture supply to these areas is primarily due to the midlatitude westerlies with contributions from higher latitudes. In addition, moisture from the Indian Ocean is notably imported into the Tarim drainage area. Monthly interannual precipitation variability relates to the variability of hemispheric circulation patterns. Extreme precipitation above and below normal in Western China and Central Asia is analyzed using the standardized precipitation index. Related circulation composites show that, despite regional and seasonal differences, episodes of extreme and severe dryness are dominated by various upstream standing wave patterns from the North Atlantic to Central Asia. These features extend further downstream to the North Pacific. Non-symmetry between wet and dry composites is noted upstream and in regional moisture flux composites.

Large-Scale Flow and the Long-Lasting Blocking High over Russia: Summer 2010

AbstractSeveral studies show that the anomalous long-lasting Russian heat wave during the summer of 2010, linked to a long-persistent blocking high, appears mainly as a result of natural atmospheric variability. This study analyzes the large-scale flow structure based on the ECMWF Re-Analysis Interim (ERA-Interim) data (1989–2010). The anomalous long-lasting blocking high over western Russia including the heat wave occurs as an overlay of a set of anticyclonic contributions on different time scales. (i) A regime change in ENSO toward La Nina modulates the quasi-stationary wave structure in the boreal summer hemisphere supporting the eastern European blocking. The polar Arctic dipole mode is enhanced and shows a projection on the mean blocking high. (ii) Together with the quasi-stationary wave anomaly, the transient eddies maintain the long-lasting blocking. (iii) Three different pathways of wave action are identified on the intermediate time scale (~10–60 days). One pathway commences over the eastern Nort...

Continuum climate variability: long-term memory, scaling, and 1/F-noise

Continuum temperature variability represents the response of the Earths climate to deterministic external forcing. Scaling regimes are observed which range from hours to millennia with low frequency fluctuations characterizing long-term memory. The presence of 1/f power spectra in weather and climate is noteworthy: (i) In the tropical atmosphere 1/f scaling ranging from hours to weeks is found for several variables; it emerges as superposition of uncorrelated pulses with individual 1/f spectra. (ii) The daily discharge of the Yangtze shows 1/f within one week to one year, although the precipitation spectrum is white. (iii) Beyond one year mid-latitude sea surface temperatures reveal 1/f scaling in large parts of the global ocean. The spectra can be simulated by complex atmosphere-ocean general circulation models and understood as a two layer heat diffusion process forced by an uncorrelated stochastic atmospheric. Long-term memory on time scales up to millennia are the global sea surface temperatures and the Greenland ice core records (GISP2, GRIP) with δ18O temperature proxy data during the Holocene. Complex atmosphere ocean general circulation models reproduce this behavior quantitatively up to millennia without solar variability, interacting land-ice and vegetation components.

A Demonstration of Long-Term Memory and Climate Predictability

Abstract Climate forecast skills are evaluated for surface temperature time series at grid points of a millennium control simulation from a state-of-the-art global circulation model [ECHAM5–Max Planck Institute Ocean Model (MPI-OM)]. First, climate predictability is diagnosed in terms of potentially predictable variance fractions and the fluctuation power-law exponent (using detrended fluctuation analysis). Long-term memory (LTM) with a fluctuation exponent (or Hurst exponent) close to 0.9 occurs mainly in high-latitude oceans, which are also characterized by high potential predictability. Next, explicit prediction experiments for various time steps are conducted on a gridpoint basis using an autocorrelation predictor. In regions with LTM, prediction skills are beyond that expected from red noise persistence—exceptions occur in some areas in the southern oceans and over the Northern Hemisphere continents. Extending the predictability analysis to the fully forced simulation shows a large improvement in pre...

Future Climates from Bias-Bootstrapped Weather Analogs: An Application to the Yangtze River Basin

Abstract The authors describe a statistical analog resampling scheme, similar to the “intentionally biased bootstrap,” for future climate projections whose only constraint is a prescribed linear temperature trend. It provides a large ensemble of day-to-day time series of single-station weather variables and other climatological observations at low computational cost. Time series are generated by mapping time sequences from the observed past into the future. The Yangtze River basin, comprising all climatological subregions of central China, is used as a test bed. Based on daily station data (1961–2000), the bootstrap scheme is assessed in a cross-validation experiment that confirms its applicability. Results obtained for the projected future climates (2001–40) include climatological profiles along the Yangtze, annual cycles, and other weather-related phenomena (e.g., floods, droughts, monsoons, typhoons): (i) the annual mean temperature and, associated with that, precipitation increase; (ii) the annual cyc...

Present and projected degree days in China from observation, reanalysis and simulations

Abstract Degree days are usually defined as the accumulated daily mean temperature varying with the base temperature, and are one of the most important indicators of climate changes. In this study, the present-day and projected changes of four degree days indices from daily mean surface air temperature output simulated by Max Planck Institute, Earth Systems Model of low resolution (MPI-ESM-LR) model are evaluated with the high resolution gridded-observation dataset and two modern reanalyses in China. During 1979–2005, the heating degree days (HDD) and the numbers of HDD (NHDD) have decreased for observation, reanalyses (ERA-Interim and NCEP/NCAR) and model simulations (historical and decadal experiments), consistent with the increasing cooling degree days (CDD) and the numbers of CDD (NCDD). These changes reflect the general warming in China during the past decades. In most cases, ERA-Interim is closer to observation than NCEP/NCAR and model simulations. There are discrepancies between observation, reanalyses and model simulations in the spatial patterns and regional means. The decadal hindcast/forecast simulation performance of MPI-ESM-LR produce warmer than the observed mean temperature in China during the entire period, and the hindcasts forecast a trend lower than the observed. Under different representative concentration pathway (RCP) emissions scenarios, HDD and NHDD show significant decreases, and CDD and NCDD consistently increase during 2006–2100 under RCP8.5, RCP4.5 and RCP2.6, especially before the mid-21 century. More pronounced changes occur under RCP8.5, which is associated with a high rate of radiative forcing. The 20th century runs reflect the sensitivity to the initial conditions, and the uncertainties in terms of the inter-ensemble are small, whereas the long-term trend is well represented with no differences among ensembles.

Future Climate in the Tibetan Plateau from a Statistical Regional Climate Model

The authors use a statistical regional climate model [Statistical Regional Model (STAR)] to project the Tibetan Plateau (TP) climate for the period 2015‐50. Reanalysis datasets covering 1958‐2001 are used as a substitute of observations and resampled by STAR to optimally fit prescribed linear temperature trends derived from the Max Planck Institute Earth System Model (MPI-ESM) simulations for phase 5 of the Coupled Model Intercomparison Project (CMIP5) under the representative concentration pathway 2.6 (RCP2.6)andRCP4.5scenarios.Toassesstherelateduncertainty, temperaturetrendsfromcarefullyselected best/worst ensemble members are considered. In addition, an extra projection is forced by observed temperaturetrendsin1958‐2001.Thefollowingresultsareobtained:(i)Spatialaveragetemperaturewillincrease by 0.68‐0.98C; the increase exceeds 18C in all months except in boreal summer, thus indicating a reduced annual cycle; and daily minimum temperature rises faster than daily maximum temperature, resulting in a narrowing of the diurnal range of near-surface temperature. (ii) Precipitation increase mainly occurs in early summer and autumn possibly because of an earlier onset and later withdrawal of the Asian summer monsoon. (iii) Both frost and ice days decrease by 1‐2 days in spring, early summer, and autumn, and the decrease of frost days on the annual course is inversely related to the precipitation increase. (iv) Degree-days increase all over the TP with peak amplitude in the Qaidam Basin and the southern TP periphery, which will result in distinct melting of the local seasonal frozen ground, and the annual temperature range will decrease with stronger amplitude in south TP.

Climate and Vegetation: An ERA-Interim and GIMMS NDVI Analysis

AbstractTo complement geographical presentation of remote sensing vegetation information, the authors apply Budyko’s physical state space diagram to analyze functional climate relations. As an example, the authors use Interim ECMWF Re-Analysis (ERA-Interim) global weather data to provide the statistics (1982–2006) of climate states in a two-dimensional state space spanned by water demand (net radiation N) versus water/energy limitation (dryness ratio D of net radiation over precipitation). Embedding remote sensing–based Global Inventory Modeling and Mapping Studies (GIMMS) data [normalized difference vegetation index (NDVI) > 0.1] shows the following results: (i) A bimodal frequency distribution of unit areas (pixels) is aligned near D ~ 1 but separated meridionally, associated with higher and lower net radiation. (ii) Vegetation states are represented as (N, D, NDVI) triplets that reveal temperate and tropical forests crossing the border (D ~ 1) separating energy- and water-limited climates but unexpecte...

Variability regimes of simulated Atlantic MOC

[1] The spectral variability structure of the meridional overturning circulation (MOC) of the Atlantic Ocean is determined in 500 year simulations with state-of-the-art coupled atmosphere-ocean general circulation models (GFDL and ECHAM5/MPIOM). The power spectra of the monthly stream function are compared with trend-eliminating detrended fluctuation analysis (DFA2). The shapes of the spectra differ substantially between latitudes, depth and the two models with constant (white) behaviour for high frequencies as a single common feature. The most frequent property of the spectra is power-law scaling, S(f) ∼f -β , with nontrivial exponents, mostly /3 ≈ 1, in agreement with 1/for flicker noise; this is mainly found in the interannual to decadal frequency range (1/f spectra observed for sea surface temperature fluctuations are explained by a stochastically forced ocean energy balance model with vertical diffusion). For lowest frequencies, some spectra show stationary long term memory, while others reveal spectra increasing with frequency. None of the spectra can be considered uniquely as red noise explained by an ocean integrating a white stochastic atmospheric forcing.

Interannual variability of winter precipitation in Southeast China

The observed winter (DJF) precipitation in Southeast China (1961–2010) is characterized by a monopole pattern of the 3-monthly Standardized Precipitation Index (SPI-3) whose interannual variability is related to the anomalies of East Asian Winter Monsoon (EAWM) systems. Dynamic composites and linear regression analysis indicate that the intensity of EAWM and Siberia High (SH), the position of East Asian Trough (EAT), and El Niño events and sea surface temperature (SST) anomalies over South China Sea (SCS) influence different regions of anomalous Southeast China winter precipitation on interannual scales. The circulation indices (EAWM index, SH index, and EAT index) mainly affect the winter precipitation in the eastern part of Southeast China. El Niño events affect the South China winter precipitation due to the anticyclone anomalies over Philippines. The effect of SCS SST anomalies on the winter precipitation is mainly in the southern part of Yangtze River. Thus, a set of circulation regimes, represented by a handful indices, provide the basis for modeling precipitation anomalies or extremes in future climate projections.