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There is limited understanding of how vegetation responds to intraseasonal modes of rainfall variability despite their importance in many tropical regions. We use observations of precipitation and X-band Vegetation Optical Depth (VOD) from 2000 to 2018 to assess the relationships between rainfall and vegetation water content on 25–60-day timescales. Cross-spectral analysis identifies coherent intraseasonal relationships between precipitation and VOD, mostly in arid or semi-arid regions where vegetation is water-limited. Changes in VOD tend to lag anomalous rainfall, usually within 7 days. The fastest vegetation response is observed in sparsely vegetated areas (median 3 days). Following strong intraseasonal wet events, anomalously high VOD can persist for 2 months after the rainfall peak. This vegetation response can feed back onto the atmosphere, so improved representation of vegetation responses in models has the potential to improve subseasonal-to-seasonal forecasts.

An understanding of where and how strongly the surface energy budget is constrained by soil moisture is hindered by a lack of large-scale observations, and this contributes to uncertainty in climate models. Here we present a new approach combining satellite observations of land surface temperature and rainfall.We derive a Relative Warming Rate (RWR) diagnostic, which is a measure of how rapidly the land warms relative to the overlying atmosphere during 10 day dry spells. In our dry spell composites, 73% of the land surface between 60°S and 60°N warms faster than the atmosphere, indicating water-stressed conditions, and increases in sensible heat. Higher RWRs are found for shorter vegetation and bare soil than for tall, deep-rooted vegetation, due to differences in aerodynamic and hydrological properties. We show how the variation of RWR with antecedent rainfall helps to identify different evaporative regimes in the major nonpolar climate zones.

Links between convergence and convection are poor in global models, and poor representation of convection is the source of many model biases in the tropics. State-of-the-art convection-permitting simulations allow us to analyze realistic convection statistically. The analysis of fractal dimension is used to show that in convection-permitting simulations (grid spacings 1.5, 4, and 12 km) of the West African monsoon, 50% of deep convective initiations occur in the near vicinity of low-level boundary layer convergence lines that are orientated along the mean wind. In these simulations, more than 80% of the initiations occur within large-scale (300 × 300 km) convergence, with some 20% in large-scale divergence, and almost all cases occur within local scale (60 × 60 km) convergence. The behavior alters in a simulation with a convection scheme and a grid spacing of 12 km; initiation is less frequent over convergence lines, and there is less dependency on high-magnitude low-level local convergence.

The validation of general circulation model (GCM) land surface schemes requires observations of energy and water fluxes averaged over an area of a typical GCM grid cell (100 km x 100 km) for a time period long enough to include the typical climatic conditions in that area. To create such a consolidated data set, soil moisture and surface evaporation are estimated with a detailed model of the surface energy and water balance. Observations from the Hydrological Atmospheric Pilot Experiment in the Sahel (HAPEX-Sahel) in Niger, West Africa, have shown that rainfall is a key source of spatial variability in the water and energy balance in semi arid regions. The model is therefore run for two wet seasons, forced by observations from a dense rain gauge network over an area of 10,000 km 2 . Analysis of the estimated surface fluxes indicates that bare soil evaporation has a strong influence on the spatial variability of evaporation during the wet season. On the other hand, leaf-level transpiration is relatively uniform and unstressed by soil moisture for most of the period. Modest spatial variability in transpiration develops through rainfall-induced contrasts in growth rates. The representation in GCMs of these moisture controls on evaporation can be problematic. In this case, where leaf area index is < 1, transpiration is well-represented by areal mean surface properties. However, an interactive growth model may be a useful component of the surface scheme when considering the large interannual rainfall variability typical of the Sahel. It is also found that the effect of spatial variability due to subgrid rainfall can not be ignored when modeling interception and bare soil evaporation. Methods of calculating mean fluxes based on mean moisture variables are therefore proposed. Using such a subgrid scheme, total evaporation errors are reduced by 50%.

This study examines thermally induced flows (or “snow breezes”) associated with snow cover in the boreal forests of Canada. Observations from a lake less than 4 km across were made as part of the Boreal Ecosystem-Atmosphere Study (BOREAS) winter field campaign. These are interpreted with the aid of idealized three-dimensional mesoscale model simulations representing the forest-lake contrast. Typically, strong forest-lake temperature contrasts develop in the lowest 50 m of the atmosphere during the morning. The resulting pressure gradients induce low-level onshore wind components across the lake. This snow breeze persists into the afternoon provided that large-scale winds remain light. A characteristic snow breeze signature is clearly evident in wind observations averaged over 27 days of data, in agreement with model simulations. The study suggests that snow breezes will regularly develop over the many larger lakes and other unvegetated areas in the region.

[1] Observed river gauging data show significant evaporative losses from the land and water surface in the Niger inland delta. These losses indicate an important potential feedback between the land surface and atmosphere. Moreover, the reduction in river flow downstream of the wetland has clear implications for water management in the region and beyond. Here we have modeled the evaporative losses that occur over the Niger inland delta by adding an overbank flow parameterization to the Joint UK Land-Environment Simulator (JULES) land surface model. The hydrological component of this model comprises a probability-distributed model of soil moisture and runoff production coupled with a discrete approximation to the one-dimensional kinematic wave equation to route river water downslope. We use subgrid-resolution topographic data to derive a two-parameter frequency distribution of inundated areas for each grid box which we then employ to represent overbank inundation in the model. The model was driven using data from the ALMIP experiment (ALMIP stands for AMMA Land surface Model Intercomparison Project, wherein AMMA stands for African Monsoon Multidisciplinary Analyses). The model reproduces the salient features of the observed river flow and inundation patterns; these include significant evaporative losses from the inundated region accounting for doubling of the total land-atmosphere water flux during periods of greatest flooding. Our predictions of inundated area are in good agreement with observed estimates of the extent of inundation obtained using satellite infrared and microwave remote sensing.

[1] The Niger Inland Delta in Mali floods every year in response to rain falling hundreds of kilometers upstream. This study examines the remote hydrological feedback between rainfall, fluvial inundation, and new convective storms. A satellite thermal infra-red dataset spanning 24 years is used to quantify both temporal variability in wetland extent, and the response of cloud cover to the wetland during August and September. The daytime initiation of convective storms is found to double during periods of inundation, consistent with a hypothesised “wetland breeze” effect. A signal of enhanced cloud cover propagates hundreds of kilometers westwards, linked to increased numbers of long-lived Mesoscale Convective Systems emanating from the wetland region. This effect raises the possibility that changes in upstream water use could have a climatic impact over a wide area.

This study uses aircraft observations over the Republic of Benin from the African Monsoon Multidisciplinary Analyses (AMMA) campaign to investigate the impact of vegetation heterogeneities on the dynamics within the planetary boundary layer, such as convection, transport, and mixing. Isoprene, a biogenic volatile organic compound emitted primarily by woody vegetation, was used as a tracer for transport to link the land surface to the boundary layer properties. Associated to planetary boundary layer (PBL) temperature gradients at vegetation boundaries, a persistent mesoscale organization of the winds which controlled patterns in the formation of cumulus congestus clouds was observed. A strong relationship among PBL temperatures, meridional wind velocity, isoprene concentrations, and fraction of forest or shrub cover was found, corroborating the land surface forcing of the observed dynamics. The observations show that the convergence zones tended to occur on the southern edge of warm surface and atmospheric anomalies. The northerly synoptic wind appears to have increased the coherency of the southerly part of the mesoscale flow and displaced the convergence zones southward. The relationships between the PBL potential temperatures and the meridional wind and isoprene concentrations were spatially coherent down to wavelengths of 10 and 8 km, respectively. A seasonal climatology of visible satellite data shows enhanced cloud cover in the afternoon over cropland, suggesting that the results presented are not limited to this case study but are of climatological significance in the region.

In situ observations from a flight made during the Geostationary Earth Radiation Budget Intercomparison of Longwave and Shortwave Radiation (GERBILS) field campaign (June 2007) show significant dust uplift into the monsoon flow immediately south of the intertropical discontinuity in the western Sahara. Dust loadings were highest in the moist monsoon air and the observations are consistent with dust uplift by the nocturnal monsoon winds. There is some evidence that cold pools within the monsoon flow contributed to the dust uplift: regions of elevated dust, water vapor, and ozone within the monsoon air are consistent with precipitation cooling and moistening air from upper levels and the resultant dusty cold pools propagating northward. However, only southward propagating cold pool outflows could be observed in satellite imagery. Using European Centre for Medium-Range Weather Forecasts analyses and satellite data, it is shown that the asymmetry in the seasonal dust cycle is closely related to the downdraft convective available potential energy (DCAPE) from convective storms. There is both more dust and more DCAPE during monsoon onset than during retreat. The larger DCAPE values during monsoon onset, as well as the stronger nocturnal monsoon flow and the stronger heat trough circulation, are expected to contribute to the higher dust loadings at this time. Both the monsoon flow and cold pool outflows within it result in dust uplift in the western Sahara during the monsoon onset, which is when the maximum dust uplift occurs. For dust modeling, this shows the importance of accurately modeling not only the monsoon flow itself but also deep convection and cold pools.

[1] Numerical and theoretical studies have shown that mesoscale gradients in land surface properties can induce circulations in the atmosphere. This study provides the first well-resolved observations of such flows induced by soil moisture from recent rainfall, and is based on aircraft data in the Sahel. Satellite imagery was used to identify fine scale soil moisture features within a wet zone spanning 160 km. Above the wet soil, the planetary boundary layer was up to 3 K cooler, 3 gkg−1 moister and extended to only half the depth of nearby drier areas. Mesoscale perturbations to the background flow were found, consistent with low level divergence over wet soil and convergence in drier areas. The soil moisture and atmospheric wind patterns were statistically coherent on wavelengths down to 20 km. These results suggest that mesoscale convergence lines forced by soil moisture may play a significant role in the meteorology of the Sahel.

[1] Forest fires in Siberia have a significant effect on the global carbon balance. It is therefore of interest to study the environmental factors that may be responsible for their variability. Here we examine variability in the annual number of forest fire scars at a spatial scale of 2.5°. This is decomposed statistically into a spatio–temporal component correlated with low summer rainfall, a spatial component correlated with population density and a temporal component correlated with the Arctic Oscillation. Data come from ten years of satellite–derived data, incorporating both the number of forest fire scars and monthly rainfall. The expected number of fire scars halves for each additional 0.35 mm per day of rainfall in the period April–July. Our findings may prove useful in parameterising both fire models within climate simulations and fire warning systems based on numerical weather predictions of regional dry anomalies.

[1] Understanding of interactions between soil moisture and precipitation is limited by a lack of direct observations at spatial scales on which feedbacks occur. This study identifies a sensitivity of convective cloud to spatial variations in soil moisture, based on analysis of satellite observations from many cases in the Sahel. Patches of wet soil were located using passive microwave data. The patches were composited according to length scale, ranging from 37 to 200 km. The response of the convective cloud field to surface variability along the composite cross-section was studied with thermal infra-red data. A suppression of convective cloud is evident over the wet soil during the afternoon and evening for all but the smallest length scales. Analysis of over 100 individual cases where convection occurred in the vicinity of a patch revealed that the development of cloud systems in their early stages appears to be particularly sensitive to soil moisture.