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Carlo Montes, Nachiketa Acharya, S. M. Quamrul Hassan, and Timothy J. Krupnik

Abstract

Extreme precipitation events are a serious threat to societal well-being over rainy areas such as Bangladesh. The reliability of studies of extreme events depends on data quality and their spatial and temporal distribution, although these subjects remain knowledge gaps in many countries. This work focuses on the analysis of four satellite-based precipitation products for monitoring intense rainfall events: the Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), the PERSIANN-Climate Data Record (PERSIANN-CDR), the Integrated Multisatellite Retrievals (IMERG), and the CPC Morphing Technique (CMORPH). Five indices of intense rainfall were considered for the period 2000-2019 and a set of 31 rain gauges for evaluation. The number and amount of precipitation associated with intense rainfall events are systematically underestimated or overestimated throughout the country. While random errors are higher over the wetter and higher-elevation north- and southeastern parts of Bangladesh, biases are more homogeneous. CHIRPS, PERSIANN-CDR and IMERG perform similar capturing total seasonal rainfall, but variability is better represented by CHIRPS and IMERG. Better results were obtained by IMERG, followed by PERSIANN-CDR and CHIRPS, in terms of climatological intensity indices based on percentiles, although the three products exhibited systematic errors. IMERG and CMORPH systematically overestimate the occurrence of intense precipitation events. IMERG showed the best performance representing events over a value of 20 mm/day; CMORPH exhibited random and systematic errors strongly associated with a poor representation of interannual variability in seasonal total rainfall. The results suggest that the datasets have different potential use and such differences should be considered in future applications regarding extreme rainfall events and risk assessment in Bangladesh.

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Sonali Shukla McDermid, Carlo Montes, Benjamin I. Cook, Michael J. Puma, Nancy Y. Kiang, and Igor Aleinov

Abstract

Modern agricultural land cover and management are important as regional climate forcings. Previous work has shown that land cover change can significantly impact key climate variables, including turbulent fluxes, precipitation, and surface temperature. However, fewer studies have investigated how intensive crop management can impact background climate conditions, such as the strength of land–atmosphere coupling and evaporative regime. We conduct sensitivity experiments using a state-of-the-art climate model with modified vegetation characteristics to represent modern crop cover and management, using observed crop-specific leaf area indexes and calendars. We quantify changes in land–atmosphere interactions and climate over intensively cultivated regions situated at transitions between moisture- and energy-limited conditions. Results show that modern intensive agriculture has significant and geographically varying impacts on regional evaporative regimes and background climate conditions. Over the northern Great Plains, modern crop intensity increases the model simulated precipitation and soil moisture, weakening hydrologic coupling by increasing surface water availability and reducing moisture limits on evapotranspiration. In the U.S. Midwest, higher growing season evapotranspiration, coupled with winter and spring rainfall declines, reduces regional soil moisture, while crop albedo changes also reduce net surface radiation. This results overall in reduced dependency of regional surface temperature on latent heat fluxes. In central Asia, a combination of reduced net surface energy and enhanced pre–growing season precipitation amplify the energy-limited evaporative regime. These results highlight the need for improved representations of agriculture in global climate models to better account for regional climate impacts and interactions with other anthropogenic forcings.

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Carlo Montes, José A. Rutllant, Anita Aguirre, Luisa Bascuñán-Godoy, and Cristóbal Juliá

Abstract

The terral de Vicuña is a warm and dry wind that flows down the Elqui Valley in north-central Chile typically at dawn and early morning. Given that most terral episodes occur in austral winter when chill accumulation by deciduous fruit trees proceeds, negative effects on agriculture may be expected. During 11 (2004–14) winters a meteorological characterization of terral winds and the assessment of their impact on chill accumulation, by the modified Utah Model and the Dynamic Model, were performed. Within this period, 67 terral days (TD) were identified as those in which nighttime to early morning wind direction and speed, air temperature, and relative humidity reached defined thresholds on an hourly basis (terral hours). Most frequent TD featured 6–9 consecutive terral hours; duration is considered here as a proxy for their intensity. Synoptic-scale meteorological analysis shows that 65% of moderate and strong terral events develop as a cold, migratory anticyclone drifts poleward of the study area, coinciding with the onset of a midtropospheric ridge over central Chile, bringing southwest winds on top of the Andes (~500-hPa level). The remaining 35% are either associated with 500-hPa easterlies (foehn like), with prefrontal conditions ahead of a trough driving northwest 500-hPa winds, or with transitional 500-hPa westerlies. Assessments of chill accumulation during TD show that, although present average and cold winter conditions do not represent a major TD hazard to local agriculture, lower chill accumulation associated with anomalously high nocturnal temperatures could be significantly more important during present and future warmer winters.

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