Implementation and evaluation of a double-plume convective parameterization in NCAR CAM5

Performance of global climate models (GCMs) is strongly affected by their cumulus parameterizations (CP) used. Similar to the approach in GFDL AM4, a double-plume CP, which unifies the deep and shallow convection in one framework, is implemented and tested in NCAR Community Atmospheric Model version 5 (CAM5). Based on the University of Washington (UW) shallow convection scheme, an additional plume was added to represent the deep convection. The shallow and deep plumes share the same cloud model, but use different triggers, fractional mixing rates and closures. The scheme was tested in single column, short-term hindcast and AMIP simulations. Compared with the default combination of Zhang-McFarlane scheme and UW scheme in CAM5, the new scheme tends to produce a top-heavy mass flux profile during the active monsoon period in the single column simulations. The scheme increases the intensity of tropical precipitation, closer to TRMM observations. The new scheme increased subtropical marine boundary layer clouds and high clouds over the deep tropics, both in better agreement with observations. Sensitivity tests indicate that regime dependent fractional entrainment rates of the deep plume are desired to improve tropical precipitation distribution and upper troposphere temperature. This study suggests that a double-plume approach is a promising way to combine shallow and deep convections in a unified framework.

Disentangling the effect of regional SST bias on the double-ITCZ problem

This study investigates the causes of the double intertropical convergence zone (ITCZ) bias by disentangling the individual contribution of regional sea surface temperature (SST) biases. We show that a previously suggested Southern Ocean warm bias effect in displacing the zonal-mean ITCZ southward is diminished by the southern midlatitude cold bias effect. The northern extratropical cold bias turns out to be most responsible for a southward-displaced zonal-mean precipitation, but the zonal-mean diagnostics poorly represent the spatial pattern of the tropical Pacific response. Examination of longitude-latitude structure indicates that the overall spatial pattern of tropical precipitation bias is largely shaped by the local SST bias. The southeastern tropical Pacific wet bias is driven by warm bias along the west coast of South America with negligible influence from the Southern Ocean warm bias. While our model experiments are idealized with ocean dynamics being absent, the results shed light on where preferential foci should be applied in model development to improve the certain features of tropical precipitation bias.

Optimal Geometric Characterization of Forced Zonal Mean Tropical Precipitation Changes.

The zonal and annual mean tropical precipitation response to paleoclimate and anthropogenic forcing scenarios ranging from the Last Glacial Maximum (LGM), CO2 quadrupling (4XCO2 ), mid-Holocene, North Atlantic freshwater hosing and volcanic forcing is analyzed in an ensemble of global climate models. Zonally averaged tropical precipitation changes are characterized in terms of three geometric manipulations of the climatological precipitation (hereafter, modes): meridional shifts, intensifications, and meridional contractions. We employ an optimization procedure that quantifies the magnitude and robustness (across different models) of changes in each mode in response to each forcing type. Additionally, the fraction of precipitation changes that are explained by the modes (in isolation and combined) is quantified. Shifts are generally less than 1º latitude in magnitude and explain a small fraction (<10%) of tropical precipitation changes. Contractions and intensifications are strongly anti-correlated across all simulations with a robust intensification and contraction of precipitation under global warming and a robust reduction and expansion under global cooling during the Last Glacial Maximum. The near constant scaling between contractions and intensifications across all simulations is used to define a joint contraction/intensification (CI) mode of tropical precipitation. The CI mode explains nearly 50% of the precipitation change under 4XCO2 and LGM forcing by optimizing a single parameter. These results suggest the shifting mode that has been extensively used to interpret paleo-rainfall reconstructions is of limited use for characterizing forced zonal mean precipitation changes and advocates for a reinterpretation of past precipitation changes to account for the CI mode

Trends of Hydroclimatic Intensity in Colombia

Prediction of precipitation changes caused by global climate change is a practical and scientific problem of high complexity. To advance, we look at the record of all available rain gauges in Colombia and at the CHIRPS database to estimate trends in essential variables describing precipitation, including HY-INT, an index of the hydrologic cycle’s intensity. Most of the gauges and cells do not show significant trends. Moreover, the signs of the statistically significant trends are opposite between the two datasets. Satisfactory explanation for the discrepancy remains open. Among the CHIRPS database’s statistically significant trends, the western regions (Pacific and Andes) tend to a more intense hydrologic cycle, increasing both intensity and mean dry spell length, whereas for the northern and eastern regions (Caribbean, Orinoco, and Amazon), the tendencies are opposite. This dipole in trends suggests different mechanisms: ENSO affects western Colombia more directly, whereas rainfall in the eastern regions depends more on the Atlantic Ocean, Caribbean Sea, and Amazon basin dynamics. Nevertheless, there is countrywide accord among gauges and cells with significant increasing trends for annual precipitation. Overall, these observations constitute essential evidence of the need for developing a more satisfactory theory of climate change effects on tropical precipitation.

Avocado cv. Hass Needs Water Irrigation in Tropical Precipitation Regime: Evidence from Colombia

The primary natural source of water for the Hass avocado crop in the tropics is precipitation. However, this is insufficient to provide most crops’ water requirements due to the spatial and temporal variability. This study aims to demonstrate that Hass avocado requires irrigation in Colombia, and this is done by analyzing the dynamics of local precipitation regimes and the influence of Intertropical Convergence Zone phenomena (ITCZ) on the irrigation requirement (IR). This study was carried out in Colombia’s current and potential Hass avocado production zones (PPA) by computing and mapping the monthly IR, and classifying months found to be in deficit and excess. The influence of ITCZ on IR by performing a metric relevance analysis on weights of optimized Artificial Neural Networks was computed. The water deficit map illustrates a 99.8% of PPA requires water irrigation at least one month a year. The movement of ITCZ toward latitudes far to those where PPA is located between May to September decreases precipitation and consequently increases the IR area of Hass avocado. Water deficit visualization maps could become a novel and powerful tool for Colombian farmers when scheduling irrigation in those months and periods identified in these maps.