Search

To investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the subsequent winter precipitation in Southeast China (SEC), observed fields of monthly precipitation, sea surface temperature (SST) and atmospheric circulation are subjected to a running and a maximum correlation analysis. The results show a significant change of the relevance of IOD for the early modulation of SEC winter precipitation in the 1980s. After 1980, positive correlations suggest prolonged atmospheric responses to IOD forcing, which are linked to an abnormal moisture supply initiated in autumn and extended into the subsequent winter. Under global warming two modulating factors are relevant: (1) an increase of the static stability has been observed suppressing vertical heat and momentum transports; (2) a positive (mid-level) cloud-radiation feedback jointly with the associated latent heating (apparent moisture sink Q) explains the prolongation of positive as well as negative SST anomalies by conserving the heating (apparent heat source Q) in the coupled atmosphere-ocean system. During the positive IOD events in fall (after 1980) the dipole heating anomalies in the middle and lower troposphere over the tropical Indian Ocean are prolonged to winter by a positive mid-level cloud-radiative feedback with latent heat release. Subsequently, thermal adaptation leads to an anticyclonic anomaly over Eastern India overlying the anomalous cooling SST of the tropical Eastern Indian Ocean enhancing the moisture flow from the tropical Indian Ocean through the Bay of Bengal into South China, following the northwestern boundary of the anticyclonic circulation anomaly over east India, thereby favoring abundant precipitation in SEC. [ABSTRACT FROM AUTHOR]

ABSTRACT Precipitation in the Tibetan Plateau ( TP) reaches its peak in summer. The seasonal projection skill of a statistical downscaling model ( SDM) for summer precipitation in the TP was compared with that of direct model output. The SDM, which is based on canonical correlation analysis ( CCA), significantly increased the projection skill. The CCA reveals the flow patterns behind the seasonal projection skill of summer precipitation in the TP between 1961 and 2012 and quantifies its relative contributions. East Asia 500 hPa geopotential height ( ZG500), tropical Indian Ocean sea surface temperature ( SST) and east Asia 850 hPa meridional water vapour flux ( MWVF850), obtained from the Max Planck Institute Earth System Model, low-resolution ( MPI- ESM- LR) simulations for phase 5 of the Coupled Model Intercomparison Project under the representative concentration pathway ( RCP) 2.6, RCP4.5 and RCP8.5 scenarios are considered as potential predictors. The SDMs are established in 1961-2005, validated in 2006-2012 and applied in 2013-2100. The ensemble canonical correlation ( ECC) is also applied to improve projection skill. The following results are obtained: (1) The SDM projection skill for each predictor is higher than that of the MPI-ESM-LR climate model, and ECC performs even better. (2) Spatial correlation patterns of different predictors with influence on the TP are well recognized by CCA. The high relevance of ZG500 can be explained by the thermal adaptation theory, that of SST exhibits a canonical Indian Ocean Dipole mode, and MWVF850 shows a simple water vapour link. (3) The amount of summer precipitation in the TP will slightly decrease under RCP2.6 by −3.4 mm decade−1, whereas RCP4.5 and RCP8.5 reveal an increase by 2.4 and 18.4 mm decade−1, respectively. [ABSTRACT FROM AUTHOR]

Vegetation greenness distributions [based on remote sensing normalized difference vegetation index (NDVI)] and their change are analyzed as functional vegetation-climate relations in a two-dimensional ecohydrological state space spanned by surface flux ratios of energy excess (U; loss by sensible heat H over supply by net radiation N) versus water excess (W; loss by discharge Ro over gain by precipitation P). An ecohydrological ansatz attributes state change trajectories in (U, W) space to external (or climate) and internal (or anthropogenic) causes jointly with vegetation greenness interpreted as an active tracer. Selecting the Tibetan Plateau with its complex topographic, climate, and vegetation conditions as target area, ERA-Interim weather data link geographic and (U, W) state space, into which local remote sensing Global Inventory Modeling and Mapping Studies (GIMMS) data (NDVI) are embedded; a first and second period (1982-93 and 1994-2006) are chosen for change attribution analysis. The study revealed the following results: 1) State space statistics are characterized by a bimodal distribution with two distinct geobotanic regimes (semidesert and steppe) of low and moderate vegetation greenness separated by gaps at aridity D ~ 2 (net radiation over precipitation) and greenness NDVI ~ 0.3. 2) Changes between the first and second period are attributed to external (about 70%) and internal (30%) processes. 3) Attribution conditioned joint distributions of NDVI (and its change) show 38.2% decreasing (61.8% increasing) area cover with low (moderate) greenness while high greenness areas are slightly reduced. 4) Water surplus regions benefit most from climate change (showing vegetation greenness growth) while the energy surplus change is ambiguous, because ecohydrological diagnostics attributes high mountainous regions (such as the Himalayas) as internal without considering the heat storage deficit due to increasing vegetation. [ABSTRACT FROM AUTHOR]