Tropical Rain Measuring Mission Research Articles

The vertical structure of latent heating and its association with cloud types during the Indian summer monsoon

ABSTRACT In the present communication, using cloud-type distribution derived from CloudSat observations during the years 2006–2010 and vertical structure of LH derived from Tropical Rain Measuring Mission (TRMM) observations during the same period over the Indian summer monsoon (ISM) region, an attempt is made to relate the both. First, the regions where particular type of clouds forms predominantly are identified and then the LH profiles over those regions are associated with that particular cloud type. Using this approach, mean vertical structure of LH of Deep convective (DC) clouds over the Bay of Bengal (BoB) and Central India (CI) region, LH profile of Stratocumulus (Sc) and Cumulus (Cu) clouds over the Arabian Sea (ARB) and the Western Ghats (WG) region, respectively are constructed. The LH profile associated with DC clouds shows a broad distribution with a bimodal structure over the BoB and CI regions with peak value around 7 km. The LH profiles associated with Sc and Cu cloud types peak at lower height levels corresponding to shallow convection over ARB and WG regions. The significance of the present study lies in indirectly associating the observed vertical structure of LH with various types of clouds over the ISM region.

Applicability Evaluation of Multisource Satellite Precipitation Data for Hydrological Research in Arid Mountainous Areas

Global Satellite Mapping of Precipitation (GSMaP), Climate Hazards Group InfraRed Preconception with Station data (CHIRPS), Tropical Rain Measurement Mission Multisatellite Precipitation Analysis (TRMM 3B42 V7) and Rainfall Estimation from Soil Moisture Observations (SM2RAIN) are satellite precipitation products with high applicability, but their applicability in hydrological research in arid mountainous areas is not clear. Based on precipitation and runoff data, this study evaluated the applicability of each product to hydrological research in a typical mountainous basin (the Qaraqash River basin) in an arid region by using two methods: a statistical index and a hydrological model (Soil and Water Assessment Tool, SWAT). Simulation results were evaluated by Nash efficiency coefficient (NS), relative error (PBIAS) and determination coefficient (R2). The results show that: (1) The spatial distributions of precipitation estimated by these four products in the Qaraqash River basin are significantly different, and the multi-year average annual precipitation of GSMaP is 97.11 mm, which is the closest to the weather station interpolation results. (2) On the annual and monthly scales, GSMaP has the highest correlation (R ≥ 0.82) with the observed precipitation and the smallest relative error (BIAS < 6%). On the seasonal scale, the inversion accuracy of GSMaP in spring, summer and autumn is significantly higher than other products. In winter, all four sets of products perform poorly in estimating the actual precipitation. (3) Monthly runoff simulations based on SM2RAIN and GSMaP show good fitting (R2 > 0.6). In daily runoff simulation, GSMaP has the greatest ability to reproduce runoff changes. The study provides a reference for the optimization of precipitation image data and hydrological simulation in data-scarce areas.

Multidimensional evaluation of the TRMM 3B43V7 satellite-based precipitation product in mainland China from 1998-2016.

This study evaluates the applicability of the Tropical Rain Measurement Mission (TRMM) 3B43V7 product for use throughout mainland China. Four statistical metrics were used based on the observations made by rain gauges; these metrics were the correlation coefficient (R), the relative bias (RB), the root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE), and they were chosen to evaluate the performance of the 3B43V7 product at temporal and spatial scales. The results revealed that 3B43V7 performed satisfactorily on all timescales (R > 0.9 and NSE > 0.86); however, it overestimated the results when compared with the rain gauge observations in certain circumstances (RB = 9.7%). Monthly estimates from 3B43V7 were in agreement with rain gauge observations. 3B43V7 can effectively capture the seasonal patterns of precipitation characteristics over mainland China. However, 3B43V7 tends to register a greater overestimation of precipitation in the winter (RB = 14%) than in other seasons while showing greater consistency with the observations made by rain gauges during dry periods. The 3B43V7 product performs well in the eastern part of mainland China, while its performance is poor in the western part of mainland China. In terms of altitude, 3B43V7 performs satisfactorily in areas with moderate to low altitudes (when altitude < 3,500 m, R > 0.9, NSE > 0.8 and RB < 10.2%) but RB values increase with altitude. Overall, 3B43V7 had a favorable performance throughout mainland China.

Variability in Spatial Distribution of Precipitation Overall Rugged Topography of Lebanon, Using TRMM Images

Rain gages data represents limited spatial coverage, especially in rugged terrains like Lebanon. Other precipitation data sources are the developing satellite and radar technologies. In this study, Tropical Rain Measurement Mission (TRMM) monthly rainfall data of 18 years (1998-2014 and 2017) was used to understand monthly and yearly precipitation spatial distribution overall Lebanon. Topographic effect of rainfall spatial distribution was investigated in comparison to Plassard’s map of 1971. The annual precipitation over the country ranged between 850 mm and 200 mm that differs than the existing historical map. The maximum rainfall rate decreased by about 700 mm between the derived TRMM rainfall map and Plassard’s one. Spatial distribution of maximum precipitation rates does not coincide between maps. TRMM map of elevated terrains did not show similar trends of rainfall distribution as Plassard’s. Pixels (Lebanon was divided into 27 pixels) of lower rainfall rates was found toward the eastern side of Lebanon, in contrast to Plassard’s results. Anti-Lebanon did not show an increase in precipitation in accordance to altitude. Spatial variability of precipitation was about 50 mm between pixels which reveals the importance of considering topography while implemented rain gages as observation points. TRMM and satellite rainfall data aid in investigating complete spatial distribution of rainfall over continuous periods. Accumulating knowledge of spatial rainfall distribution on timely basis will lead to better future modelling on floods and drought conditions in Lebanon.

Estimating One-Minute Rain Rate Distributions in the Tropics From TRMM Satellite Data (October 2017)

Internationally recognized prognostic models of rain fade on terrestrial and Earth-space extremely high frequency (EHF) links rely fundamentally on distributions of 1-min rain rates. In Rec. ITU-R P.837-6, these distributions are estimated from the data provided by Numerical Weather Products (NWPs). NWP yields rain accumulations over regions typically larger than 100 km across and over intervals of 6 h. Over the tropics, the Tropical Rain Measuring Mission (TRMM) satellite data yield instantaneous rain rates over regions 5 km across. This paper uses TRMM data to estimate rain rate distributions for telecommunications regulation over the tropics. Rain rate distributions are calculated for each 1° square between 35° south to 35° north. These distributions of instantaneous rain rates over 5 km squares are transformed to distributions over 1 km squares using a correction calculated from U.K. Nimrod radar data. Results are compared to rain distributions in DBSG3, the database of ITU-R Study Group 3. A comparison with the new Rec. ITU-R P.837-7 is also presented. A table of 0.01% exceeded rain rates over the tropics is provided as associated data.

Exploring satellite based temporal forecast modelling of Aedes aegypti oviposition from an operational perspective

Aedes aegypti, responsible for the transmission of Chikungunya, Dengue, and Zika in Latin America, represents a large public health problem for the region. For this reason, several efforts have been made to use geospatial technologies to support vector control actions developed by the public health sector.Therefore, this study establishes the base for the application of freely available remotely sensed products to assess Ae. aegypti oviposition activity from an operational perspective for the entire north region of Argentina (region with a high risk of arbovirus transmission). In particular, we improve, in several aspects from an operative vision, previous studies with a concurrent objective.This study includes Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), day and night Land Surface Temperature (LST) from Moderate Resolution Imaging Spectroradiometer (MODIS, and Tropical Rain Measurement Mission (TRMM)) / Global Precipitation Measurement (GPM) as remotely sensed (RS) variables in addition to integral LST variables for modelling a set of four years of weekly oviposition data (August 2011 – July 2015).From an initial set of 42 variables (the original RS and their lags), a subset of 11 variables were selected and retained based on the correlation between them and the oviposition series. Using these data as independent variables, we develop temporal forecasting models of Ae. aegypti oviposition using a linear multivariate method, including its validation. Several models for different time periods were obtained and a final model with prediction capacity (R2 = 0.7, p < 0.05) was established.With these results, an improved, complete set of satellite derived variables was established as the basis for the national operational risk system that was already being used in Argentina which could be used for health decision makers to develop oriented control actions.

Assessment of Runoff Pattern and Relationship to Sediment Yield of Bhagirathi–Alaknanda River Basin Using Geospatial Techniques

Erosion has been as a major issue in Bhagirathi and Alaknanda river basins due to high surface runoff. The river basins are located in the Uttarakhand state of India and have a total basin area of 19,066.5 km2. Sediment yield has been estimated and then correlated with the surface runoff using geospatial techniques during the period 2000–2015. Analytic hierarchy process (AHP) has been used to estimate the sediment yield. All required layers for assessment of runoff and sediment yield has been prepared in a geographical information system environment. Tropical Rain Measuring Mission (TRMM) rainfall data (0.25° × 0.25°), Global Land Data Assimilation System (GLDAS) runoff data (0.25° × 0.25°), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) elevation data (30 m), and Landsat 5 and Landsat 8 satellite images (30 m) have been used to prepare rainfall maps, runoff maps, relief maps, and land use/land cover maps respectively. The study has shown that the sediment yield, as well as runoff, has a non-monotonic trend during 2000 to 2015. The highest runoff has been observed in the year 2013 whereas minimum runoff was in the year 2009. Correspondingly, the highest and lowest sediment yields were observed in the years 2013 and 2009 respectively. The northern part of the catchment was observed to be more vulnerable with respect to high sediment yield as well as runoff. As a whole, both river basins have a strong positive correlation between sediment yield and runoff with R2 values of 0.8. With respect to the findings, it can be concluded that some of the reservoirs for hydropower projects within these river basins may be in danger in the near future due to high sediment yields.

On the role of precipitation latent heating in modulating the strength and width of the Hadley circulation

The latent heat released in the clouds over the tropics plays a vital role in driving the Hadley circulation (HC). The present study discusses the influence of latent heating (LH) on the HC parameters viz., centre, strength and total width by using precipitation LH profiles derived from the space-borne observations of the Precipitation Radar (PR) onboard Tropical Rain Measuring Mission (TRMM) and meridional stream function (MSF) derived from ECMWF-Interim reanalysis. The latitude of peak latent heating, width of the latent heating distribution and the total LH released within the ascending limb of the HC are estimated and their influence on the HC centre, strength and width is quantified, for the first time. The present results show that the latitude of peak LH significantly influences the position of the HC centre with correlation coefficient of ~ 0.90. This high correlation between these two quantities seems to be due to their co-variability with the apparent motion of the Sun across the latitudes. The intensity of the HC in the NH as well as SH shows high correlation with the latitude of peak LH with coefficients − 0.85 and − 0.78, respectively. These results indicate that farther the latitude of peak LH from the equator in the summer hemisphere, stronger is the HC intensity in the winter hemisphere. The present analysis also reveals that the total LH released within the ascending limb of HC substantially influence the total width of the HC, with correlation coefficient ~ 0.52, as compared to the other two LH parameters. This observation can be attributed to the fact that the HC is sensitive to the latent heat release in the mid-tropospheric levels in the tropics. An attempt is also made to investigate the degree of variability of these parameters after deseasonalization and results are discussed in the light of present understanding. The significance of the present study lies in providing the observational evidence for the influence of latent heating on the HC strength/width variability, quantitatively, for the first time using TRMM observations of precipitation latent heating.

Implications of a decrease in the precipitation area for the past and the future

The total area with 24 hrs precipitation has shrunk by 7% between 50°S–50°N over the period 1998–2016, according to the satellite-based Tropical Rain Measurement Mission data. A decrease in the daily precipitation area is an indication of profound changes in the hydrological cycle, where the global rate of precipitation is balanced by the global rate of evaporation. This decrease was accompanied by increases in total precipitation, evaporation, and wet-day mean precipitation. If these trends are real, then they suggest increased drought frequencies and more intense rainfall. Satellite records, however, may be inhomogeneous because they are synthesised from a number of individual missions with improved technology over time. A linear dependency was also found between the global mean temperature and the 50°S–50°N daily precipitation area with a slope value of −17 × 106km2∕°C. This dependency was used with climate model simulations to make future projections which suggested a continued decrease that will strengthen in the future. The precipitation area evolves differently when the precipitation is accumulated over short and long time scales, however, and there has been a slight increase in the monthly precipitation area while the daily precipitation area decreased. An increase on monthly scale may indicate more pronounced variations in the rainfall patterns due to migrating rain-producing phenomena.

The Consistent Behavior of Tropical Rain: Average Reflectivity Vertical Profiles Determined by Rain Top Height

AbstractSixteen years of Tropical Rain Measuring Mission (TRMM) reflectivity profile data are collected for oceanic, continental, and island tropical regions within the boreal winter intertropical convergence zone (ITCZ). When sorted by the rain top height (RTH), a consistent behavior emerges where the average reflectivity profiles originating at different RTHs form non-overlapping manifolds in the height–reflectivity space, excluding the brightband regions for stratiform type profiles. Based on reflectivity slope (dBZ km−1) profile characteristics and physical considerations, the profiles are divided into three classes: 1) cold profiles, which originate above the −20°C isotherm height and display convergence to a single reflectivity slope profile independent of RTH; 2) warm profiles, which originate below the 0°C isotherm height and display strong reflectivity slope dependence on RTH, with slope values per RTH linearly decreasing with decreased height; and 3) mixed profiles, which originate at the layer located in between the lowest cold rain and highest warm rain profiles and show a gradual transition from cold profile to warm profile reflectivity slope behavior. Stratiform type profiles show similarity for all regions. It is shown that the typical tropical stratiform cold rain profile can be simply parameterized given the temperature profile. Convective type profiles present larger interregional differences. Their deviation from the typical stratiform cold rain profile is used as a measure for convective intensity, where continental and island regions show larger deviations compared to oceanic ones.

On validation of the rain climatic zone designations for Nigeria

In this paper, validation of rain climatic zone classifications for Nigeria is presented based on global radio-climatic models by the International Telecommunication Union-Radiocommunication (ITU-R) and Crane. Rain rate estimates deduced from several ground-based measurements and those earlier estimated from the precipitation index on the Tropical Rain Measurement Mission (TRMM) were employed for the validation exercise. Although earlier classifications indicated that Nigeria falls into zones P, Q, N, and K for the ITU-R designations, and zones E and H for Crane’s climatic zone designations, the results however confirmed that the rain climatic zones across Nigeria can only be classified into four, namely P, Q, M, and N for the ITU-R designations, while the designations by Crane exhibited only three zones, namely E, G, and H. The ITU-R classification was found to be more suitable for planning microwave and millimeter wave links across Nigeria. The research outcomes are vital in boosting the confidence level of system designers in using the ITU-R designations as presented in the map developed for the rain zone designations for estimating the attenuation induced by rain along satellite and terrestrial microwave links over Nigeria.

Evaluation of the WRF Weather Forecasts over the Southern Region of Brazil

The data assimilation technique, known as 3DVAR, of the WRF mesoscale modeling system has been used in order to perform the impact analysis of meteorological data assimilation in the weather forecasts over the Rio Grande do Sul State in Brazil. The consistency of the data assimilation has been analyzed by investigating and evaluating the model forecast results processed with and without data assimilations. Two different procedures of data assimilation have been conducted to perform the study. The forecasts of the accumulated rainfall model variable, spatially plotted over the model integration domains, have been compared and validated against the Tropical Rain Measuring Mission (TRMM) satellite based data, as well as with the Cangucu city meteorological radar reflectivity data. The comparison has been made considering the total amount of the accumulated rainfall predicted by the model against the automatic weather station data and most of the conducted processing presented compatible results. It has also been observed that, the inclusion of assimilated data enabled an improvement in the intensity as well as in the location of the main convective cell. The radar reflectivity field showed a significant performance in all processed experiments with data assimilation. However, for some regions, more significant obtained results have been shown to be the case in which the spectral radiances were assimilated, as compared with the case in which the spectral radiances were not included. The evaluation of the vertical atmospheric profiles of temperature and dew point temperature showed only a small impact of data assimilation. However, both simulations coherently presented the two vertical profiles, when compared with the observed profiles. In short, the study shows that, although the forecasts presented some inconsistencies in the evaluated results, the 3DVAR assimilation improves significantly the forecasting of the Weather WRF model.

Development of a High-Resolution Multiscale Modeling and Prediction System for Bay of Bengal, Part II: An Application to October 2008

A high-resolution (10 km × 10 km) multiscale ocean modeling system was developed for the Bay of Bengal (BOB) region for short-term ocean hindcasts/forecasts. A physical validation of this system that was based on climatological initialization and short-term simulations was presented in Part I of this series of studies. Realistic structures for prevalent eddies, fronts and gyres were reasonably reproduced and validated for three individual months (February, June and October). In this study, we present an application and synoptic validation of the system for October 2008 in a hindcast mode. The system is based on the Regional Ocean Modeling System (ROMS), which assimilates satellite and in-situ measurements within the background climatology using an objective analysis to produce the synoptic initial condition for the model and/or to produce an estimation of the current ocean state. A meteorological forecast is then input into this synoptic three-dimensional ocean model to produce the ocean hindcast/forecast. The high-density Array for Real-time Geotropic Oceanography (ARGO) observations, and the Tropical Rain Measuring Mission (TRMM) satellite’s microwave imager (TMI) passes during the beginning of the month of October 2008, provided a unique opportunity for the system to assimilate these in-situ observations at initialization. Then, the ARGO and TMI observations during the later part of October 2008 were used for the statistical validation of the system’s fidelity. The validation shows that the hindcast/forecast system can reasonably predict the ocean currents, temperature and salinity. The forecast error increases as the forecast time window increases, although the system has a reasonable predictability for up to seven to ten days. The assimilation of both in-situ ARGO and satellite data at initialization produced better hindcasts/forecasts.

New Possibilities for Geophysical Parameter Retrievals Opened by GCOM-W1 AMSR2

A new approach to retrieve sea surface wind speed (SWS) in tropical cyclones (TCs) from the Advanced Microwave Scanning Radiometer 2 (AMSR2) data is presented. Analysis of all six AMSR2 C- and X-band channel measurements over TCs is shown to efficiently help to separate the rain contribution. Corrected measurements at 6.9 and 10.65 GHz are then used to retrieve the SWS. Spatial and temporal collocation of AMSR2 and tropical rain measurement mission (TRMM) microwave instrument (TMI) data is then further used to empirically relate TMI rain rate (RR) product to RR estimates from AMSR2 in hurricanes. SWS estimates are validated with measurements from the stepped frequency microwave radiometer (SFMR). As further tested, more than 100 North Atlantic and North Pacific TCs are analyzed for the 2012–2014 period. Despite few particular cases, most SWS fields are in a very good agreement with TC center data on maximum wind speeds, radii of storm, and hurricane winds. As also compared, very high consistency between AMSR2 and L-band SMOS wind speed estimates are obtained, especially for the super typhoon Haiyan, to prove the high potential of AMSR2 measurements in TCs.

Validation of the New Algorithm for Rain Rate Retrieval from AMSR2 Data Using TMI Rain Rate Product

A new algorithm is derived for rain rate (RR) estimation from Advanced Microwave Sounding Radiometer 2 (AMSR2) measurements taken at 6.9, 7.3, and 10.65 GHz. The algorithm is based on the numerical simulation of brightness temperatures (TB) for AMSR2 lower frequency channels, using a simplified radiation transfer model. Simultaneous meteorological and hydrological observations, supplemented with modeled values of cloud liquid water content and rain rate values, are used for the calculation of an ensemble of AMSR2TBs and RRs. Ice clouds are not taken into account. AMSR2 brightness temperature differences at C- and X-band channels are then used as inputs to train a neural network (NN) function for RR retrieval. Validation is performed against Tropical Rain Measurement Mission (TRMM) Microwave Instrument (TMI) RR products. For colocated AMSR2-TMI measurements, obtained within 10 min intervals, errors are about 1 mm/h. The new algorithm is applicable for RR estimation up to 20 mm/h. ForRR&lt;2 mm/h the retrieval error is 0.3 mm/h. ForRR&gt;10 mm/h the algorithm significantly underestimates TMI RR.

Simulation of the West African monsoon onset using the HadGEM3-RA regional climate model

The performance of the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) in simulating the West African monsoon (WAM) is investigated. We focus on performance for monsoon onset timing and for rainfall totals over the June–July–August (JJA) season and on the model’s representation of the underlying dynamical processes. Experiments are driven by the ERA-Interim reanalysis and follow the CORDEX experimental protocol. Simulations with the HadGEM3 global model, which shares a common physical formulation with HadGEM3-RA, are used to gain insight into the causes of HadGEM3-RA simulation errors. It is found that HadGEM3-RA simulations of monsoon onset timing are realistic, with an error in mean onset date of two pentads. However, the model has a dry bias over the Sahel during JJA of 15–20 %. Analysis suggests that this is related to errors in the positioning of the Saharan heat low, which is too far south in HadGEM3-RA and associated with an insufficient northward reach of the south-westerly low-level monsoon flow and weaker moisture convergence over the Sahel. Despite these biases HadGEM3-RA’s representation of the general rainfall distribution during the WAM appears superior to that of ERA-Interim when using Global Precipitation Climatology Project or Tropical Rain Measurement Mission data as reference. This suggests that the associated dynamical features seen in HadGEM3-RA can complement the physical picture available from ERA-Interim. This approach is supported by the fact that the global HadGEM3 model generates realistic simulations of the WAM without the benefit of pseudo-observational forcing at the lateral boundaries; suggesting that the physical formulation shared with HadGEM3-RA, is able to represent the driving processes. HadGEM3-RA simulations confirm previous findings that the main rainfall peak near 10°N during June–August is maintained by a region of mid-tropospheric ascent located, latitudinally, between the cores of the African Easterly Jet and Tropical Easterly Jet that intensifies around the time of onset. This region of ascent is weaker and located further south near 5°N in the driving ERA-Interim reanalysis, for reasons that may be related to the coarser resolution or the physics of the underlying model, and this is consistent with a less realistic latitudinal rainfall profile than found in the HadGEM3-RA simulations.

Rain Height Statistics Based on 0°C Isotherm Height Using TRMM Precipitation Data for Earth-Space Satellite Links in Nigeria

In the prediction of attenuation due to precipitation related phenomena, the 0°C isotherm height plays a vital role. In this paper, 2 years of precipitation data obtained from the Tropical Rain Measuring Mission (TRMM) satellite had been analyzed to establish the distribution of rain height based on 0°C isotherm heights over six locations in Nigeria. Probability of exceedance of rain heights in each of the locations was compared between the two seasons in Nigeria. Rain heights distribution was also compared with the ITU-R P.839 recommendation. The overall results show seasonal, rainfall type’s dependence and overestimation of the rain height predicted by the ITU for Nigeria.

Validation of Satellite-Derived Daily Latent Heat Flux over the South China Sea, Compared with Observations and Five Products

Abstract This study describes the development of the South China Sea (SCS) daily satellite-derived latent heat flux (SCSSLH) for the period of 1998–2011 at 0.25° × 0.25° resolution using data mainly from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI). Flux-related variables of daily TMI data smoothed with 3-day running mean were finally chosen because of the best fit with the 1727 high-quality observations from seven moored stations and 24 ship surveys. Near-surface air specific humidity was computed using the global relationship based on satellite precipitable water. Verification against 1016 high-resolution radiosonde profiles from 1998 to 2012 and the time series from the Xisha automatic weather station during 2008–10 indicate that this satellite-derived air specific humidity can reasonably capture observed mean condition and temporal variability. They are therefore used to derive SCSSLH based on the Coupled Ocean–Atmosphere Response Experiment version 3.0 (COARE 3.0) algorithm. Compared with five other latent heat flux products—the Goddard Satellite-Based Surface Turbulent Fluxes version 2 (GSSTF2), the objectively analyzed air–sea heat fluxes (OAFlux), the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data version 3 (HOAPS3), the National Centers for Environmental Prediction/Department of Energy Global Reanalysis 2 (NCEP-2), and the European Centre for Medium-Range Weather Forecasts (ECMWF)—the daily SCSSLH shows the highest spatial resolution and realistic values in the SCS, with an exception along the northern continental shelf. More importantly, the other five products seem to overestimate the latent heat flux systematically. The flux representation in this study comes not only with a better flux algorithm but also with the improved estimates of bulk variables based on in situ measurements, which further highlights the unique role of high-quality meteorological measurements and atmospheric weather stations in evaluating the air–sea interaction in the SCS.

Hydrological differentiation and spatial distribution of high altitude wetlands in a semi-arid Andean region derived from satellite data

Abstract. High Altitude Wetlands of the Andes (HAWA) belong to a unique type of wetland within the semi-arid high Andean region. Knowledge about HAWA has been derived mainly from studies at single sites within different parts of the Andes at only small time scales. On the one hand, HAWA depend on water provided by glacier streams, snow melt or precipitation. On the other hand, they are suspected to influence hydrology through water retention and vegetation growth altering stream flow velocity. We derived HAWA land cover from satellite data at regional scale and analysed changes in connection with precipitation over the last decade. Perennial and temporal HAWA subtypes can be distinguished by seasonal changes of photosynthetically active vegetation (PAV) indicating the perennial or temporal availability of water during the year. HAWA have been delineated within a region of 12 800 km2 situated in the Northwest of Lake Titicaca. The multi-temporal classification method used Normalized Differenced Vegetation Index (NDVI) and Normalized Differenced Infrared Index (NDII) data derived from two Landsat ETM+ scenes at the end of austral winter (September 2000) and at the end of austral summer (May 2001). The mapping result indicates an unexpected high abundance of HAWA covering about 800 km2 of the study region (6 %). Annual HAWA mapping was computed using NDVI 16-day composites of Moderate Resolution Imaging Spectroradiometer (MODIS). Analyses on the relation between HAWA and precipitation was based on monthly precipitation data of the Tropical Rain Measurement Mission (TRMM 3B43) and MODIS Eight Day Maximum Snow Extent data (MOD10A2) from 2000 to 2010. We found HAWA subtype specific dependencies on precipitation conditions. A strong relation exists between perennial HAWA and snow fall (r2: 0.82) in dry austral winter months (June to August) and between temporal HAWA and precipitation (r2: 0.75) during austral summer (March to May). Annual changes in spatial extend of perennial HAWA indicate alterations in annual water supply generated from snow melt.

Comparing high-resolution gridded precipitation data with satellite rainfall estimates of TRMM_3B42 over Iran

Abstract. To evaluate satellite rainfall estimates of Tropical Rain Measurement Mission (TRMM) level 3 output (3B42) (TRMM_3B42) over Iran (20°–45° N, 40°–65° E), we compared these data with high-resolution gridded precipitation datasets (0.25°×0.25° latitude/longitude) based on rain gauges (Iran Synoptic gauges Version 0902 (IS0902)). Spatial distribution of mean annual and mean seasonal rainfall in both IS0902 and TRMM_3B42 from 1998 to 2006 shows two main rainfall patterns along the Caspian Sea and over the Zagros Mountains. Scatter plots of annual average rainfall from IS0902 versus TRMM_3B42 for each 0.25°×0.25° grid cell over the entire country (25°–40° N, 45°–60° E), along the Caspian Sea (35°–40° N, 48°–56° E), and over the Zagros Mountains (28°–37° N, 46°–55° E) were derived. For the entire country, the Caspian Sea region, and the Zagros Mountains, TRMM_3B42 underestimates mean annual precipitation by 0.17, 0.39, and 0.15 mm day−1, respectively, and the mean annual rainfall spatial correlation coefficients are 0.77, 0.57, and 0.75, respectively. The mean annual precipitation temporal correlation coefficient for IS0902 and TRMM_3B42 is ~0.8 in the area along the Zagros Mountains, and ~0.6 in the Caspian Sea and desert regions.