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A two-step attribution and causality diagnostic is designed by employing singular spectrum analysis to unfold the attributed climate time series into a trajectory matrix and then subjected to an empirical orthogonal function analysis to identify the evolving driving forces, which can finally be related to major climate modes through their independent frequencies by wavelet analysis. Application results from the arid and drought-prone southern Intermountain region of North America are compared with the climate or larger scale forcing diagnosed from slow feature analysis using the sources of the water and energy flux balance. The following results are noted: (i) The changes between the subsequent four 20-year periods from 1930 to 2010 suggest predominantly climate-induced forcing by the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation. (ii) Land cover influences on the changing land cover are of considerably smaller magnitude (in terms of area percentage cover) whose time evolution is well documented from forestation documents. (iii) The drivers of the climate-induced forcings within the last 20 years are identified as the quasi-biennial oscillation and the El Niño–Southern Oscillation by both the inter-annual two-step attribution and the causality diagnostics with monthly scale-based slow feature analysis. [ABSTRACT FROM AUTHOR]

Equatorial waves (EWs) are synoptic‐ to planetary‐scale propagating disturbances at low latitudes with periods from a few days to several weeks. Here, this term includes Kelvin waves, equatorial Rossby waves, mixed Rossby–gravity waves, and inertio‐gravity waves, which are well described by linear wave theory, but it also other tropical disturbances such as easterly waves and the intraseasonal Madden–Julian Oscillation with more complex dynamics. EWs can couple with deep convection, leading to a substantial modulation of clouds and rainfall. EWs are amongst the dynamic features of the troposphere with the longest intrinsic predictability, and models are beginning to forecast them with an exploitable level of skill. Most of the methods developed to identify and objectively isolate EWs in observations and model fields rely on (or at least refer to) the adiabatic, frictionless linearized primitive equations on the sphere or the shallow‐water system on the equatorial β$$ \beta $$‐plane. Common ingredients to these methods are zonal wave‐number–frequency filtering (Fourier or wavelet) and/or projections onto predefined empirical or theoretical dynamical patterns. This paper gives an overview of six different methods to isolate EWs and their structures, discusses the underlying assumptions, evaluates the applicability to different problems, and provides a systematic comparison based on a case study (February 20–May 20, 2009) and a climatological analysis (2001–2018). In addition, the influence of different input fields (e.g., winds, geopotential, outgoing long‐wave radiation, rainfall) is investigated. Based on the results, we generally recommend employing a combination of wave‐number–frequency filtering and spatial‐projection methods (and of different input fields) to check for robustness of the identified signal. In cases of disagreement, one needs to carefully investigate which assumptions made for the individual methods are most probably not fulfilled. This will help in choosing an approach optimally suited to a given problem at hand and avoid misinterpretation of the results. [ABSTRACT FROM AUTHOR]

The representation of tropical precipitation is evaluated across three generations of models participating in phases 3, 5, and 6 of the Coupled Model Intercomparison Project (CMIP). Compared to state-of-the-art observations, improvements in tropical precipitation in the CMIP6 models are identified for some metrics, but we find no general improvement in tropical precipitation on different temporal and spatial scales. Our results indicate overall little changes across the CMIP phases for the summer monsoons, the double-ITCZ bias, and the diurnal cycle of tropical precipitation. We find a reduced amount of drizzle events in CMIP6, but tropical precipitation occurs still too frequently. Continuous improvements across the CMIP phases are identified for the number of consecutive dry days, for the representation of modes of variability, namely, the Madden– Julian oscillation and El Niño–Southern Oscillation, and for the trends in dry months in the twentieth century. The observed positive trend in extreme wet months is, however, not captured by any of the CMIP phases, which simulate negative trends for extremely wet months in the twentieth century. The regional biases are larger than a climate change signal one hopes to use the models to identify. Given the pace of climate change as compared to the pace of model improvements to simulate tropical precipitation, we question the past strategy of the development of the present class of global climate models as the mainstay of the scientific response to climate change. We suggest the exploration of alternative approaches such as high-resolution storm-resolving models that can offer better prospects to inform us about how tropical precipitation might change with anthropogenic warming. [ABSTRACT FROM AUTHOR]

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]

Tropical SST anomalies are among the largest drivers of circulation regime changes on interannual time scales due to its characteristic heat capacity decay time scales. The circulation anomalies associated with extreme precipitation and the corresponding atmospheric response to SST anomalies are derived from ECMWF ERA-Interim reanalysis data by employing composite analysis and lagged maximum covariance analysis. Our results show that interannual variability of extreme winter precipitation in Southeast China is in close accordance with the interannual variability of total winter precipitation. Both are associated with similar abnormal circulation regimes, but for extreme precipitation events the circulation anomalies and moisture transport channels are significantly intensified. Two main moisture transport channels are captured: one extends from the North Indian Ocean through India and the Bay of Bengal to South China, and the other from the West Pacific Ocean through Maritime Continent and South China Sea towards South China, which are related to the preceding autumn SST patterns, El Niño and the Indian Ocean dipole (IOD), respectively. El Niño (La Niña) SST anomalies induce anomalous anticyclonic (cyclonic) circulation over Philippine Sea, which is favorable (unfavorable) to warm and humid air transport to South China from the tropical West Pacific by southwesterly (northeasterly) anomalies. Under these circulations, northeasterlies of East Asian Winter Monsoon are weakened (strengthened) resulting in extreme precipitation to be more (less) frequent in Southeast China. During the positive (negative) IOD phase, abundant (reduced) moisture transport to South China from tropical regions through India and Bay of Bengal is observed due to weakened (strengthened) Walker circulations and abnormal anticyclonic (cyclonic) circulation over India, leading to a higher (lower) likelihood for extreme precipitation events in Southeast China. The underlying physical mechanisms can be explained by a simplified one-dimensional vorticity equation (Sverdrup balance). [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]

Ensemble-Weighted Analogs (EWA) are introduced as an empirical forecast model for tropical cyclone (TC) tracks in the Australian basin extending to the Indian Ocean. The input requires only the 6 h positions of the preceding 24 hours to estimate the actual TC's future locations (up to 48 hours ahead) using optimally weighted ensemble members (analogs) from sections of historic cyclone tracks. They are determined as nearest neighbours of the actual track positions. After model calibration, independent forecasts are evaluated (2001-2007). The forecast analysis shows an error of about 140 km (for the 24 h prediction), which is better than the CLIPER reference forecast (161 km) and comparable to a numerical weather-prediction model (NWP of the UK Met Office). Intensity estimates and the forecast error-spread relation are discussed. Error-minimizing forecast combinations are also analysed: the EWA-NWP combination improves the individual 24 h NWP forecasts by about 25 km. Track cluster conditioned 24 h EWA forecasts are introduced providing probability estimates of hazardous areas. Finally, two cases of sudden track changes and their forecasts are presented with fields of position probabilities derived from the analog ensemble members and their clusters. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

A biased coinflip Ansatz provides a stochastic regional scale surface climate model of minimum complexity, which represents physical and stochastic properties of the rainfall-runoff chain. The solution yields the Schreiber-Budyko relation as an equation of state describing land surface vegetation, river runoff and lake areas in terms of physical flux ratios, which are associated with three thresholds. Validation of consistency and predictability within a Global Climate Model (GCM) environment demonstrates the stochastic rainfall-runoff chain to be a viable surrogate model for regional climate state averages and variabilites. A terminal (closed) lake area ratio is introduced as a new climate state parameter, which quantifies lake overflow as a threshold in separating water from energy limited climate regimes. A climate change analysis based on the IPCC A1B scenario is included for completeness. [ABSTRACT FROM AUTHOR]

Tropical cyclone tracks in the Australian basin are predicted by an analog ensemble forecast model. It is self-adapting in its search of optimal ensemble members from historic cyclone tracks by creating a metric that minimizes the error of the ensemble mean forecast. When compared with the climatology-persistence reference model, the adapted analog forecasts achieve great-circle errors that improve the reference model by 15%-20%. Ensemble mean forecast errors grow almost linearly with ensemble spread. [ABSTRACT FROM AUTHOR]